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M2180-759 | IBM Connectivity and Integration Sales Mastery v1

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M2180-759 - IBM Connectivity and Integration Sales Mastery v1 - braindump

Vendor IBM
Exam Number M2180-759
Exam Name IBM Connectivity and Integration Sales Mastery v1
Questions 36 Q & A
Recent Update February 12, 2019
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M2180-759 exam Dumps Source : IBM Connectivity and Integration Sales Mastery v1

Test Code : M2180-759
Test Name : IBM Connectivity and Integration Sales Mastery v1
Vendor Name : IBM
Q&A : 36 Real Questions

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IBM IBM Connectivity and Integration

accurate cloud providers 2019: AWS, Microsoft Azure, Google Cloud; IBM makes hybrid movement; Salesforce dominates SaaS | killexams.com Real Questions and Pass4sure dumps

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The paintings Of The Hybrid Cloud

Cloud computing is insatiably gobbling up greater of the backend capabilities that vigor companies. however, some businesses have apps with privateness, security, and regulatory calls for that avert the cloud. right here's the way to discover the right mix of public cloud and private cloud.

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The suitable cloud providers for 2019 have maintained their positions, however the subject matters, techniques, and processes to the market are all in flux. The infrastructure-as-a-carrier wars were largely determined, with the spoils going to Amazon web features, Microsoft Azure, and Google Cloud Platform, however new technologies comparable to synthetic intelligence and desktop gaining knowledge of have opened the container as much as other players.

in the meantime, the cloud computing market in 2019 can have a decidedly multi-cloud spin, because the hybrid shift through avid gamers corresponding to IBM, which is acquiring crimson Hat, could trade the landscape. This year's edition of the precise cloud computing providers also features software-as-a-service giants with a purpose to increasingly run extra of your commercial enterprise's operations by means of expansion.

One thing to word in regards to the cloud in 2019 is that the market is never zero sum. Cloud computing is using IT spending common. as an example, Gartner predicts that 2019 global IT spending will enhance 3.2 percent to $3.seventy six trillion with as-a-provider models fueling every little thing from facts center spending to commercial enterprise utility.

actually, or not it's quite feasible that a big business will consume cloud computing services from every supplier in this ebook. The actual cloud innovation may be from purchasers that mix and in shape right here public cloud carriers in exciting ways.

Key 2019 subject matters to monitor among the many correct cloud providers consist of:

  • Pricing energy. Google recently raised expenditures of G Suite and the cloud space is a technology the place add-ons exist for many new applied sciences. whereas compute and storage services are often a race to the backside, equipment for laptop discovering, artificial intelligence and serverless services can add up. there's an outstanding motive that cost administration is such a large theme for cloud computing consumers--it be arguably the greatest challenge. look for can charge administration and considerations about lock-in to be huge issues.
  • Multi-cloud. A recent survey from Kentik highlights how public cloud shoppers are more and more using multiple dealer. AWS and Microsoft Azure are most frequently paired up. Google Cloud Platform is additionally within the combine. And naturally these public cloud carrier suppliers are often tied into latest facts middle and private cloud assets. Add it up and there is a in shape hybrid and private cloud race underway and that is the reason reordered the pecking order. The multi-cloud strategy is being enabled by digital machines and containers.
  • artificial intelligence, information superhighway of things and analytics are the upsell technologies for cloud carriers. Microsoft Azure, Amazon internet capabilities and Google Cloud Platform all have equivalent innovations to land valued clientele with compute, cloud storage, serverless capabilities after which upsell you to the AI that'll differentiate them. agencies like IBM wish to control AI and cloud features across dissimilar clouds.
  • The cloud computing panorama is maturing impulsively yet monetary transparency backslides. it's telling when Gartner's Magic Quadrant for cloud infrastructure goes to six gamers from greater than a dozen. additionally, transparency has deteriorate among cloud computing suppliers. as an instance, Oracle used to break out infrastructure-, platform- and utility-as-a-service in its monetary stories. today, Oracle's cloud enterprise is lumped together. Microsoft has a "industrial cloud" that is terribly successful, however also difficult to parse. IBM has cloud salary and "as-a-carrier" earnings. Google doesn't break out cloud profits in any respect. other than AWS, parsing cloud earnings has become greater problematic.
  • To that end, we're taking a special approach to our cloud buying ebook and breaking the players into the big four infrastructure suppliers, the hybrid gamers, and the SaaS crowd. This categorization has pushed IBM from being a large infrastructure-as-a-carrier participant to a tweener that spans infrastructure, platform, and utility. IBM is more private cloud and hybrid with hooks into IBM Cloud in addition to different cloud environments. Oracle Cloud is essentially a utility- and database-as-a-carrier issuer. Salesforce has develop into about manner greater than CRM.

    must examine
  • 2018 Annual income: $25.sixty five billion
  • Annual revenue run expense in accordance with latest quarter: $29.seventy two billion
  • AWS sees 2019 as an investment 12 months, because it ramps its technology buildout in addition to add income personnel. Amazon did not quantify the larger funding, but pointed out it could replace all the way through the year.

    On a conference name with analysts, CFO Brian Olsavsky pointed out 2018 become a lighter than expected 12 months for capital expenditures. "AWS maintained a really potent growth fee and persisted to deliver for shoppers," he said. "2018 became about banking the efficiencies of investments in americans, warehouses, infrastructure that we had put in vicinity in 2016 and '17."

    The cloud provider is the chief in infrastructure-as-a-carrier and moving up the stack to everything from the internet of things to artificial intelligence, augmented fact, and analytics. AWS is way over an IaaS platform at the moment.  AWS grew 45 p.c in the fourth quarter -- a clip that has been sturdy for the last year.

    When it comes to developers and ecosystem, AWS is complicated to exact. The business has a wide array of partners (VMware, C3, and SAP) and developers turning out to be the ecosystem. AWS is customarily the primary beachhead for business gamers before they expand to a multi-cloud approach.

    The large question is how some distance AWS can lengthen its attain. AWS can be a threat to Oracle on databases in addition to a bevy of other businesses. via its VMware partnership, AWS also has a robust hybrid cloud method and may meet business needs multiple ways.

    AWS' strategy was evident at its re:Invent conference. The demonstrate featured a barrage of features, new items, and developer sweets that become difficult to track. synthetic intelligence is a key enviornment of increase and a core income pitch for AWS because it turns into a machine studying platform. in accordance with 2nd Watch, AWS purchasers are going for these excessive-boom areas and seeing the cloud company as a key cog for their computing device researching and digital transformation efforts.

    need to read

    2nd Watch found that AWS' 2018 fastest growing functions had been here:

  • Amazon Athena, with a 68-percent compound annual boom fee (measured by bucks spent with 2nd Watch) versus a year ago)
  • Amazon Elastic Container carrier for Kubernetes at 53 percent
  • Amazon MQ at 37 %
  • AWS OpsWorks at 23 p.c
  • Amazon EC2 Container provider at 21 p.c
  • Amazon SageMaker at 21 percent
  • AWS certificate supervisor at 20 p.c
  • AWS Glue at 16 p.c
  • Amazon GuardDuty at sixteen p.c
  • Amazon Macie at 15 p.c
  • in accordance with 2nd Watch usage, the most regularly occurring AWS capabilities are:

  • Amazon virtual deepest Cloud
  • AWS statistics switch
  • Amazon elementary Storage provider
  • Amazon DynamoDB
  • Amazon Elastic Compute Cloud
  • AWS Key management provider
  • AmazonCloudWatch
  • Amazon standard Notification provider
  • Amazon Relational Database service
  • Amazon Route 53
  • Amazon basic Queue carrier
  • AWS CloudTrail
  • Amazon fundamental e mail carrier
  • additionally: What serverless architecture in reality capacity, and the place servers enter the image

    Analytics and forecasting can be one area price observing for AWS. As AWS rolls out its forecasting and analytics functions, it's clear that the enterprise can turn into greater intertwined with true business capabilities. 

    aws-forecast-integration.png (image: ZDNet)

    AWS' attain continues to expand in distinctive instructions, but in all probability the one to observe essentially the most is the database market. AWS is shooting greater database workloads and has emphasised its consumer wins. A stream to launch a completely managed doc database takes direct intention at MongoDB. should still AWS trap more business records, it might be entrenched for many years to return because it continues to evolve services and promote them to you. 

  • industrial cloud annual profits run price as of newest quarter: $36 billion
  • Estimated Azure annual income run fee: $11 billion
  • Microsoft Azure is the solid No. 2 to AWS, however's elaborate to without delay evaluate the two companies. Microsoft's cloud enterprise -- dubbed commercial cloud -- includes every little thing from Azure to office 365 business subscriptions to Dynamics 365 to LinkedIn services. even so, Microsoft's robust business heritage, application stack, and statistics center tools like home windows Server provide it a familiarity and hybrid method that wears smartly.

    msft-q2-2019-commercial-cloud.png

    msft-q2-2019-commercial-cloud.png

    (picture: Microsoft)

    For differentiation, Microsoft has concentrated closely on AI, analytics, and the internet of issues. Microsoft's AzureStack has been an extra cloud-meets-data core effort that has been a differentiator.

    ought to read

    CEO Satya Nadella, on Microsoft's second quarter income convention call, stated the company's cloud unit is honing in on verticals corresponding to healthcare, retail, and monetary capabilities. This method comes appropriate out of the business utility selling playbook. 

