Data alignment in an Analytical world

June 18, 2015

We all have heard the statement, “garbage in – garbage out.”  This is especially important when working with data and analytics, and extracting data as databases have become much easier to use.

When focusing on analytics and the use of system data, System Administrators must focus on today’s environment, and what the requirements are for tomorrow’s data. Although we don’t possess the proverbial crystal ball to predict tomorrow’s requirements, there are processes in place that can drive the decisions around what data should be captured.

These items include:

  1. How does our business model align with our data and talent management needs?
  2. Is the data sufficient to support the incorporation of other Talent modules?
  3. Have the department stakeholders been queried on reporting needs?
  4. Have you looked closely at what your present HR system is capturing as user requirements?

I was recently presented with a requirement to build a specific report utilizing the analytics engine of the client’s Talent Management software. The software had all the required data needed to produce the report, and I had to go to the client and tell them: “unfortunately your data does not support your requirements or needs”.

Should this happen to you, you will need to move back to the designing board to take a long hard look at your data, and evaluate what needs to occur in order to properly maintain reporting requirements. This can be tough, but is sometimes necessary to adhere to compliance and reporting standards which have evolved to become best practice.

Now that we have discussed the importance of data alignment in today’s analytical world, let’s make sure that working and outlining a plan to make this happen is part of the movement towards aligning with your reporting requirements. The use of the new analytical tools makes it so much easier to become very efficient at database table configurations and data possibilities. Be sure to take the time to familiarize yourself with your analytical tools data sets, what component object these access, and ensure the data is populated in areas that can be utilized for reporting purposes. This will give you the tools necessary to become efficient at pulling the required data and building dynamic reports.