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70-776 | Performing Big Data Engineering with Microsoft Cloud Services

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70-776 - Performing Big Data Engineering with Microsoft Cloud Services - braindump

Vendor Microsoft
Exam Number 70-776
Exam Name Performing Big Data Engineering with Microsoft Cloud Services
Questions 69 Q & A
Recent Update May 14, 2019
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Test Code : 70-776
Test Name : Performing Big Data Engineering with Microsoft Cloud Services
Vendor Name : Microsoft
Q&A : 69 Real Questions

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Performing Big Data Engineering with Microsoft Cloud Services education

a way to improve supply Chains With computer researching: 10 proven methods | 70-776 Real Questions and VCE Practice Test

bottom line: corporations are attaining double-digit advancements in forecast error rates, demand planning productivity, can charge discounts and on-time shipments the usage of computer discovering today, revolutionizing give chain management within the technique.

computer learning algorithms and the fashions they’re based on excel at discovering anomalies, patterns and predictive insights in enormous information units. Many supply chain challenges are time, cost and aid constraint-based mostly, making desktop discovering an ideal technology to solve them. From Amazon’s Kiva robotics counting on computer researching to improve accuracy, pace and scale to DHL counting on AI and laptop learning to energy their Predictive community administration system that analyzes fifty eight distinct parameters of interior information to establish the precise components influencing cargo delays, computing device learning is defining the next technology of give chain administration. Gartner predicts that with the aid of 2020, 95% of deliver Chain Planning (SCP) vendors will be relying on supervised and unsupervised computer learning of their solutions. Gartner is also predicting via 2023 clever algorithms, and AI options should be an embedded or augmented element across 25% of all supply chain expertise options.

The ten ways that machine getting to know is revolutionizing deliver chain administration consist of:

  • desktop studying-primarily based algorithms are the basis of the subsequent era of logistics applied sciences, with essentially the most colossal gains being made with advanced useful resource scheduling programs. machine discovering and AI-based concepts are the groundwork of a extensive spectrum of next-technology logistics and provide chain applied sciences now beneath building. probably the most gigantic good points are being made the place machine researching can make a contribution to fixing complex constraint, cost and start problems companies face today. McKinsey predicts machine gaining knowledge of’s most giant contributions will be in presenting give chain operators with extra colossal insights into how supply chain performance will also be superior, watching for anomalies in logistics charges and performance before they happen. laptop learning is additionally featuring insights into the place automation can convey probably the most tremendous scale advantages. source: McKinsey & business, Automation in logistics: large possibility, greater uncertainty, April 2019. by way of Ashutosh Dekhne, Greg Hastings, John Murnane, and Florian Neuhaus
  • supply: McKinsey & enterprise, Automation in logistics: huge possibility, greater uncertainty, April 2019. via Ashutosh Dekhne, Greg Hastings, John Murnane, and Florian Neuhaus

  • The wide adaptation in data sets generated from the web of things (IoT) sensors, telematics, intelligent transport methods, and traffic information have the skills to carry the most value to enhancing supply chains through the use of laptop gaining knowledge of. applying machine discovering algorithms and concepts to increase give chains starts with records units which have the most suitable variety and variability in them. probably the most challenging considerations provide chains face are sometimes present in optimizing logistics, so materials vital to complete a production run arrive on time. source: KPMG, deliver Chain huge data sequence part 1
  • supply: KPMG, supply Chain large statistics collection part 1

  • computing device gaining knowledge of indicates the talents to cut back logistics charges by way of discovering patterns in tune-and-trace statistics captured the use of IoT-enabled sensors, contributing to $6M in annual discount rates. BCG these days looked at how a decentralized deliver chain the usage of tune-and-hint purposes could improve performance and in the reduction of costs. They found that in a 30-node configuration when blockchain is used to share facts in actual-time across a supplier community, mixed with more suitable analytics perception, can charge rate reductions of $6M a yr is practicable. source: Boston Consulting community, Pairing Blockchain with IoT to cut deliver Chain fees, December 18, 2018, by Zia Yusuf, Akash Bhatia, Usama Gill, Maciej Kranz, Michelle Fleury, and Anoop Nannra
  • Boston Consulting group, Pairing Blockchain with IoT to cut deliver Chain charges, December 18, 2018, via Zia Yusuf , Akash Bhatia , Usama Gill , Maciej Kranz, Michelle Fleury, and Anoop Nannra