    Nadella said:

    From a mix of functions, it starts all the time with, i'd say, infrastructure. So this is the facet and the cloud, the infrastructure being used as compute. in reality, you could say the measure of a company going digital is the amount of compute they use. So this is the bottom. Then on accurate of that, of direction, all this compute capability it be getting used with facts. So the data property, one of the crucial largest things that occurs, is americans consolidate the records that they've and which will purpose over it.  and that's where issues like AI services all get used. So we truly see that direction the place they're adopting the layers of Azure.

    effectively put, Microsoft is selling a wide array of cloud products, however it's complicated to escape utility-as-a-provider versus Azure, which would greater directly compete with AWS.

    Macquarie estimates that Azure earnings in Microsoft's fiscal second quarter became $2.75 billion for an annualized run rate of about $eleven billion. Sarah Hindlian, an analyst at Macquarie, said in a analysis word:

    Microsoft has been capable of differentiate Azure in several critical ways, such because the enterprise being both business friendly and aggressive in layering in pleasing and incremental services akin to artificial Intelligence, Azure Stack, Azure Sphere, and a vast center of attention on edge computing and greater superior and complicated workloads.

    indeed, Microsoft's potential to target industries has also been a win. specially, Microsoft has received over colossal dealers that don't are looking to companion with AWS for the reason that they compete with Amazon. Microsoft additionally started highlighting extra customer wins including gap as well as Fruit of the Loom.

    That take became also echoed somewhere else. Daniel Ives, an analyst at Wedbush, mentioned AWS is still the massive dog, however Microsoft has some pleasing benefits within the box -- especially a strong firm and ground online game. Ives wrote:

    while Jeff Bezos and AWS proceed to naturally be an incredible drive in the rising cloud shift over the coming years, we consider Microsoft with its military of partners and dedicated earnings force have an incredible window of probability in 2019 to transform firms to the Azure/cloud platform according to our fresh in-depth discussions with companions and valued clientele.

    without difficulty put, Microsoft can couple Azure with its other cloud features corresponding to office 365 and Dynamics 365. With Azure, Microsoft has a neatly-rounded stack, ranging from infrastructure to platform to functions to run a business.

    need to read
  • Annual revenue run price: $four billion+
  • Google Cloud Platform has been winning bigger offers, has a brand new leader with Oracle veteran Thomas Kurian and is seen as a fantastic counterweight to AWS and Microsoft Azure. youngsters, Google isn't divulging annual earnings run fee or offering a lot counsel on its cloud financials.

    On Google's fourth quarter earnings conference name, CEO Sundar Pichai mentioned a large number of data facets for Google Cloud Platform (GCP). however, analysts have been frustrated through the inability of profits disclosed. To kick off 2018, Pichai talked about Google's cloud revenue became $1 billion a quarter evenly cut up between G Suite and GCP.

    In 2019, Pichai held returned on his run rate chatter, so it's doubtful even if GCP is gaining on AWS or Azure or just turning out to be since the usual cloud pie is becoming. particularly, Pichai outlined the following:

  • The variety of Google Cloud Platform (GCP) deals price more than $1 million doubled.
  • The number of multiyear contracts doubled. "We're getting tremendous wins, and that i seem to be forward to executing here," mentioned Pichai.
  • G Suite has 5 million paying purchasers.
  • there's an uptick in the number of deals price greater than $100 million.
  • CFO Ruth Porat noted:

    GCP does continue to be one of the crucial quickest-starting to be organizations throughout Alphabet. As Sundar said, we have doubled the number of GCP contracts stronger than $1 million. We're additionally seeing early first-class uptick within the number of deals that are enhanced than $one hundred million, and truly completely satisfied with the success and penetration there. At this point, not updating extra.

    Add it up, and GCP appears to be an effective No. three to AWS and Azure, but how distant it falls behind these two is still to be seen. Wall street company Jefferies is predicting that GCP will benefit share over time.

    cloud-estimated-market-share-0818.png

    cloud-estimated-market-share-0818.png

    (image: Jefferies)

    One movement that may boost Google's cloud revenue is a stream to raise G Suite expenditures for some users. G Suite, which competes directly with Microsoft's office 365, is elevating its prices for the first time. G Suite simple will carry expenditures from $5 per user per 30 days to $6. G Suite company will go from $10 per user monthly to $12. according to Google, G Suite business, which runs $25 per consumer a month, isn't impacted through the rate enhance.

    Competitively, the pricing strikes are in keeping with workplace 365.

  • Annual profits run expense: $3.85 billion
  • Alibaba is the leading cloud company in China and an option for multi-national agencies constructing infrastructure there.

    In its December quarter, Alibaba delivered cloud salary boom of 84 % to $962 million. The business has abruptly brought valued clientele and is at present within the cloud buildout phase. To wit:

    Add it up, and Alibaba has a powerful home-box talents in China, nonetheless it additionally has international ambitions. Alibaba launched 678 products within the December quarter. Relationships with the likes of SAP are more likely to put it on the radar for greater organisations with operations in China.

    while the huge cloud providers add greater to their stacks with AI as the differentiator, there is a market being carved out to manage distinct cloud providers. This crowd of cloud players used to focus on hybrid structure to bridge facts facilities with public service suppliers, but now aim to be the infrastructure management aircraft.

    also: What Kubernetes basically is, and how orchestration redefines the records core

    analysis by way of Kentik highlighted how essentially the most standard cloud mixture turned into AWS and Azure, but there are valued clientele working in Google Cloud Platform, too. in accordance with the Kentik survey, 97 percent of respondents said their corporations use AWS, however 35 percent additionally mentioned they actively use Azure too. Twenty-4 percent use AWS and Google Cloud Platform together.

    kentik-report-2019.png

    kentik-report-2019.png

    (image: Kentik)

    additionally: What a hybrid cloud is within the 'multi-cloud era,' and why you might also have already got one 

  • Annualized as-a-carrier run rate: $12.2 billion
  • IBM's cloud method and its approach to AI have an awful lot in commonplace. huge Blue's plan is to permit purchasers to control diverse programs, capabilities and providers and become the administration console. IBM desires to be a part of your cloud atmosphere as well as assist you run it. In 2018, IBM launched OpenScale for AI, which is designed to manage diverse AI tools possible offered through the foremost cloud providers. IBM additionally launched multi-cloud equipment. feel of IBM because the Switzerland of cloud adoption and computing services concepts.

    The movement through businesses to use multiple public cloud providers is wonderful and gives the purpose for IBM's acquisition of pink Hat for $34 billion. IBM has its personal public cloud and will bring every little thing from platform-as-a-provider to analytics to Watson and even quantum computing through it, however the large guess is that huge Blue with purple Hat can make it a leading cloud administration player. For its half, IBM is taking its core intellectual property -- Watson, AI administration, cloud integration -- and delivering it through distinctive clouds.

    The red Hat acquisition is a chance the farm stream by using IBM. It remains to be considered how the IBM and crimson Hat cultures come together. On the vivid side, both corporations have been hybrid cloud partners for years.

    should study

    indeed, IBM CFO James Kavanaugh on the company's fourth quarter salary conference name reiterated the pink Hat reasoning and stated huge Blue is seeing extra offers for IBM Cloud private and its method to "hybrid open" cloud environments. Kavanaugh added:

    Let me pause right here to remind you of the value we see from the mixture of IBM and pink Hat, which is all about accelerating hybrid cloud adoption. The client response to the announcement has been overwhelmingly nice. They take into account the power of this acquisition and the mixture of IBM and red Hat capabilities in assisting them move past their preliminary cloud work to really shifting their company purposes to the cloud. they are concerned about the at ease portability of statistics and workloads throughout cloud environments, about consistency in administration and safety protocols throughout clouds and in warding off seller lock-in. They take note how the mixture of IBM and purple Hat will help them tackle these issues.

    also: The AI, machine gaining knowledge of, and statistics science conundrum: Who will control the algorithms? 

    IBM's as-a-carrier income run rate exiting the fourth quarter was $12.2 billion to make it a powerful cloud issuer, however not comparable to the likes of AWS and Azure these days. it is quite viable that the ideas of the entire significant cloud providers subsequently converge.

    the new hybrid and multi-cloud landscape may be some of the more critical issues to observe within the cloud wars for 2019. 

    listed here are some key players to agree with:

    VMware: It is part of the Dell technologies portfolio, and it has had natural records centers within the fold for years. The enterprise emerged as a virtualization seller and then adopted every thing from containers to OpenStack to some thing else emerged. perhaps, the choicest flow for VMware became its tight partnership with AWS. This hybrid cloud partnership is a win-win for each events and each companies have continued to construct on their initial efforts. The partnership is so exciting that VMware is assisting to deliver AWS on premises. To wit:

    Of route, VMware also has its vRealize Suite, vCloud Air, VMware HCX, Cloud administration Platform, vSphere, and networking items.

