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Smart Data Module 6 d drive the future

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Smart Data Module 6 d drive the future

  1. 1. D: DRIVE How to become Data Driven? This programme has been funded with support from the European Commission Module 6: The Future of Big and Smart Data
  2. 2. Smart Data Smart Region | www.smartdata.how This programme has been funded with support from the European Commission. The author is solely responsible for this publication (communication) and the Commission accepts no responsibility for any use that may be made of the information contained therein. The objective of this module is to take a look into what big data can bring you in the future. Upon completion of this module you will: - See what are the predictions for the future of Big Data - Take a look at some trends that are emerging - Get an overview of possible opportunites your company can have with Big Data - Face some of the start up challenges you might have with Big Data Duration of the module: approximately 1 – 2 hours Module 6: The Future of Big and Smart Data
  3. 3. 1 Trends2 Opportunities3 Smart Data Smart Region | www.smartdata.how This programme has been funded with support from the European Commission. The author is solely responsible for this publication (communication) and the Commission accepts no responsibility for any use that may be made of the information contained therein. 4 Challenges Predictions
  4. 4. PREDICTIONS Smart Data Smart Region | www.smartdata.how
  5. 5. MACHINE LEARNING WILL BE THE NEXT BIG THING IN BIG DATA 1 Smart Data Smart Region | www.smartdata.how
  6. 6. PRIVACY WILL BE THE BIGGEST CHALLENGE Smart Data Smart Region | www.smartdata.how 2
  7. 7. CHIEF DATA OFFICER: A NEW POSITION WILL EMERGE Smart Data Smart Region | www.smartdata.how 3
  8. 8. DATA SCIENTISTS WILL BE IN HIGH DEMAND Smart Data Smart Region | www.smartdata.how 4
  9. 9. BUSINESSES WILL BUY ALGORITHMS, INSTEAD OF SOFTWARE Smart Data Smart Region | www.smartdata.how 5
  10. 10. INVESTMENTS IN BIG DATA TECHNOLOGIES WILL SKYROCKET Smart Data Smart Region | www.smartdata.how 6
  11. 11. MORE DEVELOPERS WILL JOIN THE BIG DATA REVOLUTION Smart Data Smart Region | www.smartdata.how 7
  12. 12. PRESCRIPTIVE ANALYTICS WILL BECOME AN INTEGRAL PART OF BI SOFTWARE Smart Data Smart Region | www.smartdata.how 8
  13. 13. BIG DATA WILL HELP YOU BREAK PRODUCTIVITY RECORDS Smart Data Smart Region | www.smartdata.how 9
  14. 14. WILL BIG DATA BE REPLACED BY FAST AND ACTIONABLE DATA? Smart Data Smart Region | www.smartdata.how 10
  15. 15. Every company has Big Data in its future and every company will eventually be in the data business. Thomas H. Davenport Smart Data Smart Region | www.smartdata.how
  16. 16. TRENDS Smart Data Smart Region | www.smartdata.how
  17. 17. Big Data and Open Source Open source applications like Apache Hadoop, Spark and others have come to dominate the big data space, and that trend looks likely to continue. One survey found that nearly 60 percent of enterprises expect to have Hadoop clusters running in production by the end of this year. And according to Forrester, Hadoop usage is increasing 32.9 percent per year. Experts say that many enterprises will expand their use of Hadoop and NoSQL technologies, as well as looking for ways to speed up their big data processing. Many will be seeking technologies that allow them to access and respond to data in real time. Hadoop is a high profile example of an open source Big Data project. Smart Data Smart Region | www.smartdata.how
  18. 18. In-Memory Technology One of the technologies that companies are investigating in an attempt to speed their big data processing is in-memory technology. In a traditional database, the data is stored in storage systems equipped with hard drives or solid state drives (SSDs). In-memory technology stores the data in RAM instead, which is many, many times faster. A report from Forrester Research forecasts that in-memory data fabric will grow 29.2 percent per year. Several different vendors offer in-memory database technology, notably SAP, IBM, Pivotal. Smart Data Smart Region | www.smartdata.how
  19. 19. Machine Learning As big data analytics capabilities have progressed, some enterprises have begun investing in machine learning (ML). Machine learning is a branch of artificial intelligence that focuses on allowing computers to learn new things without being explicitly programmed. In other words, it analyzes existing big data stores to come to conclusions which change how the application behaves. According to Gartner machine learning is one of the top 10 strategic technology trends. It noted that today's most advanced machine learning and artificial intelligence systems are moving "beyond traditional rule-based algorithms to create systems that understand, learn, predict, adapt and potentially operate autonomously." Machine Learning Process Smart Data Smart Region | www.smartdata.how
