Big data, or the use of extremely large data sets, is currently big business. Not only that, it is growing at almost inconceivable levels. Big data's large data-sets are used to analyse patterns on a grand scale in a wide variety of settings, including national security, research, medicine and consumer analysis. These data-sets are of such vast and growing sizes that those seeking to control and use them face problems such as speed, quality and the development of meaningful results.
There are some that predict that, because of these issues, big data's day's are numbered, but we disagree. Suggestions for replacement include fast data (the application of similar analytic techniques in real-time to smaller sets of data) and cognitive technologies (artificial intelligence products such as natural language processing and machine learning). We predict that these massive data-sets and hyper-productive data collection techniques will be around for some time yet. Here are our 7 predictions for the future of big data.
1. The volume of data will continue to increase
With the rapid global increase in the number of connected devices, data will become more and more readily available. Increased data generation is inevitable. The corresponding challenges of storage and manipulation will need to be met.
2. Data protection initiatives such as the European GDPR will present challenges
Data protection is currently big news in Europe and for those dealing with European businesses. The GDPR which replaces the Data Protection Act in May 2018 will place greater burden on data holders to ensure privacy and enable reporting of data handling.
3. There will be a rise in requirements for expert data officers
With the stakes for data compliance being so high, more companies will opt to employ an expert to manage their data protection systems. For companies with over 250 employees or 5000 data sources this will be compulsory.
4. Companies that hold data will make more moves towards monetising it
Organisations with under-developed data analysis capabilities are realising that their data-sets have a financial value to others. Mergers, such as IBM's acquisition of The Weather Channel to provide a forecasting model for their localised weather prediction, Deep Thunder, will become more common.
5. New analysis tools will emanate
As the demand for analysis increases the traditional coder-analyst model will be supplemented by non-coder app creation designed to suit individual businesses.
6. Cognitive technologies and big data will become common bed-fellows
Data-sets of increasing enormity will require cognitive technologies such as machine learning for successful data preparation and predictive analysis.
7. Real-time or near real-time requirements will increase
Expectations will move away from volume towards speed. Analysis will be expected in as near to real-time as possible. This may prompt a move away from big data and towards fast data.
Big data is not going to stop increasing and it will be interesting to see which of our predictions comes to fruition. One thing is for sure, companies who ignore the importance of their data-sets for business analytics and prediction do so at their peril. Big data is here to stay and definitely the one for the savvy organisations to watch.
Posted by:
CloudScope Recruitment