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C2090-136 | Foundations of IBM Big Data & Analytics Architecture V1

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C2090-136 - Foundations of IBM Big Data & Analytics Architecture V1 - braindump

Vendor IBM
Exam Number C2090-136
Exam Name Foundations of IBM Big Data & Analytics Architecture V1
Questions 58 Q & A
Recent Update February 15, 2019
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C2090-136 exam Dumps Source : Foundations of IBM Big Data & Analytics Architecture V1

Test Code : C2090-136
Test Name : Foundations of IBM Big Data & Analytics Architecture V1
Vendor Name : IBM
Q&A : 58 Real Questions

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IBM Foundations of IBM Big

forget Oracle, IBM Is a stronger value stock | killexams.com Real Questions and Pass4sure dumps

Some investors see loads of value in Oracle (NYSE:ORCL) shares. The database-software huge's own management, for one, lately referred to as it "an spectacular purchase" and certified another $10 billion of stock buybacks.

this is not always incorrect, however you would not have to look too a long way afield to discover a stronger price stock within the tech sector. presently, it's challenging to beat the lengthy-time period value you're going to get from IBM (NYSE:IBM) shares.

A stack of coins, topped with a bundle of rolled-up $10 bills. There's a shadow of this arrangement on the wall behind it that looks like a rocket in flight.

picture supply: Getty photographs.

Oracle's story

Oracle is a former titan of company on its approach down. a brand new breed of database structures has arrived, challenging not best Oracle's enterprise model but also the technical foundations of its flagship product line. the longer term belongs to so-referred to as NoSQL databases, that could prepare and manipulate unstructured statistics at a scale and speed it's completely alien to Oracle-trend relational databases.

Even Oracle is aware of it and is playing capture-up with its personal cloud-based mostly NoSQL platform. nonetheless it's too little, too late, and Oracle comes with the incorrect variety of street cred to drag off that transformation.

IBM's story

IBM discovered itself in the same condition five years ago. Ex-CEO Sam Palmisano had pulled huge Blue up by using its bootstraps, creating a celebrated business model the place one company offered the entire hardware, utility, and linked services it may take to run a a success IT operation at commercial enterprise scale. Oracle was one of the most many would-be IBM clones that tried to copy Palmisano's impressive template.

however markets exchange, and organizations like IBM and Oracle should change together with the environment in the event that they need to dwell important and a success. huge Blue's existing CEO Ginni Rometty stepped in with a clear imaginative and prescient of dramatic market changes and a mandate to do something became imperative to stay abreast with the brand new times. Rometty did not simply observe that alternate but started spearheading the alternate correct away.

Half-a-decade later, cloud computing is the buzzword of option across the complete IT industry; here is exactly where Rometty was aiming all alongside. The business has sacrificed billions of bucks in annual revenues by using shedding outdated computing-hardware instruments to refocus on cloud-based mostly records analytics and administration. synthetic intelligence performs a big part in IBM's new strategy. So does corporate mobility, and the enterprise is a leading provider of blockchain technologies for company purchasers.

if you're playing buzzword bingo at domestic, your gaming card should be fairly full by means of now. it truly is fine. As I pointed out, IBM is driving lots of these tendencies rather than simply following alongside.

These so-called strategic imperatives accounted for greater than half of IBM's total revenue in 2018 and should only proceed to outgrow the final legacy operations over time. We're looking at a hockey-stick moment for IBM's lengthy-term earnings increase, the place the annual raises should start stacking up very promptly after just a few years of falling earnings. The equal traits should also extend IBM's income margins over the next few years.

The upshot: big Blue is profitable -- and the inventory is low-cost!

IBM's radical method shift has been complicated on its inventory prices. Its shares have misplaced 24% of their price over the remaining 5 years, or a less hair-raising 9% in case you account for its generous dividend payouts along the way. today, IBM shares are buying and selling at just 9.5 times forward salary and 12 instances trailing free money flows. that's a fine cut price for an extended-running turnaround story it is bouncing off the rock-bottom deep conclusion of a five-yr trough.

Glancing over at Oracle, I see an organization struggling to keep up with the altering markets rather than environment the tone for a new period. Its shares are trading for 14 instances forward salary and 16.6 instances trailing money flows. You just can not persuade me that Oracle's shares are a higher purchase than IBM's right now.

