Welcome to our new three-part series on our predictions for Big Data, Information Lifecycle Management (ILM), and Enterprise Content Management (ECM). If you’re interested in the future of Big Data and want to hear what we predict will be big in 2016; you’ve come to the right place.
If you missed the first part of our series, check out our 2016 predictions for ILM here
1. 2016 is going to see solutions that automate certain data quality tasks. As the volume and velocity of data increases, common tasks, such as data preparation and data governance, will have to become automated.
2. There will be a shortage of individuals skilled in data science. Even as data science related education takes off, and universities have started offering courses on data science and data mining, there simply won’t be enough workers with these skills. Organizations will look externally for knowledge and experience in data science, and there will be a market for those who offer insights as a service and data science as a service.
3. Customers will no longer be fazed by the big data hype. They will begin asking hard questions about how big data solutions will make a difference to their bottom lines. Companies that can provide convincing answers to such questions will grow rapidly.
4. Big data will become “small”. The use of masses of data as an indicator of success will turn to the quality of the data being collected. This will mean that the variety for each company is likely to decrease, but the specific data that will be collected will become far more efficient, useful, and plentiful. As companies realize that most of what they collect isn’t being used and just taking up storage space, this will become more apparent and the use of this data will come under increased scrutiny.
5. The data from devices in the Internet of Things (IoT) will become one of the “killer apps” for the cloud and a driver of petabyte scale data explosion. For this reason, leading cloud and data will bring IoT services to life so the data can move seamlessly to their cloud-based analytics engines. Though these changes and trends may seem disparate, they’re all linked by the need to work with data quickly and conveniently.
6. 2016 will see an increased scrutiny on how data is dealt with and protected. This will also come at a time when many countries around at the world are looking at implementing new data protection and data access laws, meaning that the waters are going to become increasingly muddied. Companies will need to increase their security spending, improve database safety and prepare for changes in the way that hackers work. It is going to be a difficult year for data security, but it will build the foundation on which future stable and robust data security is created.
7. 2016 will be the year SAP teams begin sorting through the next step in earnest. With all eyes on the inevitable SAP migration to HANA and its effect of making big data and valuable insights available quickly and efficiently, 2016 is the year of big changes. Now that we finally have quick access to all these years of great SAP data and without affecting performance, how do we actually access and use it? 2016 will be the year SAP enterprise organizations go full speed ahead to research analytic tools, processes and methodology options for HANA and get ready for this brave new world of SAP data mining.
8. 2016 will see an explosion of Data Management Solutions that couple licensed software and open source software. Large enterprise CIOs will aggressively explore and ultimately mandate this from vendors to keep cost low while maximizing cutting edge innovation. Gone are the days of one size fits all, out of the box software. And customization will rule.
9. Every Fortune 500 will have a full time Chief Data Scientist. While the trend has been going in this direction for years, no board of directors will allow their company to allow that role not to exist.
10. BI reporting will revert to being a centralized activity handled by specialized groups. While many “do it yourself” SaaS packages are funded by VCs and promoted as the “answer”, the reality is much of the needed data is still in silos and requires data experts to extract and load into centralized systems before even basic BI reports can be deployed.
That’s what we have to look forward to with Big Data, according to Auritas. If you are interested in learning more about Big Data, ECM, or any related topics, check out our webinar series here.