Challenges to Big Data

Bigdatachallenges

Big Data adoption has been slow. There are a number of reasons ranging from the fact that analysis of the data can be difficult, to just getting all of the data normalized can be hard. GE did a study of the top challenges facing the implementation of Big Data and the below chart is the result.

While some of these issues are not technology as much as they are legal and user issues, such as the #1 concern of security, consolidation of disparate data, collection, and quality issues are all things that Recognant addresses. The talent requirements to interface with the data is also addressed by NLP. All in all, 6 of the top 10 issues from above are addressed by Recognant and for 54% of respondees their #1 issue is addressed by Recognant. That is a powerful step in reaching the promise of Big Data. Thus far the barrier to using NLP has been the cost and speed issues.

Big Data has has the most impact in industries with lots of structured data, and with smaller volumes of data. Real Estate, Supply Chains, and Procurement where data is straightforward and easily obtained has seen lots of growth in the use of Big Data. Sales, Finance, and Production are seeing products that leverage Big Data. These are areas of great opportunity, but likely the greatest potential markets and where the least impact has been realized so far is in Customer Service, Marketing, and BizDev. These areas haven’t had the the growth because the metrics are softer, and the data gathering is harder. Knowing what makes a good customer is often contained in the words on their website rather than in a column on a spreadsheet. A company that works in Cosmetics could sell, manufacture, or apply them and telling the difference from data is not easy. Trying to sell a product to a company that isn’t a fit, or is a competitor is a waste of both companies’ time.