How Do You Make Sense Of Your Unstructured Data?
Many of us have spent the past 10 years focusing on business intelligence solutions in order to help our businesses make better fact-based decisions. In fact, BI has been among CIOs’ top 10 priorities for more than a decade. These solutions have, for the most part, been successful — and we continue to improve our BI capabilities as the demand for fact-based decision-making goes deeper, wider, and further into the business.
This whole time, we’ve also been aware of the significant amount of unstructured data that resides within our business, and the fact that we struggle to use it to make better decisions. To begin to get value from this data, we have made our organizations more collaborative and implemented tools and platforms to support that collaboration — with varying degrees of success.
The fact remains that there’s a huge amount of unstructured information and data that we do not get value from. However, a growing number of solutions are beginning to mine elements of this data: product information, software code, legal case files, medical literature, messaging data, and other unstructured business data.
I’ve recently been working with TrustSphere, which is a messaging intelligence provider. TrustSphere has an interesting solution that mines your messaging data to get real insights and information from the mountains of emails and messages that bounce into, out of, and around your organization every day. This is an interesting concept, and TrustSphere has developed a number of use cases for its solution. I’ll be presenting at a webinar hosted by TrustSphere on February 25— feel free to register here.
I’m sure that companies like TrustSphere will see success in the short term, as companies look for solutions to their specific business problems — but how will this play out in the longer term? Do we all implement five, 10, 20, or 50 different point solutions for specific business problems only to find out in five years’ time that not only have we created an integration nightmare, and we still can’t get value across the different unstructured data stovepipes (as was the case with traditional BI before we consolidated onto a single platform)? Does a single platform exist today that could manage much or all of our unstructured data — or at least take feeds from the different point solutions? I don’t know the answer to that question, but would be interested in your thoughts. Will IBM Watson be this platform? Will it be a competitor’s solution? Or will it be something else entirely?
If we know where we will be in five years’ time, we’ll know what mistakes to avoid in getting there — so I’m interested in your thoughts of what this journey will look like. Please leave your comments below, or tweet me at @timbo2002 — I look forward to the conversation!