Anders Bylund owns shares of IBM. The Motley idiot owns shares of Oracle. The Motley idiot is brief shares of IBM and has the following options: lengthy January 2020 $30 calls on Oracle. The Motley fool has a disclosure policy.


jSonar proclaims an oem contract with IBM protection for its SonarG Database security Platform | killexams.com Real Questions and Pass4sure dumps

WALTHAM, Mass., Feb. eleven, 2019 /PRNewswire-PRWeb/ -- jSonar, a pacesetter in database security and DCAP solutions, nowadays announced that it has entered into an fashioned machine manufacturing (OEM) agreement with IBM security. as a result of this settlement, jSonar's SonarG expertise will integrate into the IBM protection Guardium facts safety portfolio as the new IBM safety Guardium large statistics Intelligence offering.

organizations continue to shift recommendations as they appreciate their facts is a critical asset requiring advanced degrees of visibility and handle. IBM safety Guardium huge statistics Intelligence couples jSonar's SonarG know-how with IBM's proven business-main safety options to create a centralized facility for consolidating records pastime counsel from a lot of sources right into a extremely effective aim-developed safety statistics lake. This records basis is then leveraged to provide business contextual insight in addition to fixing hastily expanding database compliance and safety needs. Key capabilities consist of,

  • huge statistics Scale - instantly installation 200+TB safety statistics lakes and excessive velocity analytics
  • facts Agility - exceptional flexibility of ingestion, integration, facts enrichment and self-provider entry via tons of of tools (e.g. Splunk, Tableau, SQL, provider Now, and so forth.).
  • computerized perception- An resourceful database architecture and AI-primarily based capabilities optimized for analytical workflows, superior pipelining and excessive performance queries.
  • "we're satisfied to be working intently with IBM safety to raise their large records capabilities for Guardium's customer base," spoke of Ron BenNatan, CTO at jSonar. "as the industry expands past traditional database compliance reporting, a vast range of recent use circumstances has emerged that calls for know-how to more with ease address information administration, analysis and business method automation. we have worked carefully with IBM protection to tightly couple our security information lake know-how with their latest data safety structure in order to transparently compile records possibility recreation and deliver an array of latest capabilities to additional enhance the value that both new and present consumers can derive from their Guardium investments."

    Database security trade management jSonar became situated in 2013 with the mission of featuring subsequent generation NoSQL safety analytics platforms. jSonar has been identified as an trade chief via its continuous technical innovation. The company become first recognized by using receiving the prestigious MongoDB Innovation award for its inventive NoSQL analytics equipment. other business firsts include,

  • SonarW: A JSON-native Analytics Platform that delivers ultra-excessive performance, low costs and excessive usability via its entertaining aggregate of simplicity, flexibility and accessibility.
  • DCAP relevant: provides a primary repository for the efficient collection and administration of large information scale, bendy self-provider reporting and long-time period retention. Key improvements include machine-getting to know engines, AI algorithms and functions that discover insights, along with superior integrations enabling highly computerized conclusion to end system flows.
  • SonarG: an entire, unified solution for attaining database security and compliance throughout all of your databases, including on-prem, DBaaS/PaaS and multi-cloud. improvements consist of AI and superior automation to transform large raw experience volumes into actionable assistance, which is then managed by means of completely built-in manner workflows and functions.
  • DBSec2.0 SaaS: Enabling the SonarG Database security and Compliance solution to be comfortably consumed by means of the SaaS mannequin. readily point your audit recreation statistics to DBSec2.0 and interact directly with the provider for protection and compliance insights.
  • These innovations and the OEM relationship with IBM proceed to pressure sizeable revenue growth for jSonar, together with a doubling of income in 2018. jSonar enjoys success with a wide range of trade main corporations in the finance, assurance and retail markets, and projects a further doubling of revenue in 2019.

    For greater assistance suggestions on the latest addition to IBM security's solutions for facts protection, please talk over with https://securityintelligence.com/information/the-vigor-of-a-large-records-platform-goal-developed-for-statistics-safety-requirements/ or watch this informative video.

    About jSonar jSonar gives subsequent-generation safety and compliance options for On-Premise and Cloud implementations based upon its superior SonarC2 technology. complete, "out-of-the box" protection records Lakes and DCAP solutions will also be deployed and delivering cost within days and weeks as opposed to the years needed to advance an in-residence platform. Underlying all solutions is an impressive NoSQL, compressed–columnar records shop coupled with analytical engines that allow extremely-high efficiency and not pricey capture, retention, administration and AI-enhanced. These solutions can implemented both as an on-premise or software as a provider (SaaS) capacity.

     

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    Settling In With IBM i For The lengthy Haul | killexams.com Real Questions and Pass4sure dumps

    February 11, 2019 Timothy Prickett Morgan

    If nothing else, the IBM i platform has exhibited incredible toughness. One may even say legendary toughness, if you want to take its history all the means again to the device/three minicomputer from 1969. this is the real beginning aspect within the AS/400 family unit tree and here's when massive Blue, for terribly sound prison and technical and advertising and marketing motives, determined to fork its items to address the enjoyable wants of enormous organizations (with the equipment/360 mainframe and its comply with-ons) and small and medium groups (starting with the equipment/three and relocating on during the gadget/34, system/32, system/38, and device/36 within the Nineteen Seventies and early Nineteen Eighties and passing through the AS/400, AS/400e, iSeries, equipment i, after which IBM i on vigor programs structures.

