
Almost everyone can agree that big data has taken the business world by storm, but what’s next? Will data continue to grow? What technologies will develop around it? Or will big data become a relic as quickly as the next trend — cognitive technology? fast data? — appears on the horizon.
Let’s 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’s 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.
- Ways to analyse data will improve. While SQL is still the standard, Spark is emerging as a complementary tool for analysis and will continue to grow, according to Ovum.
- More tools for analysis (without the analyst) will emerge. Microsoft MSFT +0.22% andSalesforce both recently announced features to let non-coders create apps to view business data.
- Prescriptive analytics will be built in to business analytics software. IDC predicts that half of all business analytics software will include the intelligence where it’s needed by 2020.
- In addition, real-time streaming insights into data will be the hallmarks of data winners going forward, according to Forrester. Users will want to be able to use data to make decisions in real time with programs like Kafka and Spark.
- Machine learning is a top strategic trend for 2016, according to Gartner. And Ovumpredicts that machine learning will be a necessary element for data preparation and predictive analysis in businesses moving forward.
- Big data will face huge challenges around privacy, especially with the new privacy regulation by the European Union. Companies will be forced to address the ‘elephant in the room’ around their privacy controls and procedures. Gartner predicts that by 2018, 50% of business ethics violations will be related to data.
- More companies will appoint a chief data officer. Forrester believes the CDO will see a rise in prominence — in the short term. But certain types of businesses and even generational differences will see less need for them in the future.
- “Autonomous agents and things” will continue to be a huge trend, according toGartner, including robots, autonomous vehicles, virtual personal assistants, and smart advisers.
- Big data staffing shortages will expand from analysts and scientists to include architects and experts in data management according to IDC.
- But the big data talent crunch may ease as companies employ new tactics. The International Institute for Analytics predicts that companies will use recruiting and internal training to get their personnel problems solved.
- The data-as-a-service business model is on the horizon. Forrester suggests that afterIBM IBM +0.30%’s acquisition of The Weather Channel, more businesses will attempt to monetize their data.
- Algorithm markets will also emerge. Forrester 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.
- Cognitive technology will be the new buzzword. 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.
- “All companies are data businesses now,” according to Forrester. More companies will attempt to drive value and revenue from their data.
- Businesses using data will see $430 billion in productivity benefits over their competition not using data by 2020, according to International Institute for Analytics.
- “Fast data” and “actionable data” will replace big data, according to some experts. The argument is that big isn’t necessarily better when it comes to data, and that businesses don’t 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 — big or otherwise
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.
This article was originally published forbes.com and can be viewed in full here


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)