Analysis Ladies And Gentlemen - 1124 Words

Ladies and gentlemen, it’s time to let our data out of database purgatory and allow it safe passage back home to the business. No more rigid, back and forth time-consuming requests to IT for â€Å"ad-hoc† reports and result sets. The first phase of the project defined and described our KPIs as well as the presentation of those KPIs on our new BI portal. These standard KPI dashboards allow â€Å"drive-by† views of how the organization is doing via real-time display of critical measures, as well as the ability to delve deeper into those metrics if desired. The second phase of the project liberates our data, making it available and leverageable to most personnel on demand using self-service analytics. Essentially, if you can visualize the data you†¦show more content†¦However, turning over the data analytics keys to business users is not necessarily a â€Å"turn-key† event. It will require a philosophical buy-in on the part of those users. Specifically, they will have to adopt a true do-it-yourself philosophy. While the next phase of the project will provide a tool that makes dashboard creation and enhancement easier, it will also require business users to become better at â€Å"systems-thinking† and will require them to be closer to their own data. They will need to have better knowledge of their data than ever before. After all, the best aircraft in the world are useless without pilots and aircrew who know the airframe inside and out. Similarly, the best data analytics systems are useless without knowledgeable users to administer them and get the most out of them. The payoff for the organization is a business user that is many times more knowledgeable and effective than ever before because they know the organization’s data and how to leverage it. How does the organization inculcate a data culture, if not already there? If all business users had a foundation in SQL, then it might be much easier, but it’s unrealistic to expect all users to acquire those skills. However, it is realistic to expect all users to think logically about the data they need, in order to create the metrics they would like to see. Assuming the business knows