    It has been a long run certainly, and many purchasers who've invested within the platform started method back then and there with the early models of RPG and moved their purposes ahead and adjusted them as their agencies evolved and the depth and breadth of company computing modified, moving on up through RPG II, RPG III, RPG IV, ILE RPG, and now RPG free kind. Being on this platform for even three decades makes you a relative newcomer.

    there's a longer run forward, since we agree with that the companies which are still working IBM i systems are the actual diehards, the ones who don't have any intention of leaving the platform and that, as a minimum in response to the survey facts we have been privy too, are desiring to proceed investing in, and even extend their investments in, the IBM i platform.

    thus far, we are not in a recession and heaven willing there are not one, so the priorities that IBM i retail outlets have aren't the ones that they'd a decade ago right through the peak of the exquisite Recession. back then, as turned into the case in just about all IT companies, IBM i retail outlets have been hunkering down and were attempting to reduce expenses in all methods viable, together with deferring equipment enhancements and migrations as well as cutting returned on different initiatives. simplest 29 percent of the 750 IBM i retail outlets that participated within the 2019 IBM i industry Survey, which HelpSystems did again in October 2018, have been involved about cutting back IT spending. here is a remarkably low stage, and i feel is indicative of how particularly effective the economic climate is – excepting one of the vital fits and starts we noticed at the conclusion of 2018 and right here in early 2019 that make us anxious and could delivery inserting pressure on things. here are the good issues as culled from the survey:

    dealing with the increase in facts and in deciding the analytics to chew on that data ranked a little bit bigger on the 2019 IBM i industry Survey than did decreasing prices, and i suppose over the lengthy haul these concerns will become extra essential than modernizing functions and coping with the IBM i talents shortages which are a perennial be concerned. each of these considerations are being solved as new programmers and new equipment to make new interfaces to database purposes are getting extra average and as applied sciences akin to free kind RPG, which appears extra like Java, Python, and Hypertext Preprocessor, are being extra generally deployed and, importantly, can also be picked up more without delay by using programmers experienced with these different languages.

    Given the character of the consumer base, it looks not likely to me that safety and excessive availability will no longer proceed to be fundamental issues, although that the IBM i platform is among the many most relaxed structures on earth (and not simply since it is imprecise, however since it is tremendously difficult to hack) and it has more than a few high availability and disaster healing tools (from IBM, Syncsort, Maxava, and HelpSystems) attainable for those who need to double up their techniques and offer protection to their applications and records. The bar is frequently better than basic backup and restoration for a lot of IBM i retail outlets in the banking, assurance, manufacturing, and distribution industries that dominate the platform. These organizations can’t have safety breaches, and that they can’t have downtime.

    there's a superb quantity of steadiness in the IBM i client base that we think, at this aspect, is reflective within the stability of the IBM i platform and big Blue’s own perception that it needs a fit IBM i platform to have an average in shape power techniques business. all of us understand that the energy methods hardware company has simply became in five quarters of profits boom – some thing we mentioned recently in establishing our own income mannequin for the vigour programs company – but what we didn't recognize, and what you should definitely know, is that within the second and third quarters of 2018, the IBM i element of the enterprise grew enormously quicker than the general vigor methods company, and the best rationale that this did not occur within the closing quarter of 2018 is that income of IBM i machinery in this fall 2017 was fairly potent and represented a extremely tough evaluate. The point is, the IBM i enterprise has been raising the power methods classification normal. (These tips in regards to the IBM i enterprise come compliments of Steve Sibley, vice president and offering supervisor of Cognitive techniques at IBM.)

    IBM’s personal monetary stability of the energy platform – which has been bolstered by means of a circulation into Linux clusters for analytics and excessive efficiency computing simulation and modeling as well as with the aid of the adoption of the HANA in-memory database by using SAP customers on large iron machines including Power8 and now Power9 programs – helps IBM i consumers consider more assured in investing in the present IBM i platform. The recent proof from a few diverse surveys, no longer simply the one completed by using HelpSystems each year, suggests that corporations are via and large both continuing to make investments in the platform or even in some situations are planning to enhance their spending on the IBM i platform in 2019.

