Big Data Trends to Watch for 2017

Monday, December 12, 2016

Big data has become the cornerstone of the modern business world. Just like money, it needs to be carefully utilized and not placed into the wrong hands. Throughout 2016, more businesses of all sizes have been making use of big data to make more informed business decisions and provide better products and services to their customers.
Here’s what many experts think is going to come to the wide world of big data come 2017.

Big Data Analysis is Going to Become More Friendly to Non-Techies.

Business and technology experts have been saying for the past five years that learning to code is becoming a must for people in just about every role, even if it’s not IT. But if programming and analyzing data isn’t your strong suit, there’s more front-end tools being created to extrapolate and analyze data so that you don’t need to be a C++ expert to figure it out. Both Microsoft and Salesforce have also announced that in 2017, there will be ways for users to create apps that let them analyze data without needing any coding knowledge1.

Chief Data Officers Are Having a Moment in the Sun

The CDO is already starting to rise up and become an integral part of the C-suite as more and more firms are relying on the collection and analysis of data. There may be less need for CDOs in the future, but as big data changes the landscape the CDO is needed to take the strain off CTOs and CIOs.

Data Analysis Will Become More Sophisticated

SQL is the order of the day but Spark could oust it as the chief analyst as it continues to experience rapid growth.

Data Volume Will Not Stop Growing

It isn’t called big data for nothing. With billions of internet-connected devices and growing, people will continue to generate more data than ever before.

Machine Learning Will Become More Necessary than Ever

Machine learning is going to be more necessary for preparing data than before, as well as in automating processes and predictive analysis.

Real-Time Insights are the Hot New Thing and Only Getting Hotter

Kafka and Spark have made it possible to have real-time streaming insights into big data. Decisions based on data can be made in real time using these programs, and we can expect to see more of this in 2017.

Data-As-A-Service Will Slowly Become a Common Business Model

Companies monetizing their data is nothing new. However, the large scale in which it is happening will cause many larger companies to adopt a data-as-a-service (DaaS) model. This trend is expected to explode in 2017 following IBM’s acquisition of the Weather Channel. Companies are deriving both their revenue and residual value from the data they hold: not just their intellectual property.

Privacy Concerns Are On the Rise and Will Continue to be Throughout 2017

In the tense political climate in the US where talks of bringing back the SOPA/PIPA bill have rattled the infosec community, the UK and European Union are facing more challenges on account of privacy regulations. More companies and individuals will want to keep their data safe from both hackers and the government. This is particularly true in the UK where surveillance laws were recently passed that many citizens and infosec professionals feel is a blatant violation of privacy.

Automation Will Abound

Driverless cars and trucks are already here, as is robotic process automation. “Autonomous agents and things” will start to include virtual personal assistants, customer service agents that can speak to customers in their native language, and much more.

The rise in robotics and automation will mean job loss. It also means that data collection, processing, and analysis will not run the risks of human errors and judgment (such as releasing the data to the wrong parties or holding it for ransom.) However, robotics and data-related staffing shortages are also to be expected for recruiters in 20172.

Algorithm Markets Are Emerging

Data Xu, Kaggle, Algorithmia, and other startups taking advantage of the interest in big data and analytics are selling algorithms. By making algorithms available for purchase, companies can save a great deal of time and money buying one then refining it instead of hiring data experts and coders to create an algorithm from scratch and having to populate it with their own data. Algorithm sellers can expect exponential growth in 2017.

Big Data Continues to Expand, and Will Likely Be Split Off Into “Fast Data” and “Actionable Data”

Time will tell as to what the case will be. But big data is going to keep getting bigger, and organizations that fail to adapt to this change and swiftly will get left behind.

Companies don’t always use all of the data that they collected and have access to. Rather, they will need to change their focus to the most relevant data for growth, sustainability, and increasing value.