  • cutting back forecast error up to 50% is attainable the usage of desktop getting to know-based recommendations. misplaced revenue as a result of products now not being attainable are being reduced up to sixty five% by using computing device researching-based planning and optimization recommendations. inventory discounts of 20 to 50% are additionally being performed these days when desktop discovering-based give chain administration systems are used. source: Digital/McKinsey, Smartening up with synthetic Intelligence (AI) - What’s in it for Germany and its Industrial Sector? (PDF, fifty two pp., no choose-in).
  • source: Digital/McKinsey, Smartening up with synthetic Intelligence (AI) - What’s in it for Germany and its Industrial Sector? (PDF, fifty two pp., no choose-in).

  • DHL research is finding that desktop getting to know allows for logistics and provide chain operations to optimize capability utilization, enrich client adventure, in the reduction of risk, and create new enterprise models. DHL’s research group normally tracks and evaluates the affect of emerging technologies on logistics and provide chain efficiency. They’re also predicting that AI will enable lower back-workplace automation, predictive operations, clever logistics property, and new consumer adventure models. source: DHL fashion analysis, Logistics fashion Radar, edition 2018/2019 (PDF, 55 pp., no decide-in)
  • supply: DHL fashion analysis, Logistics trend Radar, edition 2018/2019 (PDF, fifty five pp., no decide-in)

  • Detecting and acting on inconsistent organisation first-rate levels and deliveries using desktop studying-primarily based functions is a local manufacturers are investing in today. based on conversations with North American-based mid-tier manufacturers, the 2nd most tremendous boom barrier they’re dealing with nowadays is suppliers’ lack of constant quality and delivery performance. The premier increase barrier is the shortcoming of knowledgeable labor attainable. using machine getting to know and superior analytics producers can discover right away who their highest quality and worst suppliers are, and which creation centers are most accurate in catching errors. manufacturers are the usage of dashboards a great deal like the one beneath for applying computer discovering to agency quality, beginning and consistency challenges. supply: Microsoft, corporation first-rate analysis sample for vigour BI: Take a tour, 2018
  • supply: Microsoft, enterprise fine evaluation pattern for power BI: Take a tour, 2018

  • decreasing chance and the talents for fraud, while improving the product and manner exceptional according to insights gained from computer discovering is forcing inspection’s inflection element throughout supply chains these days. When inspections are automatic using mobile technologies and results are uploaded in precise-time to a secure cloud-primarily based platform, desktop researching algorithms can carry insights that immediately cut back risks and the advantage for fraud. Inspectorio is a machine gaining knowledge of startup to watch during this area. They’re tackling the various complications that a lack of inspection and supply chain visibility creates, focusing on how they could remedy them automatically for manufacturers and retailers. The picture beneath explains their platform. source: Forbes, How computer gaining knowledge of Improves Manufacturing Inspections, Product high-quality & provide Chain Visibility, January 23, 2019
  • source: Forbes, How desktop learning Improves Manufacturing Inspections, Product pleasant & provide Chain Visibility, January 23, 2019

  • machine discovering is making fast beneficial properties in conclusion-to-conclusion supply chain visibility feasible, presenting predictive and prescriptive insights which are assisting corporations react quicker than earlier than. Combining multi-enterprise commerce networks for global alternate and provide chain administration with AI and laptop researching systems are revolutionizing provide chain conclusion-to-end visibility. one of the most early leaders in this enviornment is Infor’s manage core. control middle combines statistics from the Infor GT Nexus Commerce community, got through the business in September 2015, with Infor’s Coleman synthetic Intelligence (AI) Infor selected to name their AI platform after the inspiring physicist and mathematician Katherine Coleman Johnson, whose path-blazing work helped NASA land on the moon. be certain to opt for up a copy of the publication and notice the film Hidden Figures if you haven’t already to recognize her and a lot of other astounding girls mathematicians’ many contributions to space exploration. ChainLink analysis provides an overview of control center of their article, How Infor is helping to recognise Human abilities, and two screens from control middle are proven under.
  • ChainLink research, How Infor is helping to understand Human knowledge,