    As that you would be able to see, the pattern of funding plans for the IBM i platform, as proven in the chart above, has no longer changed very lots in any respect in the past four years. it is a remarkably strong sample with however a little wiggling here and there that may additionally not even be statistically significant. simply under a quarter of IBM i retail outlets have mentioned during the past 4 years that they plan to raise their funding within the platform in each and every year, and simply beneath half say that they're protecting constant. This does not mean that the equal companies, year after year, are investing greater and other businesses are staying pat, year after yr. it is far more likely that each handful of years – extra like 4 or 5 – customers upgrade their programs and extend their capability, and that they then take a seat tight. The ask yourself is that the cut up isn’t showing a long way fewer companies investing and much extra sitting tight. That more than a tenth of the retail outlets don’t comprehend what their plan is as each prior yr comes to an in depth is somewhat annoying, but it is honest and shows that a good portion of shops produce other priorities other than hardware and operating device improvements. we've pointed out this earlier than and we are able to say it once more: We think that the americans who respond to surveys and browse weekly publications concentrated on the IBM i platform are essentially the most energetic stores – those greater likely to reside pretty existing on hardware and application. So the tempo of adoption for brand spanking new applied sciences, and the rate of investment, should still be bigger than within the precise base, plenty of which doesn't exchange a lot at all.

    So if we had to alter this information to take on the complete base, there might possibly be some distance fewer sites that are investing more funds, far more agencies that are sitting tight, and perhaps fewer sites which are taking into account moving off the IBM i platform. I feel the distribution of facts is doubtless whatever thing like 10 percent of shops have no thought what they are doing investment wise with IBM this 12 months, 5 percent are considering relocating some or all of their purposes to another platform, perhaps 10 % are investing greater this year, and the remaining 75 p.c are sitting tight. here's just a bet, of direction. so far as we can inform, the fee of attrition – what number of websites we actually lose every yr – just a tad over 1 p.c. So the rate of stream of purposes off the platform, or incidences of unplugging IBM i databases and purposes, may additionally not be any place near as high within the average base as the statistics above suggests. what's alarming, in all probability, is that the fee of relocating some or all functions off the platform is balanced in opposition t folks that say they'll boost investments. perhaps these are hopeful survey takers, and those who suppose it's easy to flow locate it is not and those that suppose they will discover the funds to make investments will not.

    What we do be aware of is that if the rate of software attrition became anywhere close as excessive as these surveys imply, then the IBM i business would now not be growing to be, but shrinking. And we are aware of it isn't shrinking, so we suppose there's a disconnect between planning and truth, each on the upside and the downside.

    in case you drill down into the facts for the 2019 IBM i marketplace Survey, there have been 13 % of outlets that observed they'd be relocating some functions to a brand new platform, and a further 9 percent that spoke of they have been going to circulate all of their functions off IBM i. (This number is consistent with the contemporary ALL400s survey executed by using John Rockwell.)

    Anyway, respectable good fortune with that.

    Porting purposes from one platform to one more, of buying a brand new suite on that new platform, is an awfully complicated task. It is not like making an attempt to change a tire while riding down the road, as is a typical metaphor, but rather like attempting to take the tire off one car moving down the highway and installation it on yet another automobile riding beside it in the adjoining lane devoid of crashing either car or smashing into any one else on the highway. Optimism abounds, but when push involves shove, very few organizations are attempting any such maneuver, and when they do, it is constantly as a result of there's a corporate mandate, extra times than no longer caused by using a merger or acquisition, that pits another platform towards IBM i running on energy methods. companies that say they're making this sort of movement off IBM i are sanguine for his or her own very own motives, possibly, however they are not necessarily realistic about how lengthy it could take, what disruption it will cost, and what most desirable benefit, if any, can be realized.

    in case you do the math on the chart above, eight-tenths of the bottom has no theory how long a move will take, one other 1.7 p.c thinks it is going to take more than 5 years, and 3 p.c say it's going to take between two years and 5 years. best 3.four p.c of the overall base say they could do it in under two years. We believe all of those numbers are positive, and the organizations who may easily depart OS/400 and IBM i already did a long time in the past and people that are stay have a tougher time, now not a less complicated time, relocating. If this had been not proper, the IBM i base would be a hell of plenty smaller than the one hundred twenty,000 purchasers we believe are available, in response to what big Blue has instructed us during the past. here is the difference between concern or drive or way of life and the reality of making an attempt to movement a business off one platform and onto another. These moves are always an awful lot more durable than they look on the front end, and we suspect lots of the advantages also don’t materialize for people that do soar systems.

    on the normal attrition expense counseled via this survey records – 9 p.c circulate off the platform in somewhere between three hundred and sixty five days and more than 5 years, with most organizations not being able to see more than five years into the future it truly is a neat trick – the installed base would decrease dramatically. it is difficult to claim how far as a result of the wide selection of timeframes within the survey. If it turned into 9 p.c of the base within two years – name it 4.5 p.c of the bottom per 12 months – then inside a decade the basic base would reduce from 120,000 IBM i sites international right down to about 72,000. this is able to dramatic indeed. however at a 1 % attrition expense per year, the bottom continues to be at 107,500 unique customers (now not websites and never installed machines, both of which are better) by 2029. We suppose there's each probability that the attrition fee will definitely gradual and drop beneath 1 % as IBM demonstrates dedication to the vigor systems platform and its IBM i working equipment. There are at all times some new purchasers being delivered in new markets, to be sure, however the bleed cost (in spite of the fact that it is small) remains likely an order of magnitude greater than the feed price.