  20. 20. Predictive Analytics Predictive analytics is closely related to machine learning; in fact, ML systems often provide the engines for predictive analytics software. In the early days of big data analytics, organizations were looking back at their data to see what happened and then later they started using their analytics tools to investigate why those things happened. Predictive analytics goes one step further, using the big data analysis to predict what will happen in the future. The number of organizations using predictive analytics today is surprisingly low— only 29 percent according to a 2016 survey from PwC. However, numerous vendors have recently come out with predictive analytics tools, so that number could skyrocket in the coming years as businesses become more aware of this powerful tool. The process of Predictive Analytics Smart Data Smart Region | www.smartdata.how
  21. 21. Big Data Intelligent Apps Another way that enterprises are using machine learning and AI technologies is to create intelligent apps. These applications often incorporate big data analytics, analyzing users' previous behaviors in order to provide personalization and better service. One example that has become very familiar is the recommendation engines that now power many ecommerce and entertainment apps. In its list of Top 10 Strategic Technology Trends, Gartner listed intelligent apps second. "Over the next 10 years, virtually every app, application and service will incorporate some level of AI," said David Cearley, vice president and Gartner Fellow. "This will form a long-term trend that will continually evolve and expand the application of AI and machine learning for apps and services." Smart Data Smart Region | www.smartdata.how
  22. 22. Intelligent Security Many enterprises are also incorporating big data analytics into their security strategy. Organizations' security log data provides a treasure trove of information about past cyberattack attempts that organizations can use to predict, prevent and mitigate future attempts. As a result, some organizations are integrating their security information and event management (SIEM) software with big data platforms like Hadoop. Others are turning to security vendors whose products incorporate big data analytics capabilities. Smart Data Smart Region | www.smartdata.how
  23. 23. Internet of Things (IoT) The Internet of Things is also likely to have a sizable impact on big data. According to a report from IDC, "31.4 percent of organizations surveyed have launched IoT solutions, with an additional 43 percent looking to deploy in the next 12 months." With all those new devices and applications coming online, organizations are going to experience even faster data growth than they have experienced in the past. Many will need new technologies and systems in order to be able to handle and make sense of the flood of big data coming from their IoT deployments. Growth of the Internet of Things Smart Data Smart Region | www.smartdata.how Complete Exercise 1 of Learners workbook #6 to see how well do you really know IoT
  24. 24. Edge Computing One new technology that could help companies deal with their IoT big data is edge computing. In edge computing, the big data analysis happens very close to the IoT devices and sensors instead of in a data center or the cloud. For enterprises, this offers some significant benefits. They have less data flowing over their networks, which can improve performance and save on cloud computing costs. It allows organizations to delete IoT data that is only valuable for a limited amount of time, reducing storage and infrastructure costs. Edge computing can also speed up the analysis process, allowing decision makers to take action on insights faster than before. Edge computing is a new network functionality that offers connected compute and storage resources right next to you Smart Data Smart Region | www.smartdata.how
  25. 25. High Salaries For IT workers, the increase in big data analytics will likely mean high demand and high salaries for those with big data skills. According to IDC, "In the U.S. alone there will be 181,000 deep analytics roles in 2018 and five times that many positions requiring related skills in data management and interpretation.„ As a result of that scarcity, Robert Half Technology predicts that average compensation for data scientists will increase 6.5 percent in 2017 and range from $116,000 to $163,500. Similarly, big data engineers should see pay increases of 5.8 percent with salaries ranging from $135,000 to $196,000 for next year. Smart Data Smart Region | www.smartdata.how