    Dell applied sciences and HPE: each of those companies have dissimilar products to function records centers and are plugging into cloud providers. 

    HPE's plan boils down to multi-cloud, hybrid infrastructure that extends to the aspect.

    hpe-growth-plan-fy-19.png

    hpe-growth-plan-fy-19.png

    (photograph: HPE)

    after which, there's Cisco, which via acquisitions has constructed out a significant utility portfolio. Cisco outlined a data middle any place vision that revolves around plugging its application centric infrastructure (ACI) into multiple clouds. No count how you slice the hybrid cloud online game, the conclusion state is an identical: diverse suppliers and personal infrastructure seamlessly connected. Cisco additionally has partnerships with Google Cloud. Kubernetes, Istio, and Apigee serve because the glue within the Cisco-Google effort.

    while the hybrid cloud market turned into greatly panned as legacy providers cooking up new easy methods to sell hardware, the new multicloud world has more acceptance even among the former upstarts who wanted to show the likes of IBM, VMware, Dell, and HPE into dinosaurs.

    The SaaS market also highlights how vendors and their altering concepts and acquisition plans make cloud classification extra complicated. within the 2018 version of our cloud rankings, Oracle became lumped into the AWS, Azure, and GCP crowd generally since it changed into trying to play within the IaaS market.

    while CTO Larry Ellison nevertheless appears to be smitten by AWS, Oracle is very nearly a utility- and database-as-a-service business. perhaps Oracle's efforts to automate the cloud and cook up next-gen infrastructure pay off, but for now, the business is in reality about application. Salesforce via the acquisition of MuleSoft has also modified its stripes a bit of and delivered an integration spin to the cloud method (and even just a little of natural application licensing). SAP has grown into a sizable cloud player and Workday has opened its ecosystem.

    masking every SaaS player is past the scope of this overview, however there are a gaggle of companies that may well be referred to as SaaS+. These cloud service suppliers extend into structures and all of these providers have distinctive SaaS items that may run your company.

  • Annual cloud services and license assist income run cost: $26.four billion
  • ERP and HCM annualized earnings: $2.6 billion
  • In Gartner's 2018 Magic Quadrant for IaaS, the analysis enterprise narrowed the field to just cloud organizations. Oracle made the cut. It would not be superb if Oracle turned into reclassified in 2019 out of the infrastructure race.

    Let's get real: Oracle is a SaaS provider and there's no disgrace in that. really, Oracle is rattling first rate on the SaaS video game and has every thing covered from small- and mid-sized businesses by the use of NetSuite to big organizations migrating on-premise software to the cloud.

    however the real differentiation with Oracle is its database. The business has a large installed base, an self sufficient database that goals to remove grunt work and the talents to place its expertise on greater clouds past its own. Oracle is pitching itself as a Cloud 2.0 participant.

    For now, Oracle is somewhat obsessive about AWS. consider:

    Andy Mendelsohn, govt vp of database server technologies at Oracle, said it's very early within the cloud migration of databases. "within the SaaS world or not it's a mature market the place enterprise valued clientele have accredited they could run HR and ERP in the cloud," he spoke of. "Database in the cloud has little or no adoption."

    Mendelsohn pointed out what Oracle sees more of is customers using features like Cloud at consumer and a non-public cloud strategy to moving databases. Initiatives like Oracle's autonomous database can be extra about a personal cloud method, he talked about.

    among smaller businesses, databases are more universal within the cloud as a result of there may be much less investment essential.

    "The large battleground will revolve across the information. it be the core asset at each enterprise accessible," he referred to.

    Cloud at customer is part of how Oracle sees its multi-cloud strategy. Analysts have raised concerns that Oracle should run its software and databases on extra clouds.

    Following Oracle's 2d quarter profits in December, Stifel analyst John DiFucci spoke of:

    while we continue to feel Oracle is well-located in the SaaS market, we stay greater cautious around PaaS/IaaS, each when it comes to right-line salary and linked cap-ex implications.

    whereas there is no doubt in our intellect that Oracle's installed base is extremely comfortable, we trust that a big element of net new database workloads are going to non-Oracle platforms (hyperscale options, NoSQL, open source, and so on).

    We continue to be cautious on Oracle's IaaS efforts and aid the notion of Oracle expanding guide for other clouds.

    Mendelson pointed out that Oracle has worked with diverse dealer concepts all over its heritage, so it be no longer a good deal of a stretch to peer multi-cloud emerge over time.

  • Annual cloud earnings run rate:$14 billion
  • revenue Cloud annual revenue run price: $four billion
  • carrier Cloud annual revenue run cost: $3.6 billion
  • Saleforce Platform & other annual salary run rate: $2.8 billion
  • advertising and Commerce Cloud annual earnings run cost: $2 billion
  • Salesforce began as a CRM company 20 years in the past and has accelerated into every thing from integration to analytics to marketing to commerce. Woven during the Salesforce clouds are add-ons comparable to Einstein, an AI system.

    with no trouble put, Salesforce desires to be a digital transportation platform that's targeting fiscal 2022 aim of revenue between $21 billion to $21 billion.

    Most cloud carriers -- public, inner most, hybrid or otherwise -- will tell you the game is shooting facts under administration. Salesforce additionally sees the promise of being the information platform of record.

    salesforce-portfolio.png

    salesforce-portfolio.png

    (photograph: Salesforce)

    Enter Salesforce's consumer 360. The grasp plan is to make use of client 360 to enable Salesforce shoppers to join all their information into one view. The concept is rarely exactly usual, but Salesforce's argument is that it will probably execute better and put the customer on the core of the facts universe.

    Add it up, and Salesforce is becoming a platform guess for its consumers. Salesforce co-CEO Keith Block observed the enterprise is touchdown extra deals price $20 million or greater and these days renewed a 9-determine win with a monetary capabilities enterprise. Marc Benioff, co-CEO and chairman, pointed out that Einstein AI is being brought into all of the enterprise's clouds.

    should examine

    Salesforce has additionally partnered well with the likes of Apple, IBM, Microsoft (in some areas), AWS, and Google Cloud.

    The go-to-market strategy for Salesforce revolves around selling distinctive clouds and establishing trade selected purposes such as the business's financial functions Cloud.

    Block said:

    I've traveled all over assembly with greater than one hundred CEOs and world leaders. The dialog is consistent all over i'm going. it be about digital transformation. it's about leveraging our technology. it's about our subculture, and or not it's about our values. This C-level engagement is translating into extra strategic relationships than ever.

    For 2019, there may be little on the radar -- short of a broad financial downturn -- that might derail Salesforce's momentum. sure, Oracle and SAP continue to be fierce competitors with the latter actively pitching its subsequent-gen CRM system, but Salesforce is considered as a digital transformation engine. Microsoft is yet another competitor worth staring at, on the grounds that it additionally wants to offer a single view of the client. Dynamics 365 is becoming greater aggressive with Salesforce. With its marketing Cloud, Salesforce competes with Adobe. As Salesforce continues to expand so will its competitive set.

    greater on Salesforce:
  • Annual cloud subscriptions and aid income: €5 billion
  • Annual cloud salary run price: €5.sixty four billion
  • SAP has a sprawling cloud utility company that runs from ERP and HR to expenses (Concur) in addition to Ariba. The business is basic enterprise utility, but consumers are migrating to the cloud. SAP's strategy rhymes with Oracle's approach, but there may be a key difference: SAP will run on diverse clouds.

    CEO invoice McDermott cited the SAP cloud companions on the business's fourth quarter earnings call. "SAP has mighty partnerships with Microsoft, Google, Amazon, Alibaba, and others to include this value advent probability," he observed. "purchasers can run on-premise, in a non-public cloud or in the public cloud. it be their alternative."

    sap-qualtrics-combo-2.png

    sap-qualtrics-combo-2.png

    (photo: SAP)

    The SAP cloud lineup carries here:

  • SAP S/4HANA Cloud
  • SAP SuccessFactors
  • SAP Cloud Platform, records Hub (that are hybrid plays)
  • SAP C/four HANA
  • company network software (Ariba, Concur, and Fieldglass)
  • within the end, SAP is a mix of traditionally licensed software and cloud types. CEO bill McDermott also outlined some massive growth dreams. For 2019, SAP is projecting cloud subscription and assist earnings between €6.7 to €7.0 billion.

    Going forward, SAP is projecting cloud subscription and support profits of €eight.6 to €9.1 billion. with the aid of 2023, SAP wants to triple cloud subscription and guide revenue from the 2018 tally.

    more on SAP:
  • Annual cloud revenue run fee: $3 billion
  • Workday made its identify with human capital administration, extended into financials and ERP, and is including analytics by means of a sequence of acquisitions.

    before AWS grew to become an Oracle obsession, Workday changed into a chief goal of Larry Ellison's rants. these verbal barbs from Ellison grew to be a inform that Workday changed into faring neatly.