    when they do suppose about making the stream, IBM i stores be aware of exactly where they want to go, and this answer has been progressively altering through the years: Linux as a substitute for IBM i is on the upward thrust and windows Server as an option is on the wane. in the newest survey, 52 percent of the corporations that spoke of they have been moving all or a few of their applications to a further platform talked about they had been picking out home windows Server, while 34 percent selected Linux. This displays the relative popularity of home windows Server and Linux within the datacenters of the realm at significant, and may be tipped simply a bit more heavily in opposition t Linux in comparison to the relaxation of the realm. curiously, 10 % of these polled who mentioned they had been relocating have been taking a look at AIX platforms, and a different four percent have been going upscale to system z mainframes – as not likely as this might also seem. structures are inclined to roll downhill; they do not constantly defy gravity like that.

    The element about such surveys is that they show intent, no longer motion. We commonly intend to do much more than we definitely can accomplish, and relocating systems after spending many years of increase skills is not usually a very smart stream except the platform is in true concern – just like the Itanium systems from Hewlett Packard commercial enterprise working OpenVMS or HP-UX or the HP 3000s operating MPE or the Sparc programs from Oracle operating Solaris. These have been as soon as fantastic platforms with big installed bases and colossal earnings streams, however now, IBM is the remaining of those Unix and proprietary systems with its vigor programs line. And it is by a ways the greatest and for certain the only one showing any increase.

    linked reviews

    The IBM i Base Did indeed circulation On Up

    The IBM i Base Is ready to flow On Up

    funding And Integration warning signs For IBM i

    safety nevertheless Dominates IBM i discussion, HelpSystems’ 2018 Survey displays

    The IBM i Base not As Jumpy because it Has Been

    The Feeds And Speeds Of The IBM i Base

    IBM i Priorities For 2017: Pivot To defense

    IBM i developments, issues, And Observations

    IBM i Survey gets more suitable As Numbers grow

    the place Do those IBM i Machines Work?

    finding IBM i: A online game Of forty Questions

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    IBM i market Survey: The value Of Being Earnest

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    IBM i market Survey Fills within the Blanks


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    Elke Rundensteiner, right, professor of computer science at Worcester Polytechnic Institute (WPI), and PhD student Allison Rozet, stand beside an autonomous vehicle testbed used in research at WPI. The analytics tools Rundensteiner and Rozet are developing could make driverless cars safer by analyzing data streaming from vehicles in real time. Credit: Worcester Polytechnic Institute

    A new big data analytic tool being developed by computer scientists at Worcester Polytechnic Institute (WPI) will help businesses make sense, in real time, of the deluge of data that streams at them like water from a fire hose.

    With a three-year, $499,753 grant from the National Science Foundation, Elke Rundensteiner, professor of computer science and director of WPI's Data Science Program, is leading a team of computer science and data science students that is building a next-generation event trend analysis tool known as SETA (Scalable Event Trend Analytics). This open-source software will be used not just to find patterns in real-time, high-volume data streams ("data in motion"), but to analyze those patterns and make sense of them on the fly for just-in-time decision making.

    SETA could enable large businesses, social media sites, fraud detection centers, autonomous vehicle networks, governments, and other users to harness the continuous flow of big data as it streams in and transform it into actionable insights that could allow them to be increasingly responsive and competitive. "In a world where big data is continuously accelerating in volume and velocity, real-time streaming data analysis has become increasingly critical," said Rundensteiner, an internationally recognized expert in scalable data stream processing.

    Event processing is a way to track and analyze incoming streams of information, such as online purchases, the rise and fall of a stock price, the length of time users remain on a website, or whether healthcare workers wash their hands before entering patients' rooms. It's all about flagging important events in the incoming data, so an organization can respond to them in real time. SETA will be able to handle complex queries and analytics, while providing users summarized insights cheaper and faster than is currently possible.

    Most existing data analysis tools are not designed to work with streaming data, Rundensteiner noted. Instead, information must be stored in a static database before it can be analyzed, introducing a delay that might prevent the fast detection, for example, of the start of an infectious disease outbreak in a hospital. Rundensteiner's tools operate on the data as it is being generated, allowing even complex patterns to be spotted in real time, so critical decisions can be made quickly.

    "Data streams are increasing at a dramatic rate, overwhelming businesses that can't make sense of their data in real time," Rundensteiner said. "By finding ways to handle these live streams, we are breaking new ground in data analytics. You could stick all this big data into a static database and look at it later, but if you want to catch a fraudulent credit card purchase as it's happening or alert a network of autonomous cars about an accident ahead, you need to analyze that information as it's streaming in at the rate of tens of thousands of pieces of data per microsecond."

