Informatica Data Quality

In my previous posts, I have discussed building the business case for data quality as well as the role that a data quality dashboard plays in supporting this case. As previously noted, these efforts will directly impact your ability to articulate the need to pursue a data quality initiative. The reason for returning to this topic is that I have recently participated in multiple discussions with a variety of companies that were either in the process of forming a data governance council or in the process of building the internal business case to support exploring a data governance initiative. In these discussions two common threads were present – the role of data quality in the data governance initiative and the need to change the culture within the organization if data governance is going to succeed. Although these are only two aspects to consider when pursuing a data governance initiative, they are directly tied to the underlying success or failure of the program.As it pertains to data quality, the key point I often discuss in these meetings is that without a firm understanding of the types of issues in the underlying data and an action plan to remediate these issues, the governance program will ultimately be flawed. The reason is that any decisions made based upon the data assumes it is correct and that a single version of the truth exists within an organization. The concept of governance is to drive to this common version of the truth where data definitions and processes are standardized at the enterprise level. In each of these scenarios, data quality serves a key role, as it allows an organization to monitor and then remediate issues as they arise. By leveraging data quality software and processes on an ongoing basis, the organization is able to monitor and address data quality on an iterative basis. In a sense, you can consider the data quality scorecard a report on the overall health of your organization’s data. If data issues are not addressed, the data related processes or definitions are likely to have issues as well, which compromises the intent of a data governance initiative.

Although data quality plays an important role in any data governance initiative, another key aspect that should be addressed is the cultural impact within an organization. Although processes can be put in place and data quality software can be licensed and implemented, the ultimate success or failure of the initiative will be determined by the acceptance (or lack thereof) within your organization. To that point, data governance needs executive sponsorship within an organization and should be initiated via a top down approach. Without this executive sponsorship and the willingness to make data governance a strategic initiative to the organization, the program is unlikely to gain the traction needed. The reason is often cultural, as people find it easier to continue to do business as usual. To address this, I often request that the various key stakeholders from across an organization are present when we conduct a data governance workshop, as I want to observe how everyone interacts as well as listen to any concerns, criticisms or objections that might be present, as these are the very issues that must be addressed if a governance program is to succeed.

Just as the title of this blog states, “Rome Wasn’t Built in a Day and Neither is a Data Governance Initiative” - as your organization begins to consider a data governance initiative this is something you should remain cognizant of, as the time to initiate a governance program is going to vary based on the types of issues noted in this post. If you do not have executive buy-in and if significant resistance to governance exists, the time to implement a program is going to be longer, as there is going to be a need for educational workshops to address concerns. If you have this sponsorship in place, you should begin to examine the quality of the data that the processes, policies and standards will be built upon.

Until next time….