In previous CIO.com articles, we talked about three of the five capabilities needed to turn data into insight. The fourth key capability is to have “data-centric processes.” What we mean by this is twofold: There are processes embedded into the organization that are focused on data and data management and optimization. There is a recognition that data is an input and a valuable output of other processes in the organization, and these inputs and outputs are understood and retained to extend data understanding in the organization.
Welcome back to our CIO.com series on managing the data landscape and making sure you get the most value out of your data. In our first article in the series, 5 Critical Success Factors to Turn Data Into Insight, and the ones that follow it, we seek to define these five capabilities that play key roles in the success and…
Our first two articles in this series introduced the essential capabilities that contribute to the success of analytics-based initiatives: business alignment (determining context and value); data understanding (seeking to better understand data assets and manage accordingly); data quality (defining accuracy for data’s use); data-centric processes (increasing understanding as new data is created, used, managed and measured); and data-centric resources (embedding data-oriented knowledge and skills).
Our recent article written by our CEO Kelle O’Neal, “5 Critical Success Factors to Turn Data Into Insight,” indicated there should be concern around the not-so-successful outcomes of many analytics and big data projects. In her article, Kelle also covered five capabilities that contribute to the success of analytics-based initiatives: business alignment; data understanding; data quality; data-centric processes; and data-centric resources.
A quick Google search on the term “Analytics” yields varying definitions. Oxford Dictionaries defines it as “the systematic computational analysis of data or statistics” or the “information resulting from the systematic analysis of data or statistics.” Here are five actionable tips and best practices to ensure your organization’s process for turning data into insight is effective, efficient and repeatable.