    With the new award, Rundensteiner will build upon her previous NSF-sponsored research in event stream analytics, which focused on finding patterns in streaming data. That work (in collaboration with former Ph.D. students, Olga Poppe, a research scientist at Microsoft Gray Systems Lab, Chuan Lei, a research staff member at IBM Almaden Research Center, and Di Wang, a research scientist at Facebook), produced analytics tools that enabled users to query a data stream for relatively simple event sequences. But if the software found many instances of the same or similar sequences and displayed them all, the user would often become overwhelmed and miss the significant patterns or the overall trends across patterns.

    Rather than displaying detected sequences one by one, the new tool Rundensteiner is developing will aggregate those patterns and show the user how many times each occurs. "By showing a spike of abnormal activity, the system lets you very quickly see what is going on," she said. "Sometimes I'm more interested in the deviation from the typical count of patterns because then I instantly know if something abnormal is happening. If one autonomous car is swerving, that might mean nothing. But if a thousand cars on the same stretch of road all exhibit deviating behavior, then something real is happening. You can then dig deeper into that particular subset of data to explore this unexpected behavior."

    Developing the tools to dig deeper into these pattern aggregates is another element of the research on SETA. Rundensteiner wants to empower users to look for far more sophisticated patterns. For example, while her previous tool could be used to look for a sequence of a fixed length (say, instances of a vehicle activating the brakes, swerving, and then stopping), she wants to make it possible, with a single simple stream query, to spot sequences involving an unbounded number of instances (a car swerving an unknown number of times, braking repeatedly, and then coming to a stop, for example). While the number of potential matches to such a query could grow exponentially due to the complexity of the query language, the results promise to be more useful, she said.

    To create new event trends analytics tools, Rundensteiner must first design a new query language, which is used to find and retrieve patterns in the data. By allowing users to search for more complicated patterns, the new language will make the tool significantly easier to use. She is also building a new "query engine" to process these sophisticated queries and find the requested patterns or events. A distributed engine, it will run on multiple servers across a cloud network, dramatically increasing its speed.

    "Building that engine is a key part of the project," she said. "Traditionally, an engine might generate all the answers to a query, store them, and then start counting them. That's too time-consuming and expensive. Current technology might take hours, or even longer, to process a complicated query. Ours will take a few seconds. There's no point in asking these big questions if you have to wait days for the answers."

    The new event trends analytics software, which she is developing with Allison Rozet, a Ph.D. candidate in data science, will be tested using real-world datasets and applications supplied by a health care center and a financial transaction processing company.

    "In the health care field, this could save lives," Rundensteiner said. "We could detect patterns that show how infection is spreading. We could see when, for example, staff are not putting on surgical gowns or washing their hands. We can thus see problems as they unfold, so we can see where the problems are originating. We're making better tools to get the answers we need from a growing flood of incoming information."

    Explore further: New platform to help business tap full potential of big data


    Worcester Polytechnic Institute Computer Scientists Develop Big Data Analytics Tools To Make Sense of Streaming Data in Real Time | killexams.com real questions and Pass4sure dumps

    With support from the National Science Foundation, a team at Worcester Polytechnic Institute is developing software to help organizations in a range of fields, including transportation and health care, make data-driven decisions in real time.

    WORCESTER, Mass., Jan. 28, 2019 /PRNewswire-PRWeb/ -- A new big data analytic tool being developed by computer scientists at Worcester Polytechnic Institute (WPI) will help businesses make sense, in real time, of the deluge of data that streams at them like water from a fire hose.

    With a three-year, $499,753 grant from the National Science Foundation, Elke Rundensteiner, professor of computer science and director of WPI's Data Science Program, is leading a team of computer science and data science students that is building a next-generation event trend analysis tool known as SETA (Scalable Event Trend Analytics). This open-source software will be used not just to find patterns in real-time, high-volume data streams ("data in motion"), but to analyze those patterns and make sense of them on the fly for just-in-time decision making.

    SETA could enable large businesses, social media sites, fraud detection centers, autonomous vehicle networks, governments, and other users to harness the continuous flow of big data as it streams in and transform it into actionable insights that could allow them to be increasingly responsive and competitive. "In a world where big data is continuously accelerating in volume and velocity, real-time streaming data analysis has become increasingly critical," said Rundensteiner, an internationally recognized expert in scalable data stream processing.

    Event processing is a way to track and analyze incoming streams of information, such as online purchases, the rise and fall of a stock price, the length of time users remain on a website, or whether healthcare workers wash their hands before entering patients' rooms. It's all about flagging important events in the incoming data, so an organization can respond to them in real time. SETA will be able to handle complex queries and analytics, while providing users summarized insights cheaper and faster than is currently possible.