    Most of Workday's revenue derives from HCM, but the business is beginning to promote financials along with it. In other words, Workday is making an attempt to improve that multi-cloud playbook that Salesforce has going. That said, Workday also has loads of runway for HCM. Workday hasl half of the Fortune 50 as customers and about forty p.c of the Fortune 500.

    The analytics company for Workday is being developed by way of acquisition. Workday received Adaptive Insights, a business planning participant, and will target analytics workloads.

    whereas Workday fared well on its own, the company changed into gradual to increase its ecosystem and run on infrastructure from the general public cloud giants. Workday has spread out to enable purchasers to run on AWS and that is the reason a big stream that may pay dividends in the future.

    The enterprise also launched the Workday Cloud Platform, which enables valued clientele to write applications inside of Workday by way of a group of application programming interfaces. The Workday Cloud Platform, launched in 2017, makes its platform extra flexible and open.

    In 2019, that you could expect Workday to discover growth ito greater industries past training and government. Healthcare could be an option for a broader effort.

    Robynne Sisco, CFO of Workday, observed at an investor convention in December:

    for those who suppose about expanding in terms of trade operational methods, there is in reality an awful lot that we might do going forward. We may do retail. We may do hospitality. As of at this time, we have got a lot of issues we're working on. So we're staying where we are. but trade does turn into very important if you talk about promoting financials.

    Workday is also targeting more mid-sized companies with Workday Launch, a set-payment, preconfigured application package.

    The competitive set for Workday is Oracle and SAP for HCM and Financials. additionally watch Salesforce, which is a Workday associate and competencies foe in the future. one more wild card for Workday will be Microsoft, which is integrating LinkedIn extra for HR analytics.

    more on Workday: extra on cloud management: greater on seller management: more on internet of things: greater on cloud vs statistics center:

    Mendix Unveils video game-altering Native Integration with IBM's Cloud functions and Watson | killexams.com Real Questions and Pass4sure dumps

    BOSTON, Feb. 11, 2019 /PRNewswire/ -- Mendix, a Siemens company and the leader in low-code for the business, today introduced new and significantly more suitable platform enhancements for Mendix on IBM Cloud to be delivered through Erno Rorive, senior product manager at Mendix, talking at IBM believe 2019. Mendix is IBM's best enterprise-grade, low-code construction platform absolutely optimized and cloud-natively built-in with IBM Cloud functions. Rorive will highlight Mendix's reengineered cloud-native structure that now fully supports Kubernetes containerization for the IBM ecosystem. Full guide for IBM's Kubernetes implementation provides Mendix low-code app developers with seamless access to the capabilities of Watson, the realm's leading company of AI cognitive services.

    "The purpose of the Mendix-IBM Alliance is to location the ease of drag-and-drop, low-code utility construction into the fingers of the enterprise cloud market, leverage Watson's AI capabilities for the greatest number of clients, and vastly speed up the time-to-cost deployment of company innovation," says Rorive. "the mixing of the Mendix platform with IBM Cloud and Watson represents a golden triangle of enterprise-ready options as a way to power the subsequent wave of smart applications to center of attention the power of AI on vertical trade options."

    Mendix's platform enhancements for the IBM Cloud infrastructure include:

  • Broader access to IBM Cloud capabilities. Integrating Mendix's low-code app development and deployment with Watson's out-of-the-container AI capabilities will enable commercial enterprise valued clientele to scan with AI-in a position capabilities, including access to weather Channel content material, App id, and App Launch on IBM Cloud.
  • Full help for Kubernetes. integrated support for Kubernetes production-grade container orchestration is now part of Mendix's cloud-native architecture. Native Kubernetes help allows for streamlined administration and interoperable deployment across public, private, and hybrid clouds. This turbocharged integration with IBM Cloud and the Mendix platform eliminates costly IT overhead with automated healing and horizontal scaling, enabling seamless management for migrating legacy programs or developing new, cloud-native, microservices-based capabilities.
  • Single sign-on Onboarding. Reengineered platform integration creates a frictionless consumer experience for all Mendix low-code purposes with one-click, out-of-the container deployment to IBM Cloud's complete catalog of third-party carriers. This enhancement enables enterprise shoppers to operate and computer screen mission-essential applications in a single IBM-centric dashboard, casting off the need for extra logins and passwords.
  • integrated Billing with IBM Cloud. The newly streamlined financial platform gives commercial enterprise consumers with a single bill for any bought IBM Cloud service. by using adding the Mendix platform to IBM Cloud's catalog, shoppers can straight away start to discover Mendix's commercial enterprise-ready, low-code software construction, allowing them to bring industrial advantages at speed and for the bottom feasible total can charge of ownership, the usage of their IBM Cloud credits.
  • p>"The billing platform integration will encourage new clients who are seeking for an effortless approach to consider reducing-facet products," says Rorive. "It becomes a whole lot greater flexible for agencies to experiment and lengthen their utility landscape with low-code construction, at a lots lower investment possibility than common."

    The IBM think 2019 conference  at San Francisco's Moscone center is the largest annual gathering of good executives, business strategists, skilled developers, and academic and enablement consultants who will share their stories, insights, and choicest practices for creating price with IBM's cloud-primarily based ecosystem.

    Erno Rorive's presentation, "build purposes 10x quicker with the IBM Cloud low-code platform through Mendix"takes place on Tuesday, February 12, at 1:30 p.m. at Moscone center South as a part of IBM consider 2019's track on Cloud and Infrastructure: wise starts here.

    to hear Rorive's speak, register for IBM consider 2019.

    About MendixMendix, a Siemens company and the global leader in low-code for the enterprise, is transforming the world of legacy software and utility building via bringing company and IT teams together to all of a sudden and collaboratively construct amazing and up to date purposes for the commercial enterprise. The Mendix software construction platform directly addresses the gigantic international utility developer ability hole, and involves business and IT at the very start and during the entire utility building and deployment procedure. identified as a "leader" by means of correct analysts, together with Gartner and Forrester, Mendix helps customers digitally radically change their agencies and industries by constructing, managing, and improving apps at exceptional speed and scale. more than four,000 ahead-thinking corporations use the Mendix platform to build enterprise functions that pleasure consumers and improve operational effectivity. be a part of the Mendix community on LinkedIn and Twitter. delivery constructing apps for free at signup.mendix.com.

    Press InquiriesKatie McGovernSenior Account manager, SHIFT Communicationsmendix@shiftcomm.com (617) 779-1867

    Dan BerkowitzSenior Director, world CommunicationsDan.Berkowitz@mendix.com (415) 518-7870

    View original content to down load multimedia:http://www.prnewswire.com/information-releases/mendix-unveils-video game-altering-native-integration-with-ibms-cloud-services-and-watson-300792660.html

    source Mendix

    Copyright (C) 2019 PR Newswire. All rights reserved


    Inpixon pronounces IPA Connector for IBM MaaS360 With Watson Integration | killexams.com Real Questions and Pass4sure dumps

    Inpixon (NASDAQ:INPX) announced on Monday that the company introduced the liberate of the Indoor Positioning Analytics for IBM MaaS360 with Watson. The company pointed out that the valued clientele of IBM MaaS360 and Inpixon IPA can immediately disable instant contraptions in no-telephone zones. As quoted within the press liberate: MaaS360 cellular equipment administration (MDM)  permits IT organizations … continued

    Inpixon (NASDAQ:INPX) introduced on Monday that the enterprise introduced the free up of the Indoor Positioning Analytics for IBM MaaS360 with Watson.

    The business observed that the purchasers of IBM MaaS360 and Inpixon IPA can automatically disable instant gadgets in no-telephone zones.

    As quoted within the press release:

    MaaS360 cellular gadget administration (MDM)  allows for IT companies to cozy, control and display screen any corporate- or worker-owned mobile machine. The answer allows corporations to configure the machine with corporate connectivity settings, e mail profiles and gadget-particular restrictions; to encrypt business counsel; to remotely wipe misplaced devices; and extra.

    The Inpixon IPA Connector for MaaS360 provides interesting capabilities to the IBM solution. particularly, the Inpixon IPA Connector for MaaS360 allows MDM directors to utilize multiple geo-fenced zones on a facility flooring plan. As a instant equipment strikes throughout the workplace environment, the Inpixon IPA Connector sends the cellphone’s location to MaaS360, enabling MaaS360 to push out vicinity-particular guidelines. essentially the most usual use case is to disable a mobile’s digicam, audio recorder and transmission capabilities whereas in a excessive security, no-cellphone-phones zone. This capability helps to steer clear of recording of private conversations, theft of highbrow property, and transmission/reception of voice and statistics while within the zone.

    “Cybersecurity situation recognition and wireless intrusion detection are key price propositions Inpixon IPA provides out of the box,” cited Soumya Das, COO of Inpixon. “When used along side MaaS360, purchasers are able to enhance their mobile security capabilities. We’re excited to make the Inpixon Indoor Positioning Analytics integration available to MaaS360 international consumers in the course of the IBM security App alternate.”

