In my ever evolving goal to identify, investigate and report on the current status of Enterprise Class Information Technology (IT), I have recently begun to dive into the “new world” of Enterprise Data Supply Chain Management.
With the accelerating proliferation of Big Data and the associated enterprise demands for better and more real time “Business Intelligence” from this data, IT is faced with ensuring the integrity of the “Data Supply Chain”. Fulfilling this requirement would be easy if all of the data was magically located on a single server in a common format. However, in today’s distributed, virtual, cloud based, SaaS Based, BYOD, mobile computing environments, enterprise data is scattered all over the globe. Identifying, extracting, processing, analyzing and creating actionable items can be daunting if the required data is stored in 10 different unrelated servers, needs to be processed through 3 different apps, analyzed by 2 different BI engines and provided to operations managers in a form that is easy to understand and act on.
Leveraging enormous, real-time amounts of marketing data to provide more efficient product manufacturing or retail delivery choices is a trending example of the potential value of Enterprise Supply Chain Management.
In an article by H.O. Maycotte titled, “The Big Data Supply Chain Is Hungry, And You Need To Feed It,” published March 18, 2015 on Forbes.com, Maycotte states, “There’s been a lot of focus and innovation on the front and back ends of the data supply chain. Storage, which was once considered a prohibiting factor has largely been solved thanks to solutions such as Amazon AWS. On the other end, there are hundreds if not thousands of companies creating algorithms and cognitive computing solutions that are focused on BI and AI leveraging big data to drive marketing. What is still missing for a complete marketing solution is the link between the stored data and the applications that automate and take action. I believe this is something CMOs and CIOs need and want to control so they are free to try new vendors without the risk of losing the direct connection to all the customer data they work so hard to generate.”
However, any IT processes that involve the analysis of Big Data is more than likely going to require some type of Enterprise Data / Big Data Supply Chain Management. And, supporting Enterprise Data Supply Chain Management in today’s distributed IT environments is going to require the extensive use of common / universal agents that can be controlled from a single workflow platform with the ability to move the required data along the “data supply chain”.
Over the coming weeks and months I will be investigating the details of what Enterprise Supply Chain Management is all about, which vendors are leading the charge and which technologies seem to be working.
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