    Most existing data analysis tools are not designed to work with streaming data, Rundensteiner noted. Instead, information must be stored in a static database before it can be analyzed, introducing a delay that might prevent the fast detection, for example, of the start of an infectious disease outbreak in a hospital. Rundensteiner's tools operate on the data as it is being generated, allowing even complex patterns to be spotted in real time, so critical decisions can be made quickly.

    "Data streams are increasing at a dramatic rate, overwhelming businesses that can't make sense of their data in real time," Rundensteiner said. "By finding ways to handle these live streams, we are breaking new ground in data analytics. You could stick all this big data into a static database and look at it later, but if you want to catch a fraudulent credit card purchase as it's happening or alert a network of autonomous cars about an accident ahead, you need to analyze that information as it's streaming in at the rate of tens of thousands of pieces of data per microsecond."

    With the new award, Rundensteiner will build upon her previous NSF-sponsored research in event stream analytics, which focused on finding patterns in streaming data. That work (in collaboration with former PhD students, Olga Poppe, a research scientist at Microsoft Gray Systems Lab, Chuan Lei, a research staff member at IBM Almaden Research Center, and Di Wang, a research scientist at Facebook), produced analytics tools that enabled users to query a data stream for relatively simple event sequences. But if the software found many instances of the same or similar sequences and displayed them all, the user would often become overwhelmed and miss the significant patterns or the overall trends across patterns.

    Rather than displaying detected sequences one by one, the new tool Rundensteiner is developing will aggregate those patterns and show the user how many times each occurs. "By showing a spike of abnormal activity, the system lets you very quickly see what is going on," she said. "Sometimes I'm more interested in the deviation from the typical count of patterns because then I instantly know if something abnormal is happening. If one autonomous car is swerving, that might mean nothing. But if a thousand cars on the same stretch of road all exhibit deviating behavior, then something real is happening. You can then dig deeper into that particular subset of data to explore this unexpected behavior."

    Story continues

    Developing the tools to dig deeper into these pattern aggregates is another element of the research on SETA. Rundensteiner wants to empower users to look for far more sophisticated patterns. For example, while her previous tool could be used to look for a sequence of a fixed length (say, instances of a vehicle activating the brakes, swerving, and then stopping), she wants to make it possible, with a single simple stream query, to spot sequences involving an unbounded number of instances (a car swerving an unknown number of times, braking repeatedly, and then coming to a stop, for example). While the number of potential matches to such a query could grow exponentially due to the complexity of the query language, the results promise to be more useful, she said.

    To create new event trends analytics tools, Rundensteiner must first design a new query language, which is used to find and retrieve patterns in the data. By allowing users to search for more complicated patterns, the new language will make the tool significantly easier to use. She is also building a new "query engine" to process these sophisticated queries and find the requested patterns or events. A distributed engine, it will run on multiple servers across a cloud network, dramatically increasing its speed.

    "Building that engine is a key part of the project," she said. "Traditionally, an engine might generate all the answers to a query, store them, and then start counting them. That's too time-consuming and expensive. Current technology might take hours, or even longer, to process a complicated query. Ours will take a few seconds. There's no point in asking these big questions if you have to wait days for the answers."

    The new event trends analytics software, which she is developing with Allison Rozet, a PhD candidate in data science, will be tested using real-world datasets and applications supplied by a health care center and a financial transaction processing company.

    "In the health care field, this could save lives," Rundensteiner said. "We could detect patterns that show how infection is spreading. We could see when, for example, staff are not putting on surgical gowns or washing their hands. We can thus see problems as they unfold, so we can see where the problems are originating. We're making better tools to get the answers we need from a growing flood of incoming information."

    About Worcester Polytechnic Institute

    WPI, a global leader in project-based learning, is a distinctive, top-tier technological university founded in 1865 on the principle that students learn most effectively by applying the theory learned in the classroom to the practice of solving real-world problems. Recognized by the National Academy of Engineering with the 2016 Bernard M. Gordon Prize for Innovation in Engineering and Technology Education, WPI's pioneering project-based curriculum engages undergraduates in solving important scientific, technological, and societal problems throughout their education and at more than 45 project centers around the world. WPI offers more than 50 bachelor's, master's, and doctoral degree programs across 14 academic departments in science, engineering, technology, business, the social sciences, and the humanities and arts. Its faculty and students pursue groundbreaking research to meet ongoing challenges in health and biotechnology; robotics and the internet of things; advanced materials and manufacturing; cyber, data, and security systems; learning science; and more. http://www.wpi.edu

    Media contact:Colleen Wamback, Public Relations ManagerWorcester Polytechnic InstituteWorcester, Massachusetts508-831-6775; cbwamback@wpi.edu

     


    Big Data and Cognitive Business Disruption is all You Need to Know | killexams.com real questions and Pass4sure dumps

    The future has arrived. Today, computers can nearly mimic the human mind’s ability to learn, think, reason, analyze and make decisions. This technology is called cognitive computing.