    “IBM believes in the value of ecosystems and integrating seamlessly with superior-of-breed commercial enterprise security infrastructure, like Inpixon,” talked about Charles Brown, Sr. offering supervisor, IBM. “including the Inpixon IPA Connector for MaaS360 in the IBM protection App trade allows our mutual consumers to leverage the rich cellular safety information set of MaaS360 with the power of Inpixon IPA.”

    click right here for the total text unlock.

    See our free file to get began

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    How Slack’s Content Strategy Expanded from a Single Page to a Media Company | killexams.com real questions and Pass4sure dumps

    “If a tree falls in a forest and no one is around to hear it, does it make a sound?” This analogy applies to the ideas we so painstakingly put together. If nobody can access the words conveying ideas, does it make an impact?

    For example, content strategist Gerry McGovern did some digging for Microsoft, and realized a whopping 30% of its 10 million pages at its website went completely unread. Missed opportunities like these are the ones that competitors like Slack must identify and exploit, in order to compete and win.

    Here are three ideas that every CEO, product marketer, and wordsmith needs to consider for their business’s content strategy:

    1. If It’s Important Enough, Say It More than Once

    People read through skimming. Saying the most important things at your site just once is not enough. Repetition is no longer tiresome. It’s essential, because most readers might miss it if placed sparsely.

    The more careful reader will notice this repetition, but no feature description, testimonial, or any other other phrase are exactly identical. Instead, each adds to an overall point…

    A throughline threads together sentences that convey each of these points. For example, at the third version of Slack’s homepage (V3), there’s a slider with three panels that highlight Slack’s most important features — “Channels,” “Integration,” and “Search” — above the fold.

    Each of these features have their own throughlines, but “Integration” is particularly important to potential users for convenience, organization, and consolidation. Let’s dive into how Slack constructs the “Integration” throughline:

    Full version (July 23, 2015)

    IntegrationsPlug the tools you already use into Slack and get all your notifications in one place

    “Integration” is on the second panel of the slider above the fold. Let’s say someone carelessly scrolls past before the slider changes. Their eyes jump right into the product features section grid:

    Over 80 integrationsIt’s not ‘yet another app’ you have to use. Slack works with all the tools you already use; set them up to post notifications directly to Slack in a single work space.”

    Slack opens with a quantity, “80 integrations.” It’s visual and lets the reader know Slack’s not full of hot air. The first sentence anticipates the reader’s objection, and re-explains “integration” in different words, “notifications… in a single work space.” Now, let’s say they even if they miss that, since it’s buried along with five other points…

    Like your team’s collective brain.Slack integrates with over 80 external services to help you pull information from outside tools in a way that’s timely, relevant, and always searchable. No more switching between apps. Bring it all together in one simple place.

    Assuming the reader keeps scrolling, there’s no way they can miss this. It’s a featured blurb on its own, capturing the imagination with a simile, “Like your team’s collective brain.” I suspect it’s a residual thought from Slack’s first homepage (V1), a header preceding testimonials, describing Slack, “It’s like an infinite brain for your whole team.”

    Notice the repeated quantity from the produce feature grid, the emphasis on “timely, relevant, and always searchable,” and ending in, “all together in one simple place.”

    To Slack, the “integration” point is clearly far too important for the average reader’s careless reading habits. So, they repeat some variation of it three times on their home page. At their Tour page, they dive deep into types of notifications, to paint a very concrete picture for the reader:

    All your tools in one place.Connect all the tools you use to Slack and avoid all that constant switching between apps. Set up your integration so that you get all your notifications directly within Slack — from support requests, code check-ins, and error logs to sales leads — all of them searchable in one central archive.

    As you may guess from previous observations, ideas like “all in one place,” “notifications,” and “one central archive” come up. The most interesting thing is that in the final point on the Tour page (“All your tools in one place”), this point also ties into the “Search” throughline.

    Repetition ensures careless readers leave with an impression things you want to tell them. It also reinforces these important ideas to more careful readers. Strong content strategy ties throughlines together for readers across different pages and properties, each reinforcing the other.

    2. Slack as a Media Company

    One of the most interesting aspects of Slack is neglected by most other startups — their brand. Slack invests heavily not just in the aesthetics of their product and website, but also into content that conveys larger ideas, tying in stories with their brand. The adage goes, “Every company is a media company.”

    Some companies, like Peloton and Tonal, take this to heart, integrating media with their product’s soul. Slack ultimately sells “organizational transformation,” so it invests heavily in media to support the change in mindsets. With the exception of Slack’s podcasts, here’s each one at the time of writing (notice how each of their media channels has its own name and domain):

  • Blog: Several People Are Typing, which prior to July 2018 received on average 150,000 pageviews per month according to Similarweb. It was hosted at Medium before the Slack team migrated to WordPress.com in July 2018, because they wanted more custom tools and workflows (and more granular reporting). Medium served as a solid host for two years for Slack to draw readers and operate with few design and development resources.
  • Engineering blog: Several People Are Coding is still hosted at Medium, and receives a widely fluctuating 45,000–120,000 pageviews, according to Similarweb.
  • Design blog: #slack-design is hosted at Medium. It does not yet receive as much traffic as its main blog or engineering blog.
  • Job board: Slack at Work is a job board, also hosted at WordPress, where Slack customers can post their jobs.
  • Store: The Slack Shop is a Shopify store that sells Slack merch, like branded socks and stickers. It’s also a branding and corporate responsibility play, donating proceeds from the store to a new charity every month.
  • Twitter: @slackhq is where much of their support and brand interactions take place. People talk with and to Slack on Twitter. This is their two-way channel, whereas the aforementioned resemble broadcast.
  • Podcast #1: Slack Variety Pack, distributed over Soundcloud and iTunes.
  • Podcast #2: Eventually, Slack deprecated the slack Variety Pack and made a second podcast, entitling it “Work in Progress,” and distributing it on SiriusXM and iTunes.
  • Every startup has a slightly different way of building trust through its brand and eventually driving sales. For example, Buffer’s hypothesis is transparency builds trust faster than all other methods, so they built a transparency dashboard. Drift’s hypothesis goes a step further, in saying authenticity builds trust faster, so they build their own reality TV show.

    I believe that Slack’s less deliberate, more organic, hypothesis is that humanity builds trust faster than all other methods. It’s a core part of their voice (clear, concise, and human). It’s also the antithesis to Microsoft’s — and many other company’s — voice and brand. And even with these qualities, part of Slack’s magic is in how they represent it…

    The human experience is incredibly wide. Slack chooses to share emotion with their readers (e.g., Wall of Love), and convey it through quality work by investing heavily into its content creation. In principle, it’s not dissimilar from art.

    For example, both their podcasts explore the nature of work (e.g., a corporate retiree re-entering the workforce), because people spend more and more time doing it (and, at times, finding meaning through it). Their blog does the same. So does their job board — as people’s work locations could affect their personal lives immensely (long distance relationships, travel opportunities, commute, etc.).

    Slack hires experts like Pacific Content to create their podcast. They also hire illustrators to create unique art accompanying each blog post. They reach out to people outside of the company to conduct interviews that they publish at their blog, similar to what a magazine would’ve done.

    Without overlooking their core communications product, all this content accelerates people’s trust in Slack, and builds up Slack’s credibility and favorability. To varying degrees, each of their properties are now a defensible marketing asset that they can control and own, especially after they started hosting their own blog (which can be exported from WordPress). They’ve also got a ton of real estate online, a lot of it distributed at platforms (e.g., Twitter, their design and eng blogs at Medium).

    Consider also the beginning of each initiative — only the Slack at Work site required dev resources (to set up WordPress to be a job board). Their blog started at Tumblr, then moved to Medium. Their support and brand interactions are expanded by Twitter’s platform reach. They bring their Twitter interactions back to their website by linking to their Wall of Love list in V2, and embedding Tweets from this account in V3 (Archive doesn’t load it well).

    Full version (October 20, 2014)

    With any other organization, I’d suggest that they set up a mailing list. This is typically the anchor of all owned content properties, because email lists can be downloaded and stored. However, since this is Slack and their whole goal is to kill email, they’d be better served building a large community of Slack users (e.g., friends.slack.com).

    All said, Slack’s content has an incredible amount of integrity and taste. I love it. If you told me there was a Slack magazine, to me it would look like Airbnb’s Pineapple (and not their dreadful new one…) This admiration, and respect, is a difficult “feeling” to replicate in an advertisement. Blended in with trust, these feelings might just be enough to give up email.

    Trust is a priceless asset, but the question of direct ROI inevitably comes up. Their blog (slackhq.com) hosted at Medium didn’t seem to bring many people back to their main site (slack.com). At the time of writing, Similarweb reporting that 0.57% of their overall website’s overall traffic comes from referrals.

    However, an old screenshot from Openview, highlighting Similarweb stats from a year ago, reports slackhq.com drives 2% of referral traffic:

    My guess is Slack didn’t care much for their content’s SEO, or “content marketing” success metrics, in conventional terms. They just wanted content that would educate people and build trust. In fact, it seems they’re just hiring for it now, at the time of writing. Their word-of-mouth marketing, SEO through integrations, and app ecosystem, all feed user acquisition and conversion much better than content did…

    But their content makes Slack most favorable and trustworthy than their current competitors (Microsoft, IBM, etc.). And, their content ushers in a new way of thinking about work, retains loyal brand users, and lays the foundation for their company’s future.

