In our last piece, we talked about accurate data matching at length, but it is as good as nothing in the absence of a proper data governance system. Why did I say so? Let’s take an example to explain that to you. In 2022, Equifax, a major credit rating agency, underwent a major embarrassment when a coding error gave millions of customers faulty credit scores. What would it result in? Disbursing loans to individuals who wouldn’t be in a situation where they would have to pay it later. How could one deal with this problem? Through data governance.
What is Data Governance?
Data governance is a process where you define a framework to ensure that data keeping is done in a standardized manner to improve organizational efficiency. In this model, you will consider data quality, privacy, management, compliance risk management and more.
How To Use Data Governance To Improve Data Quality?
1. Setting up A process to Analyze and Communicate Data
The approach shouldn’t be forwarding data like machines with no brains. On the contrary, there should be a mechanism to perform data assessment in transit so that data emanating from anywhere can be first analyzed and then forwarded for computation and necessary actions.
2. Setting Up Accountability
There should be accountability in place, and that can only happen when you have a data governance model. The data governance model will break the responsibilities based on the need to ensure that data flows in a measurable and accountable manner.
3. Setting up Quality Control
A good data governance model will also instill a quality control mechanism in operations. Due to this, it will be possible to perform data profiling and cleansing, as well as identify, remediate, and prevent data errors.
4. Setting up a Final Reporting and monitoring system
After everything has been done, there’s the final touchdown, where the processed data will be tracked and reported vigilantly. In this initiative, the use of specific tools and software would ensure that there’s a proper problem-solving mechanism in place to eliminate the marginal errors in the data left after all the above-given processes to deliver the best quality for optimum results.
What Will Be The Impact of Setting Up a Good Data Governance System?
1. Better Data Quality
The quality of the data will improve dramatically. For example, imagine if the Equifax code went through different checking windows. If such an arrangement was there, it was very easy to avert such incidents from happening. That said, when you have a very strong data governance framework, all the data that is stored is consistent, qualitative and efficient.
2. Better Decision Making
Decisions are dependent on data, and if you have faulty data, you have faulty decisions. However, when you have a good data governance system, it is possible to keep well-managed, accurate, and trustworthy data, which will end up as the foundation for making better-informed decisions to improve the scope of growth and expansion.
3. Managing the Compliances
As you know, that data is oil, but the same oil can create fire if not kept well. For example, when you are collecting data from consumers, there has to be a specific way and standard. If you are found violating those standards, the outcomes are catastrophic.
For example, in the EU region, non-compliance of data comes at the following cost: According to the General Data Protection Regulation (GDPR), companies violating data privacy rules in Europe can face fines of up to €20 million, or 4% of their total worldwide annual turnover from the previous financial year, whichever is higher; with lesser violations potentially incurring fines of up to €10 million or 2% of annual turnover depending on the severity of the infraction. With an effective data governance system in place, you can easily dodge this bullet.
4. Better Operational Efficiency
Imagine having a data governance system where every department gets the most updated data about production, stock-keeping and more. In that case, it will enable better decision-making and improve organizational efficiency. For example, if the production unit is well informed of the consumption and the marketing unit can anticipate, based on their marketing efforts, how many new orders can be in place, it can keep everything in order and improve the organisation’s efficiency. However, if the data coming from the operations, marketing, production/manufacturing are different, it can create a lot of open spots to bring the organization down.
Conclusion
The future is data, and with that said, when you are collecting quadrillion of data without a proper governance system, you are simply collecting dust for no reason. However, when you have a robust compliance and governance system, as provided by Ve3, you can always stay ahead of the competition and achieve more with your data.
In the race to become data-driven, ensuring data quality is not optional—it is essential. Empower your organization with the right tools and strategies. Explore MatchX today and take the first step toward data-driven success. Contact us or Visit us for a closer look at how VE3’s solutions can drive your organization’s success. Let’s shape the future together.