Data analytics governance is the insurance in digital analytics. It is the key to make meaningful decisions and grow your business is maintaining reliable and trustworthy data.
It’s extremely important to have a quality control mechanism that helps validate the consistency and reliability of digital analytics data. Hence, it is critical to invest time and resources for setting up a comprehensive data governance strategy.
Benefits of Data Governance
No strategy or campaign can start without planning. Go to whiteboard and jot down all the objectives, resources, cost, market, and other relevant factors that would fuel the digital campaign going forward. Plan how the data would be used and ask yourself these questions.
7 important rules that define data governance
Let us elaborate the above rules :
Analytics data can be collected in numerous ways but documentation on data collection needs to be in place for any future reference/amendments.
These are the few things we should document when it comes to data collection:
Good quality data assists in better decision-making.
Once digital analytics tracking is implemented on the site, next step would be who all need to have access to the tools and data being collected (this includes the data analytics team, marketing team, agencies, IT team, contractors and so on). Need and Role based data accessibility needs to be defined across organization.
When we talk about data accessibility and data security, they are very closely related but data security is not only about restricting access of tools to people but protecting organization’s data warehouse.
If the organization works on collection of user/customer data then the big responsibility of the organization is to safeguard the privacy of data.
Data integrity refers to the accuracy and consistency (validity) of data over its lifecycle. Compromised data is of little use to enterprises, not to mention the dangers presented by sensitive data loss. For this reason, maintaining data integrity is a core focus when it comes to data governance.
Data presentation refers to how you are presenting the data being collected to the stakeholders. The end goal is that the metrics & insights what you derive from the data collected need to be presented to the stakeholders in appropriate manner.