    Final Thoughts

    Slack’s content strategy grew with their business, going from a single page in the first version of their website (V1), to a media company by the fourth (V4). And yet, the principles stayed the same. They weren’t afraid to repeat the important things, they told human stories, and they invested heavily in distributing their content through their “media company” arm. But if you’ve had a look at their sites, you’ll realize there’s so much more I could cover.

    At the end of the day, Slack focuses on humans. They speak with candor, politeness, and courtesy. Consciously or not, they align themselves with how we’ve consumed content in the past. They apply the format of variety shows into their podcast, and like a magazine they combine beautiful illustrations with in-depth interviews into their blog. They invest not just in their technology platform, but in communicating their product’s value through education. Even the world’s most powerful tool is useless without an understanding of its possibilities or how to actually use it.

    Metaphors run rampant in content strategy, partially because of the creative nature of the workers, and partially because it’s such a new discipline that nobody understands it. Beyond the attribution, the CMS’s, and the information architecture, it’s very simple:

    Create ideas worth talking about, and figure out how and where to talk about them.


    10 Reasons to Unify Your Data With a Data Warehouse | killexams.com real questions and Pass4sure dumps

    Savvy leaders are transforming their organizations with data, using hard numbers to make decisions and align their teams toward tangible goals. More efficiency, faster production, lower costs — all of these are within reach for organizations that can master their data.

    As more and more tools are required to drive different processes, and each provides different sets of data, the key is to manage and govern increasingly massive data collections. For hundreds of thousands of companies, that means unifying that data inside of a data warehouse.

    What is a Data Warehouse?

    A data warehouse is NOT just another database. A data warehouse is a federated (uses a unifying standard for separate databases) repository for all the data collected by an enterprise’s various operational systems. Data warehousing emphasizes the capture of data from diverse sources specifically for access and analysis, including large-scale analysis, rather than for transaction processing.

    Because they’re designed for analytical processing, data warehouses offer many advantages for organizations of all types.

    Benefits of Unifying Your Data in a Data Warehouse 1. More Consistency in Your Data

    A properly deployed data warehouse makes it possible to convert data from many different sources into a unified format. Once in the data warehouse, in the standard format, all of your analysts, throughout various departments and teams can access the data in a governed, standard, secure way. This allows you to keep processes standardized and consistent across the organization — while still providing analysts all the data they want and need.

    2. 360 Degree Analysis

    Data warehouses are designed specifically to aggregate data from many sources into a specifically accessible central store. By unifying the data in one place, (and in the same format) analysts can perform more comprehensive, 360 degree reviews. You get both deeper and broader analysis on all the trends happening throughout your company.

    3. Better Organizational Alignment

    With better 360 degree insights and different teams (sales, marketing, operations, support, etc.) all using the same repository for reporting, each department can better align with the others. All the key stakeholders can see what’s going on throughout the organization and stay on the same page. The practical implications extend beyond analysis and directly into day-to-day operations: the left hand can always know what the right hand is doing and take action in concert.

    4. Built for Performance

    Data warehouses are built differently than operational database systems, which are more focused on creating and modifying data. Data warehouses are built specifically for analysis and retrieval rather than the upkeep of individual records. As a result, they offer both a more scalable solution for storing large volumes of data and faster processing for advanced data analysis using BI tools, processing queries more efficiently to enable faster analysis.

    5. Simplify API Management

    Data warehouses help eliminate API management headaches. With data warehouses, there’s no need to juggle or manage separate APIs to access data in every single application or database. Instead, you simply copy the data from a given data source and replicate it in your data warehouse, saving time and reducing error-prone processes. Then, you can use transactional replication, which copies only new entries in the data source to the data warehouse, so your warehouse stays up to date without a massive stream of new data eating up bandwidth.

    6. Skip the API Limitations

    Another benefit of using data replication is that you circumvent costly, complex API limitations. This expands your general data access by allowing you to dodge the problems associated with live querying of certain APIs that are either slow or limit the number of queries you can run against them.

    7. Historical Intelligence

    Data warehouses can store absolutely gargantuan amounts of historical data, with some organizations’ data warehouses clocking in at petabytes of data. For context, a petabyte is 1000 terabytes, or 1 million gigabytes, the unit most people use to denominate storage needs. With spacious petabytes of data at your disposal, you have all the elbow room you need to track historical data, giving your organization the ability to analyze different time periods and trends in order to make future predictions. This is crucial because vast reams of historical data just can’t be stored in a transactional database or used to generate reports from a transactional system — databases get too cumbersome and quickly overloaded.

    8. 167% Median ROI Due to Massive Cost Savings

    According to an in-depth study conducted by the International Data Corporation (IDC), the median three-year ROI of a data warehouse investment was 167 percent, for a wide range of companies studied, big and small, across industries. The average was even higher, at 400 percent ROI. The reason? Data warehouses help organizations massively cut their costs for streamlining and governing their data. Organizations that start with an actionable path and iterative, smaller projects can especially speed up their payback period, with the average payback period at just over 1.5 years.

    9. Proven and De-Risked

    Enterprise data warehouses have been around forever. The military command-and-control, intelligence, manufacturing, banking, finance and retail industries have used data warehouses since the 1960s. In the mid-90s, data warehousing emerged as an IT specialization, after Walmart changed the game. Behind the mastery of Walmart’s supply chain, their data warehouse helped them leverage transaction data collected by its point-of-sales systems to gain deep insight into the purchasing habits of its 100 million customers and the logistics guiding its 25,000 suppliers. Since then, data warehousing has steadily gained adoption by many of the biggest companies in the world, with proven implementation models.

    And on the actual data warehouse side, you’re dealing with the hulking giants of tech: Amazon, IBM, Microsoft, Oracle, Google and Teradata (which has been around for 30 years) provide the largest data warehouses on the web, all with deep support.

    10. Higher Security: Consolidated Data Access

    By using a data warehouse as a unified repository for your data, you can not only bring together all your data, you can make it more secure through consolidated data access. If you control data access through a centralized system, you can combine role-based user access controls, providing different permissions to different users, with row-level access controls (which data is available to different users) to lock down data security. In particular, row-level access control provides several security benefits, including:

  • More granular data security: set permissions for rows, not just tables and columns
  • Automatic data filtering according to group, role, application and more
  • Server-encoded data-level security
  • This helps meet compliance requirements for regulated industries, such as healthcare and comes standard now in the biggest data warehousing tools.

    How to Move Data into Data Warehouses

    There are a number of different ways you can get data from your various enterprise IT systems, databases and applications into a unified data warehouse. One that is particularly effective for this type of use case and gets around many integration challenges and API limits as well is incremental data replication. In this process, you use a tool to replicate data from various sources into the warehouse then regularly sync new updates (or increments) from those sources into the warehouse.


    The Best Self-Service Business Intelligence (BI) Tools of 2018 | killexams.com real questions and Pass4sure dumps

    Analytics Beyond Spreadsheets

    For many years, Microsoft Excel and other spreadsheets were the tools of choice for business professionals who were looking to visualize their data. But spreadsheets had their limits for many business intelligence (BI)-related tasks. Even today, trying to creating charts analyzing complex datasets in Excel can still be frustrating. Sometimes you start with the wrong kind of data, for example, or you may not know how to manipulate the spreadsheet to create the data visualization{{/ZIFFARTICLE} you need. On the other hand, the rising tide of data democratization is giving everyone in an organization access to corporate data. The need has arisen for effective tools that people of all skill levels can use to make sense of the wealth of information created by businesses every single day.

    Spreadsheets also fall down when the data isn't well-structured or can't be sorted out in neat rows and columns. And, if you have millions of rows or very sparse matrices, then the data in a spreadsheet can be painful to enter and it can be hard to visualize your data. Spreadsheets also have issues if you are trying to create a report that spans multiple data tables or that mixes in Structured Query Language (SQL)-based databases, or when multiple users try to maintain and collaborate on the same spreadsheet.

    A spreadsheet containing up-to-the-minute data can also be a problem, particularly if you have exported graphics that need to be refreshed when the data changes. Finally, spreadsheets aren't good for data exploration; trying to spot trends, outlying data points, or counterintuitive results is difficult when what you are looking for is often hidden in a long row of numbers.

    While spreadsheets and self-service BI tools both make use of tables of numbers, they are really acting in different arenas with different purposes. A spreadsheet is first and foremost a way to store and display calculations. While some spreadsheets can create very sophisticated mathematical models, at their core it is all about the math more than the model itself.

    This is all a long-winded way of saying that when businesses use a spreadsheet, they are actively sabotaging themselves and their ability to consistently get valuable insights from their data. BI tools are specficially designed to help businesses better understand their data, and can prove to be a huge benefit to those upgrading from what a limited spreadsheet can do.

    What Is Business Intelligence?

    Defining BI is tricky. When you examine what it does and why companies use it, it can start to sound vague and nebulous. After all, many different kinds of software offer analytics features, and all businesses want to improve. Understanding what a BI is or isn't can be unclear.

