{"id":2188,"date":"2016-04-03T22:15:35","date_gmt":"2016-04-04T01:15:35","guid":{"rendered":"http:\/\/roberval.com.br\/roberval\/?p=2188"},"modified":"2016-04-03T22:15:35","modified_gmt":"2016-04-04T01:15:35","slug":"17-predictions-about-the-future-of-big-data-everyone-should-read-bernard-marr-linkedin","status":"publish","type":"post","link":"https:\/\/roberval.com.br\/roberval\/2016\/04\/17-predictions-about-the-future-of-big-data-everyone-should-read-bernard-marr-linkedin\/","title":{"rendered":"17 Predictions About The Future Of Big Data Everyone Should Read | Bernard Marr | LinkedIn"},"content":{"rendered":"

\"\"<\/a>Almost everyone can agree that big data has taken the business world by storm, but what\u00e2\u20ac\u2122s next? \u00c2\u00a0Will data continue to grow? \u00c2\u00a0What technologies will develop around it? Or will big data become a relic as quickly as the next trend \u00e2\u20ac\u201d cognitive technology? fast data? \u00e2\u20ac\u201d appears on the horizon. \u00c2\u00a0Let\u00e2\u20ac\u2122s look at some of the predictions from the foremost experts in the field, and how likely they are to come to pass.Data volumes will continue to grow. There\u00e2\u20ac\u2122s absolutely no question that we will continue generating<\/p><\/blockquote>\n

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  1. Data volumes will continue to grow. <\/strong>There\u00e2\u20ac\u2122s absolutely no question that we will continue generating larger and larger volumes of data, especially considering that the number of handheld devices and Internet-connected devices is expected to grow exponentially.<\/li>\n
  2. Ways to analyse data will improve.<\/strong> While SQL is still the standard, Spark is emerging as a complementary tool for analysis and will continue to grow, according to Ovum<\/a>.<\/li>\n
  3. More tools for analysis (without the analyst) will emerge.<\/strong> Microsoft<\/a>and Salesforce<\/a> both recently announced features to let non-coders create apps to view business data.<\/li>\n
  4. Prescriptive analytics will be built in to business analytics software.<\/strong> IDC predicts<\/a> that half of all business analytics software will include the intelligence where it\u00e2\u20ac\u2122s needed by 2020.<\/li>\n
  5. In addition, real-time streaming insights into data will be the hallmarks of data winners<\/strong> going forward, according to Forrester<\/a>. Users will want to be able to use data to make decisions in real time with programs like Kafka and Spark.<\/li>\n
  6. Machine learning is a top strategic trend for 2016<\/strong>, according toGartner<\/a>. And Ovum<\/a> predicts that machine learning will be a necessary element for data preparation and predictive analysis in businesses moving forward.<\/li>\n
  7. Big data will face huge challenges around privacy,<\/strong> especially with the new privacy regulation by the European Union. Companies will be forced to address the \u00e2\u20ac\u02dcelephant in the room\u00e2\u20ac\u2122 around their privacy controls and procedures. Gartner<\/a> predicts that by 2018, 50% of business ethics violations will be related to data.<\/li>\n
  8. More companies will appoint a chief data officer.<\/strong> Forrester<\/a> believes the CDO will see a rise in prominence \u00e2\u20ac\u201d in the short term. But certain types of businesses and even generational differences will see less need for them in the future.<\/li>\n
  9. \u00e2\u20ac\u0153Autonomous agents and things\u00e2\u20ac\u009d will continue to be a huge trend<\/strong>, according to Gartner<\/a>, including robots, autonomous vehicles, virtual personal assistants, and smart advisers.<\/li>\n
  10. Big data staffing shortages will expand<\/strong> from analysts and scientists to include architects and experts in data management according to IDC<\/a>.<\/li>\n
  11. But the big data talent crunch may ease<\/strong> as companies employ new tactics. The International Institute for Analytics predicts<\/a> that companies will use recruiting and internal training to get their personnel problems solved.<\/li>\n
  12. The data-as-a-service business model is on the horizon.<\/strong> Forrester<\/a>suggests that after IBM\u00e2\u20ac\u2122s acquisition of The Weather Channel, more businesses will attempt to monetize their data.<\/li>\n
  13. Algorithm markets will also emerge.<\/strong> Forrester<\/a> surmises that businesses will quickly learn that they can purchase algorithms rather than program them and add their own data. Existing services like Algorithmia, Data Xu, and Kaggle can be expected to grow and multiply.<\/li>\n
  14. Cognitive technology will be the new buzzword.<\/strong> For many businesses, the link between cognitive computing and analytics will become synonymous in much the same way that businesses now see similarities between analytics and big data.<\/li>\n
  15. \u00e2\u20ac\u0153All companies are data businesses now<\/strong>,\u00e2\u20ac\u009d according to Forrester<\/a>. More companies will attempt to drive value and revenue from their data.<\/li>\n
  16. Businesses using data will see $430 billion in productivity benefits<\/strong>over their competition not using data by 2020, according to IIA<\/a>.<\/li>\n
  17. \u00e2\u20ac\u0153Fast data\u00e2\u20ac\u009d and \u00e2\u20ac\u0153actionable data\u00e2\u20ac\u009d will replace big data<\/strong>, according tosome experts<\/a>. The argument is that big isn\u00e2\u20ac\u2122t necessarily better when it comes to data, and that businesses don\u00e2\u20ac\u2122t use a fraction of the data they have access too. Instead, the idea suggests companies should focus on asking the right questions and making use of the data they have \u00e2\u20ac\u201d big or otherwise.<\/li>\n<\/ol>\n

    Only time will tell which of these predictions will come to pass and which will merely pass into obscurity. But the important takeaway, I believe, is that big data is only going to get bigger, and those companies that ignore it will be left further and further behind.<\/p>\n

    As always, let me know your thoughts on the topic, please share them in the comments below.<\/p>\n

    Thank you for reading my post.\u00c2\u00a0Here\u00c2\u00a0at LinkedIn<\/a>\u00c2\u00a0and at\u00c2\u00a0Forbes<\/a>\u00c2\u00a0I regularly write about management, technology and\u00c2\u00a0Big Data<\/a>. If you would like to read my future\u00c2\u00a0posts then please click ‘Follow<\/strong>‘ and feel free to also connect via\u00c2\u00a0Twitter<\/a>,\u00c2\u00a0Facebook<\/a>,\u00c2\u00a0Slideshare<\/a>,\u00c2\u00a0and\u00c2\u00a0The Advanced Performance Institute<\/a>.<\/p>\n

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