  • desktop getting to know is proving to be foundational for thwarting privileged credential abuse which is the main cause of security breaches throughout world deliver chains. through taking a least privilege entry method, businesses can cut assault surfaces, improve audit and compliance visibility, and cut back risk, complexity, and the charges of operating a modern, hybrid enterprise. CIOs are solving the paradox of privileged credential abuse of their give chains by way of understanding that notwithstanding a privileged user has entered the correct credentials but the request is available in with harmful context, then greater verification is required to enable entry.  Zero have confidence Privilege is rising as a proven framework for thwarting privileged credential abuse via verifying who is requesting access, the context of the request, and the possibility of the access ambiance.  Centrify is a leader in this area, with globally-diagnosed suppliers together with Cisco, Intel, Microsoft, and Salesforce being existing consumers.  source: Forbes, excessive-Tech's most effective problem should be Securing supply Chains In 2019, November 28, 2018
  • Capitalizing on machine researching to foretell preventative protection for freight and logistics machinery in response to IoT data is improving asset utilization and reducing operating charges. McKinsey discovered that predictive protection better by using laptop studying allows for for better prediction and avoidance of laptop failure by way of combining records from the advanced internet of things (IoT) sensors and renovation logs as well as exterior sources. Asset productivity raises of up to twenty% are possible and standard preservation prices may be reduced by means of up to 10%. supply: Digital/McKinsey, Smartening up with artificial Intelligence (AI) - What’s in it for Germany and its Industrial Sector? (PDF, fifty two pp., no opt-in).
  • References

    Accenture, Reinventing The deliver Chain With AI, 20 pp., PDF, no opt-in.

    Bendoly, E. (2016). healthy, Bias, and Enacted Sensemaking in information Visualization: Frameworks for continuous development in Operations and provide Chain administration Analytics. Journal Of company Logistics, 37(1), 6-17.

    Boston Consulting community, Pairing Blockchain with IoT to cut provide Chain expenses, December 18, 2018, through Zia Yusuf, Akash Bhatia, Usama Gill, Maciej Kranz, Michelle Fleury, and Anoop Nannra

    Capgemini, provide Chain administration – The Quiet Revolution. April 24, 2019

    CB Insights, Stocked Up: one hundred fifty+ organizations Attacking The supply Chain & Logistics house, November 30, 2016

    Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the use of huge facts Analytics impacts price advent in deliver Chain management. Journal Of administration suggestions techniques, 32(4), 4-39.

    Council of give Chain administration experts (CSCMP) provide Chain Quarterly, desktop discovering: a brand new tool for improved forecasting, Joseph Shamir, q4, 2014

    Council of deliver Chain administration specialists (CSCMP) supply Chain Quarterly, Paving the style for AI in the warehouse, Luke Waltz   Quarter 1 2018 situation

    DHL, artificial Intelligence in Logistics, 2018 (PDF, forty five pp., no opt-in)

    DHL, Cracking Logistics with the aid of laptop getting to know, Harvard enterprise school, November 13, 2018

    DHL, Logistics vogue Radar, 2016 (PDF, fifty five pp., no opt-in)

    DHL vogue research, synthetic Intelligence in Logistics, 2018 (PDF, forty five pp., no decide-in)

    DHL fashion analysis, Logistics vogue Radar, version 2018/2019 (PDF, fifty five pp., no opt-in)

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    Feizabadi, J., & Shrivastava, A. (2018). Does AI-enabled demand forecasting enhance supply chain efficiency? supply Chain administration assessment, 22(6), eight-10.

    Gartner, provide Chain trends within the Digital Age, February 17, 2016 (PDF, 9 pp., no choose-in)

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    Hahn, G. J., & Packowski, J. (2015). A standpoint on applications of in-reminiscence analytics in supply chain management. decision aid programs, 7645-52.

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