    Often, cognitive computing is confused with other emerging data science advancements such as business intelligence (BI), deep learning (DL) and machine learning (ML).

    However, what differentiates cognitive computing from these other amazing technologies is that it can read and comprehend “dark data.”

    Dark data is commonly known as unstructured information.

    This kind of data is not conducive to analysis by BI, DL or ML technologies. As a result, cognitive computing is vitally important, as technology experts report that unstructured data represents 80-percent of the sum of the world’s digital information.

    Resultantly, enterprise leaders need skilled data science professionals who can prevent information bias, leverage unstructured data for decision-making and increase the speed and accuracy of data analysis. Despite the ability of cognitive technology to “think,” this kind of resource always requires a skilled operator.

    Humans must always be in control and have the ability to explain to stakeholders how data is being used, how it’s managed it how it’s protected. No matter how advanced the technology, humans must stay at the helm to ensure security and safety.

    Big Data and Cognitive Disruption

    According to a recent IBM report, unstructured data will represent 90-percent of all information as soon as 2020. This information comes from images, sensors, videos, audio files and telephony data.

    Cognitive systems build on current advanced big data technologies by reducing much of the programming required to perform effective analyses.

    Prior to this innovation, data scientists had to explicitly program systems to perform desired functions. Because of this, analysis frameworks prior to cognitive systems couldn’t perform outside of programmed scenarios.

    Alternatively, cognitive analysis systems have critical thinking abilities that mimic the human mind. They analyze, learn and understand, without the need for programmer intervention. Still, the foundation of cognitive computing lies in assisting mankind – not replacing it.

    IBM’s survey revealed that 73-percent of polled CEOs from around the world plan to deploy cognitive computing in their operations. Additionally, 75-percent of the group believes that cognitive technology will disrupt their industry soon.

    Creating a New Discipline for Marketers

    In marketing, advanced analysis technologies magnify the abilities of professionals working in the field. As an example, personalization, consumer-centric strategy and long-term relationship building are essential for promoting sustainable positive enterprise outcomes.

    Advanced analysis systems help marketers deliver the right messages to the right customers at the right time.

    In addition, technologies such as cognitive computing help marketing professionals discover opportunities that no human being could ever hope to find using manual research methods. By extrapolating data from social media sites, email communications and website metrics, marketers can leverage advanced analysis systems to build a strong rapport with and create valuable experiences for their audiences.

    Still, cognitive systems have a long way to go before mastering emotional intelligence and creativity.

    For now, enterprises need skilled marketers for their storytelling and creative skills to create messages that resonate with potential buyers.

    Data is still key to understanding consumer behavior, but with advanced data analysis systems, marketers can make sense of seemingly immeasurable amounts of information and drive corporate success. While data analysis provides insight, marketers turn those insights into actions that produce tangible value.

    Impacting the Road Ahead

    Advanced technologies such as cognitive intelligence, predictive analytics and machine learning build on the foundation of big data systems. Now, with the introduction of cognitive intelligence technology, cutting-edge data analysis systems emulate the complexity of the human mind.

    Today, data scientists must teach cognitive intelligence technology how to learn. Tomorrow, the technology will teach itself.

    The number of executives who plan to leverage this remarkable new technology in 2019 may seem astounding, but the reasoning behind this is crystal clear. Still, deploying cognitive intelligence systems in conjunction with existing enterprise analysis technology will prove challenging.

    IBM’s Watson technology, for instance, took decades to assemble, cost hundreds of millions of dollars and required the work of thousands of highly talented engineers.

    For now, this bleeding-age technology will be inaccessible to all but the most resource-rich enterprises. Still, some firms who are not quite within the upper echelon of corporate influence may be able to leverage the technology by partnering with the right software-as-a-service (SaaS) vendor.

    In the IBM survey, the executives who reported the largest economic benefits believe that advanced technologies, such as cognitive intelligence, are best leveraged for transformational rather than incremental change. In other words, executives believe that cognitive intelligence is a tool for disruptive transformation.

    Conclusion

    Early adopters of cognitive technology expect that the innovative resource will have a major impact on commerce.

    Already, advanced analysis systems are heavily impacting and changing how enterprises conduct business. If this trend continues, advanced analysis systems may live up to the hype promoted by the global media and the world’s information technology service notice he got me all stirred of this will be to first falcon thing on my mind in the morning providers.

    Ryan Ayers

    Ryan Ayers is a researcher and consultant within multiple industries including information technology, blockchain and business development. Always up for a challenge, Ayers enjoys working with startups as well as Fortune 500 companies. When not at work, Ayers loves reading science fiction novels and watching the LA Clippers.



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