  26. 26. Self-Service As the cost of hiring big experts rises, many organizations are likely to be looking for tools that allow regular business professionals to meet their own big data analytics needs. IDC has previously predicted "Visual data discovery tools will be growing 2.5 times faster than rest of the business intelligence (BI) market. By 2018, investing in this enabler of end-user self service will become a requirement for all enterprises." Several vendors have already launched big data analytics tools with "self-service" capabilities, and experts expect that trend to continue into 2017 and beyond. IT is likely to become less involved in the process as big data analytics becomes more integrated into the ways that people in all parts of the business do their jobs. Smart Data Smart Region | www.smartdata.how
  27. 27. OPPORTUNITIES Smart Data Smart Region | www.smartdata.how
  28. 28. WHY IS BIG DATA A BIG OPPORTUNITY? Smart Data Smart Region | www.smartdata.how
  29. 29. 10% Can lead to large returns For the median Fortune 1000 company, a 10% increase in usability of and accessibility to data means significant boosts in productivity and sales Smart Data Smart Region | www.smartdata.how Complete Exercise 2 of Learners workbook #6 to find out more about the future of data-driven technology
  30. 30. What does that mean for specific industries? RETAIL 49% CONSULTING 39% AIR TRANSPORTATION 21% CONSTRUCTION 20% FOOD PRODUCTS 20% STEEL 20% AUTOMOBILE 19% INDUSTRIAL INSTRUMENTS 18% PUBLISHING 18% TELECOMMUNICATIONS 18% RETAIL $1.2 bn CONSULTING $5.0 bn AIR TRANSPORTATION $3.4 bn CONSTRUCTION $2.0 bn FOOD PRODUCTS $3.4 bn STEEL $4.3 bn AUTOMOBILE $4.2 bn INDUSTRIAL INSTRUMENTS $0.8 bn PUBLISHING $0.4 bn TELECOMMUNICATIONS $9.6 bn Smart Data Smart Region | www.smartdata.how Productivity Increase Sales Increase
  31. 31. Smart Data Smart Region | www.smartdata.how HOW CAN YOU ACHIEVE THOSE NUMBERS? To be effective you must be able to discuss the industry-specific needs and pain points of business leaders. GOVERNMENT • Cut costs, improve efficiencies • Improve security, transparency, public participation and internal collaboration • Analyze and predict events related to security, reduce fraud TELECOMMUNICATIONS • Manage high volumes of customer data being driven by operational systems • Deliver value and services by having „single view“ of customer and their changing behavior • Optimize mobile data and network efficiency BANKING • Manage risk and detect fraud • Manage explosive growth in trade volumes and shrinking trade size • Increase customer focus for the business • Reduce data management costs INSURANCE • Improve processing speed of new applications • Reduce inconsistencies in the increased manual claims processing • Customize sales campaigns by improving claims segmentation RETAIL • Manage proliferation of text and numerical data including customer data and transaction information • Optimize marketing spend, increase ROI • Optimize inventory and supply chain MEDICAL • Consolidate data and data center • Automate patient records and vendor payments • Implement electronic health records • Innovate – study the human genome MANUFACTURING • Optimize supply chain • Synchronize data with suppliers for sources products and retailers for sales • Create centralized view of product and parts data for inventory control • Reduce production downtime UTILITIES • Forecast/plan shutdowns • Improve utilization of assets, reduce outages • Improve integration of energy management systems Can you think of advantages of Big Data in other industries? Complete Exercise 3 of Learners workbook #6
  32. 32. Smart Data Smart Region | www.smartdata.how SPECIALIZATION OPPORTUNITIES The database marketplace is defined by the following segments. STORAGE FOR DATA SERVERS FOR DATABASES BUSINESS INTELLIGENCE ADVANCED ANALYTICS DATA INTEGRATION TEXT ANALYTICS
  33. 33. CHALLENGES Smart Data Smart Region | www.smartdata.how
  34. 34. CHALLENGE 1: Figuring Out Your Big Data Use Cases CHALLENGE 2: Improving Your Agility to Get Answers Fast CHALLENGE 3: Building Strong Governance Around Your Big Data CHALLENGE 4: Progressing Along Your Big Data Journey CHALLENGE 5: What to Consider With Big Data Analytics Software?
  35. 35. www.smartdata.howwww.facebook.com/smartdatasr

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