Is the future of analytics within your enterprise architecture a rapidly changing agile innovation platform (Lab), separated from operations and broad enterprise audience usage, alongside a consistently slowly changing enterprise analytics platform (factory) that supports operations and a broad enterprise audience? That is the question this blog digs into?
This is an important IT topic at the moment as working out how innovate and modernize at the same time is one of the biggest challenges organizations are facing right now. In the past this has been like changing to new wings while flying the plane which has always been slow and risky.
All hail the data lake, destroyer of enterprise data warehouses and the solution to all our enterprise data access problems! Ok – well, maybe not. In part four of this series I want to talk about the confusion in the market I am seeing around the data lake phrase, including a look at how the term seems to be evolving within organizations based on my recent interactions.
Working out where Hadoop might fit alongside, or where it might replace components, of existing IT architectures is a question on the minds of every organization that is being drawn towards the promises of Hadoop. That is the main focus of this blog along with discussions of some of the reasons they are drawn towards Hadoop.
For the past 12 months, I have spent a great deal of time speaking to organizations that were either thinking about adopting Hadoop as a data platform or were already well underway with their Hadoop journey. During this time, I have heard two core arguments as to why people want to adopt Hadoop: cost and agility. Perhaps unsurprisingly if you talk to those that have implemented, they often tout the same two things as the benefits of having adopted Hadoop. Lets dig into both.