    BI is an umbrella term meant to cover all of the activities necessary for a company to turn raw information into actionable knowledge. In other words, it's a company's efforts to understand what it knows and what it doesn't know of its own existence and operations. The ultimate goal is being able to increase profits and sharpen its competitive edge.

    Framed that way, BI as a concept has been around as long as business. But that concept has evolved from early basics [like Accounts Payable (AP) and Accounts Receivable (AR) reports and customer contact and contract information] to much more sophisticated and nuanced information. This information ranges across everything from customer behaviors to IT infrastructure monitoring to even long-term fixed asset performance. Separately tracking such metrics is something most businesses can do regardless of the tools employed. Combining them, especially disparate results from metrics normally not associated with one another, into understandable and actionable information, well, that's the art of BI. The future of BI is already shaping up to simultaneously broaden the scope and variety of data used and to sharpen the micro-focus to ever finer, more granular levels.

    BI software has been instrumental in this steady progression towards more in-depth knowledge about the business, competitors, customers, industry, market, and suppliers, to name just a few possible metric targets. But as businesses grow and their information stores balloon, the capturing, storing, and organizing of information becomes too large and complex to be entirely handled by mere humans. Early efforts to do these tasks via software, such as customer relationship management (CRM) and enterprise resource planning (ERP), led to the formation of "data silos" wherein data was trapped and useful only within the confines of certain operations or software buckets. This was the case unless IT took on the task of integrating various silos, typically through painstaking and highly manual processes.

    While BI software still covers a variety of software applications used to analyze raw data, today it usually refers to analytics for data mining, analytical processing, querying, reporting, and especially visualizing. The main difference between today's BI software and Big Data analytics is mostly scale. BI software handles data sizes typical for most organizations, from small to large. Big Data analytics and apps handle data analysis for very large data sets, such as silos measured in petabytes (PBs).

    Self-Service BI and Data Democratization

    The BI tools that were popular half a decade or more ago required specialists, not just to use but also to interpret the resulting data and conclusions. That led to an often inconvenient and fallible filter between the people who really needed to get and understand the business—the company decision makers—and those who were gathering, processing, and interpreting that data—usually data analysts and database administrators. Because being a data specialist is a demanding job, many of these folks were less well-versed in the actual workings of the business whose data they were analyzing. That led to a focus on data the company didn't need, a misinterpretation of results, and often a series of "standard" reporting that analysts would run on a scheduled basis instead of more ad hoc intelligence gathering and interpretation, which can be highly valuable in fast-moving situations.

    This problem has led to a growing new trend among new BI tools coming onto the market today: that of self-service BI and data democratization. The goal for much of today's BI software is to be available and usable by anyone in the organization. Instead of requesting reports or queries through the IT or database departments, executives and decision makers can create their own queries, reports, and data visualizations through self-service models, and connect to disparate data both within and outside the organization through prebuilt connectors. IT maintains overall control over who has access to which tools and data through these connectors and their management tool arsenal, but IT no longer acts as a bottleneck to every query and report request.

    As a result, users can take advantage of this distributed BI model. Key tools and critical data have moved from a centralized and difficult-to-access architecture to a decentralized model that merely requires access credentials and familiarity with new BI software. This results in a whole new kind of analysis becoming available to the organization, namely, that of experienced, front-line business people who not only know what data they need but how they need to use it.

    The emerging crop of BI tools all work hard at developing front-end tools that are more intuitive and easier to use than those of older generations—with varying degrees of success. However, that means a key criteria in any BI tool purchasing decision will be to evaluate who in the organization should access such tools and whether the tool is appropriately designed for that audience. Most BI vendors indicate they're looking for their tool suites to become as ubiquitous and easy to use for business users as typical business collaboration tools or productivity suites, such as Microsoft Office. None have gotten quite that far yet in my estimation, but some are closer than others. To that end, these BI tool suites tend to focus on three core types of analytics: descriptive (what did happen), prescriptive (what should happen now), and predictive (what will happen later).

    What Is Data Visualization?

    In the context of BI software, data visualization is a fast and effective method of transferring information from a machine to a human brain. The idea is to place digital information into a visual context so that the analytic output can be quickly ingested by humans, often at a glance. If this sounds like those pie and bar charts you've seen in Microsoft Excel, then you're right. Those are early examples of data visualizations.

    But today's visualization forms are rapidly evolving from those traditional pie charts to the stylized, the artistic, and even the interactive. An interactive visualization comes with layered "drill downs," which means the viewer can interact with the visual to reach more granular information on one or more aspects incorporated in the bigger picture. For example, new values can be added that will change the visualization on the fly, or the visualization is actually built on rapidly changing data that can turn a static visual into an animation or a dashboard.

    The best visualizations do not seek artistic awards but instead are designed with function in mind, usually the quick and intuitive transfer of information. In other words, the best visualizations are simple but powerful in clearly and directly delivering a message. High-end visuals may look impressive at first glance but, if your audience needs help to understand what's being conveyed, then they've ultimately failed.

    Most BI software, including those reviewed here, comes with visualization capabilities. However, some products offer more options than others so, if advanced visuals are key to your BI process, then you'll want to closely examine these tools. There are also third-party and even free data visualization tools that can be used on top of your BI software for even more options.

    Products and Testing

    In this review roundup, I tested each product from the perspective of a business analyst. But I also kept in mind the viewpoint of users who might have no familiarity with data processing or analytics. I loaded and used the same data sets and posed the same queries, evaluating results and the processes involved.

    My aim was to evaluate cloud versions alone, as I often do analysis on the fly or at least on a variety of machines, as do legions of other analysts. But, in some cases, it was necessary to evaluate a desktop version as well or instead of the cloud version. One example of this is Tableau Desktop, a favorite tool of Microsoft Excel users who simply have an affinity for the desktop tool (and who just move to the cloud long enough to share and collaborate).

    I ended up testing the Microsoft Power BI desktop version, too, on a Microsoft representative's recommendation because, as the rep said, "the more robust data prep tools are there." Besides, said the rep, "most users prefer the desktop tool over a web tool anyway." Again, I don't doubt Microsoft's claim but that does seem weird to me. I've heard it said that desktop tools are preferred when the data is local as the process feels faster and easier. But seriously, how much data is truly local anymore? I suspect this odd desktop tool preference is a bit more personal than fact-based, but to each his own.

    Then there's Google Analytics, a pure cloud player. The tool is designed to analyze website and mobile app data so it's a different critter in the BI app zoo. That being the case, I had to deviate from using my test data set and queries, and instead test it in its natural habitat of website data. Nonetheless, it's the processes that are evaluated in this review, not the data.

    While I didn't test any of these tools from a data scientist's role, I did mention advanced capabilities when I found them, simply to let buyers know they exist. IBM Watson Analytics is one tool with the ability to extend to highly advanced features and was also one of the easiest to use upfront. IBM Watson Analytics is well-suited for business analysts and for widespread data democratization because it requires little, if any, knowledge of data science. Instead, it works well by using natural language and keywords to form queries, a characteristic that can make it valuable to practically anyone. It's highly intuitive, very powerful, and easy to learn. Microsoft Power BI is a strong second as it, too, is powerful while also familiar, certainly to any of the millions of Microsoft business users. However, there are several other powerful and intuitive apps in this lineup from which to choose; they all have their own pros and cons. We'll be adding even more in the coming months.

    One thing to watch out for during your evaluations of these products is that many don't yet handle streaming data. For many users, that won't be a problem in the immediate future. However, for those involved with analyzing business processes as they happen, such as website performance metrics or customer behavior patterns, streaming data can be invaluable. Also, the Internet of Things (IoT) will drive this issue in the near future and make streaming data and streaming analytics a must-have feature. Many of these tools will have to up their game accordingly so, unless you want to jump ship in a year or two, it's best to think ahead when considering BI and the IoT.

    BI and Big Data

    Another area in which self-service BI is taking off is in analyzing Big Data. This is a newer development in the database space but it's driving tremendous growth and innovation. The name is an apt descriptor because Big Data generally refers to huge data sets that are simply too big to be managed or queried with traditional data science tools. What's created these behemoth data collections is the explosion of data-generating, tracking, monitoring, transaction, and social media tools (to name a few) that have become so popular over the last several years.

    Not only do these tools generate loads of new data, they also often generate a new kind of data, namely "unstructured" data. Broadly speaking, this is simply data that hasn't been organized in a predefined way. Unlike more traditional, structured data, this kind of data is heavy on text (even free-form text) while also containing more easily defined data, such as dates or credit card numbers. Examples of apps that generate this kind of data include the customer behavior-tracking tools you use to see what your customers are doing on your e-commerce website, the piles of log and event files generated from some smart devices (such as alarms and smart sensors), and broad-swath social media tracking tools.

    Organizations deploying these tools are being challenged not only by a sudden deluge of unstructured data that quickly strains storage resources [think beyond terabytes (TB) into the PB and even exabyte (EB) range] but, even more importantly, they're finding it difficult to query this new information at all. Traditional data warehouse tools generally weren't designed to either manage or query unstructured data. New data storage innovations such as data lakes are emerging to solve for this need, but organizations still relying exclusively on traditional tools while deploying front-line apps that generate unstructured data often find themselves sitting on mountains of data they don't know how to leverage.

