All in Strategic Planning
Creating a data program governance strategy is not unlike creating other types of enterprise business strategies.
Whatever the environment, new data management and analysis technology may be important, but success and sustainability will also be driven by how we manage it and by how successful we are in putting data users and their priorities into the driver’s seat.
If you’re doing exploratory data analysis to help you decide how much data prep might be needed to make your data public, that’s one thing.
A slide deck summarizing where I am on researching Big Data Project Management.
I began researching “big data project management” when I started seeing publications and online discussions concerning big data project “failures” being attributed to the classic reasons for project failure such as scope creep, poor stakeholder engagement, and inadequately understood requirements.
“If data analysis is Big Data’s “tip of the spear” when it comes to delivering data-dependent value to customers or clients, we also must address how that spear is shaped, sharpened, aimed, and thrown – and, of course, whether or not it hits its intended target. We also want the processes associated with throwing that spear to be both effective and efficient.”
If what Nate Silver said in a recent presentation is true – “Big Data has Peaked, and that’s a Good Thing” – perceptions about big data are maturing.
After this week’s call with Socrata’s Health Data Publishers Roundtable about working with data owners I put together a few thoughts to share with the group. Here are some observations along with a list of questions that I think deserve further discussion.
Each data element in a data asset inventory has its own “lifecycle” that when properly managed provides a framework for tracking and optimizing how data are used from creation through obsolescence.