A few weeks back I told you I was changing the model for thinkJar, then I shared with you the agenda for customer service. This time, I am presenting you with the agenda for Data Usage in the Enterprise.
First, the question everyone asks – what is Data Usage in the Enterprise.
I came to this name because I am not very creative with TLA (three letter acronyms, if it has to be said) to be honest (or TBH – to stay on topic…). I cannot think of something like “Enterprise Data Usability – EDU” o “Enterprise Data What-To-Do-For-Value – EDW” or anything like that. I mean last two times I had to do TLA I ended up with EFM and CIH – neither one of them lighting the world on fire…
Reality has four facets:
- There is an ungodly amount of hype surrounding the use of data in the enterprise – from Big Data to Analytics and even ending up in AI these days. Everyone is calling it something different — yet…
- The need for data usage in the enterprise has not changed much over the past few years (I’d even say decades, but we have a different battle). What has changed dramatically is…
- The power and speed at which we can process, store and use data have grown dramatically. When Gartner was doing RTE (real-time enterprise — see, TLAs are not good) back in the early 2000s we lamented that the lack of processing power and speed was the killer for the RTE. However, in spite of this growth…
- Enterprises continue to have similar needs: create a data management model to make data-backed decisions efficiently.
And that is what Data Usage in the Enterprise is: a summary of a market that has many vendors aiming to help customers make sense of their data needs, and service those to create better decision solutions. Everything else is just plain hype.
I will focus my research on what I considered a semi-mature market (virtually all organizations have more than three “analytics” systems in place today) and cut through the many hype-tastic labels to give you a useful model of what you should be looking for, where, and why. I am working this year the following pieces (with due dates, which could change based on external factors):
- February 14 – State of the Market: Data Usage in the Enterprise
- March 21 – DU Market Drivers and Inhibitors
- April 25 – Latest and Greatest Lessons Learned: DU
- May 30 – DU Implementation: A Case Study
- September 5 – DU Implementation: A Case Study
I may also, from time to time, write something that is not on the agenda as it fits into the research (already got some ideas, but always welcome more)… How can you help (or how can I help you)?
If you have an interesting case study, if you are willing to be interviewed for a “lessons learned” interview, if you have some wisdom or insight you’d like to contribute, if you would like to discuss the market — or if you are looking to sponsor the research (wink-wink) simply contact me. You can also leave a comment below if you prefer.
(part three of this five-part research agenda publishing is coming soon and will display the same information for the topic of Artifical Intelligence in the Enterprise)
disclaimer: no disclaimers at this time, sorry – writing templates and prepping to cover 5 research topics has taken all the humor away… sigh.
(Cross-posted @ thinkJar)