    Enter Big Data analysis standards. The golden standard here is Hadoop, which is an open-source software framework that Apache specifically designed to query large data sets stored in a distributed fashion (meaning, in your data center, the cloud, or both). Not only does Hadoop let you query Big Data, it lets you simultaneously query both unstructured as well as traditional structured data. In other words, if you want to query all of your business data for maximum insight, then Hadoop is what you need.

    You can download and implement Hadoop itself to perform your queries, but it's typically easier and more effective to use commercial querying tools that employ Hadoop as the foundation of more intuitive and full-featured analysis packages. Notably, most of the tools reviewed here, including Chartio, IBM Watson Analytics, Microsoft Power BI, and Tableau Desktop, all support this. However, each requires varying levels of configuration or even add-on tools to do so—with IBM, Microsoft, and Tableau offering exceptionally deep capabilities. However, both IBM and Microsoft will still expect customers to utilize additional tools around aspects such as data governance to ensure optimal performance.

    Finding the Right BI Tool

    Given the issues spreadsheets can have when used as ad hoc BI tools and how firmly ingrained they are in our psyches, finding the right BI tool isn't a simple process. Unlike spreadsheets, BI tools have major differences when it comes to how they consume data inputs and outputs and manipulate their tables. Some tools are better at exploration than analysis, and some require a fairly steep learning curve to really make use of their features. Finally, to make matters worse, there are dozens if not hundreds of such tools on the market today, with many vendors willing to claim the self-serve BI label even if it doesn't quite fit.

    Getting the overall workflow down with these tools will take some study and discussion with the people you'll be designating as users. Tableau Desktop and Microsoft Power BI, for example, will start users out with the desktop version to build visualizations and link up to various data sources. Once you have this together, you can start sharing those results online or across your organization's network. With others, such as Chartio or Google Analytics, you start in the cloud and stay there.

    In recent years, companies have been taking advantage of the wide selection of online learning platforms out there to train their employees on using these platforms. As intuitive as these platforms may be, it is important to make sure that your employees actually know how to use these BI platforms so that you can make sure your investment was worthwhile. There are many ways of approaching this, but using the right online learning platform might be a good place to start looking.

    Given the wide price range of these products, you should segment your analytics needs before you make any buying decision. If you want to start out slowly and inexpensively, then the best route is to try something that offers significant functionality for free, such as Microsoft Power BI. Such tools are very affordable and make it easy to get started. Plus, they tend to have large ecosystems of add-ons and partners that can be a cost-effective replacement for doing BI inside a spreadsheet. Tableau Desktop still has the largest collection of charts and visualizations and the biggest partner network, though both IBM Watson Analytics and Microsoft Power BI are catching up fast.

    IBM Watson Analytics scored the highest, and Microsoft Power BI and Tableau Desktop scored the next highest in our roundup. However, all three products received our Editors' Choice award. Tableau Desktop may have a big price tag depending on which version you choose but, as previously mentioned, it has an exceptionally large and growing collection of visualizations plus a manageable learning curve if you're willing to devote some effort to it. Microsoft Power BI and Tableau Desktop also have large and growing collections of data connectors, and both Microsoft and Tableau have their own sizable communities of users that are vocal about their wants and needs. This can carry a lot of weight with the vendors' development teams so it's a good idea to spend some time looking through those community forums to get an idea where these companies are headed.

  • Pros: Extremely user-friendly. Fantastic automatic report generation. Impressive support availability.

    Cons: Automated reports can quickly become defaults. Steep learning curve that might confuse beginners.

    Bottom Line: Zoho Reports is a solid option for general business users who might not be knowledgeable in analytics software. It's also available at an attractive price.

    Read Review
  • Pros: Accessible user interface. Smart guidance features. Impressively fast analytics. Robust natural language querying.

    Cons: Unable to do real-time streaming analytics.

    Bottom Line: IBM Watson Analytics is an exceptional business intelligence (BI) app that offers a strong analytics engine along with an excellent natural language querying tool. This is one of the best BI platforms you'll find and easily takes our Editors' Choice honor.

    Read Review
  • Pros: Extremely powerful platform with a wealth of data source connectors. Very user-friendly. Exceptional data visualization capabilities.

    Cons: Desktop and web versions divide data prep tools. Refresh cycle is limited on free version.

    Bottom Line: Microsoft Power BI earns our Editors' Choice honor for its impressive usability, top-notch data visualization capabilities, and superior compatibility with other Microsoft Office products.

    Read Review
  • Pros: Enormous collection of data connectors and visualizations. User-friendly design. Impressive processing engine. Mature product with a large community of users.

    Cons: Full mastery of the platform will require substantial training.

    Bottom Line: Tableau Desktop is one of the most mature offerings on the market and that shows in its feature set. While it has a steeper learning curve than other platforms, it's easily one of the best tools in the space.

    Read Review
  • Pros: Bottlenecks are eliminated thanks to in-chip processing. Impressive natural language query in third-party applications.

    Cons: Might be too difficult for self-service business intelligence (BI). Analytics process still needs to be ironed out. Natural language capability can be limited.

    Bottom Line: Sisense is a complete platform that should be popular for experienced BI users. It may fall short for beginners, however.

    Read Review
  • Pros: Wide range of connectors. Impressive sharing features. Limitless data storage.

    Cons: User interface is not intuitive. Steep learning curve. Unwelcoming to new analysts.

    Bottom Line: Domo isn't for newcomers but for companies that already have business intelligence (BI) experience in their organization. Domo's a powerful BI tool with a lot of data connectors and solid data visualization capabilities.

    Read Review
  • Pros: Exceptional platform for website and mobile app analytics.

    Cons: Customer support has way too much automation. Focus on marketing and advertising can be frustrating to users. Relies mostly on third parties for training.

    Bottom Line: Due to its brand recognition and the fact that it's free, Google Analytics is the biggest name in website and mobile app intelligence. It has a steep learning curve but it is an awesome business intelligence tool.

    Read Review
  • Pros: Designed with general business users in mind. Solid return on investment.

    Cons: The data you can use is limited. Needs additional platform to connect.

    Bottom Line: The Salesforce Einstein Analytics Platform is designed for customer, sales, and marketing analyses, although it can server other needs, too. Its powerful analytics capabilities along with its solid natural language querying functionality and a wide array of partners make it an attractive offering.

    Read Review
  • Pros: Real-time analytics for Internet of Things (IoT) and streaming data features. Massive ecosystem with plentiful extenders. Responsive pages make mobile publishing easiest. Impressive storytelling paradigm. Centralized view with consolidated analytics.

    Cons: Data prep features are lacking. Confusing toolbar design. Not friendly for beginners.

    Bottom Line: If your business already uses SAP's HANA database platform or some of its other back-end business platforms, then SAP Analytics Cloud is a powerful, well-priced choice. But be warned that there's a steep learning curve and a noted dependence on other SAP products for full functionality.

    Read Review
  • Pros: Impressive processing engine. Powerful query optimization on SQL. Entirely web-based. Complex queries are handled very well.

    Cons: Poorly designed user interface. Steep learning curve.

    Bottom Line: Chartio excels at building a powerful analytics platform that experienced business intelligence (BI) users will appreciate. Those new to BI, however, will find it very difficult to use.

    Read Review
  • Pros: Very deep SQL modeling ability. Uses Git for version management and collaboration.

    Cons: Very expensive. Not for small teams.

    Bottom Line: Looker is a great self-service business intelligence (BI) tool that can help unify SQL and Big Data management across your enterprise.

    Read Review
  • Pros: Custom access roles. Solid collection of public data online.

    Cons: Complex pricing is a deterrent.

    Bottom Line: Qlik Sense Enterprise Server is a self-service business intelligence (BI) tool that delivers the best collection of user access roles among the BI tools we tested, and also demonstrates a promising start towards integrating Data-as-a-Service (DaaS).

    Read Review
  • Pros: One of the largest collections of data connectors. Many granular access roles.

    Cons: No free trial available. Training webinars can be costly.

    Bottom Line: The company's Focus query language is showing its age but Information Builders' self-service business intelligence (BI) tool WebFocus nevertheless has some powerful analysis features.

    Read Review
  • Pros: Very easy to get started. Nice team management and collaboration features.

    Cons: The cloud version has a subset of features found in Windows version. Online documentation could be improved.

    Bottom Line: While Tibco is still making the transition from a desktop to a cloud software vendor, its self-service business intelligence (BI) tool Tibco Spotfire is a great way to start visualizing your Excel data.

    Read Review
  • Pros: Excellent analytical support for Intuit QuickBooks. Very easy setup.

    Cons: Installation and setup is a bit of chore. No support for Intuit QuickBooks' online versions.

    Bottom Line: Clearify QQube is the best self-service business intelligence (BI) tool for in-depth analysis of your Intuit QuickBooks files, though you'll need to look elsewhere for broader BI tasks.

    Read Review


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