Integration is central to digital transformation and growth. However, with the wealth of data used by organizations today, it’s important that any data project keep data governance practices in mind.
In cloud and hybrid environments particularly, data governance standards are crucial for supporting risk management efforts, compliance regulation, data discovery, and the ultimate control and visibility of data across the enterprise.
Data governance is a multi-level, multi-departmental effort. It’s defined by how data is ingested into systems, how data is retained and stored throughout systems, how it’s shared, how it’s archived and backed-up, recovered, and deleted. Data integration ingests and shares data between solutions and is therefore important to the overall data governance strategy of any business.
So, how can we maintain data governance during integration? Here are a few factors to consider:
Stick to a formal process.
Integrations bring together a company’s technical and functional stakeholders to make decisions about the project. To maintain data governance throughout, there must be a formal process of approvals and communications between these parties. Integration specifications that document the purpose of the integration as well as data mappings and code values should be documented in the data governance knowledgebase. This allows that documentation to be referred to for future projects and keeps the information accessible to everyone involved in the project.
Make sure your data model and naming standards are being followed.
If you already have data governance policies in place, you should have documentation that defines naming standards for your data. Part of preparing for integration involves cleaning and organizing data, so you should be referencing back to those standards as you undergo that preparation. If you organization doesn’t have a formal data governance strategy implemented, use the integration as an opportunity to define those naming conventions and the type of data model your company is following, or should be following going forward.
Create a data flow diagram.
A data flow diagram is a visual representation of the flow of data in a business system (or in the case of integration, between business systems). There are logical data flow diagrams and physical data flow diagrams.
A logical data flow diagram focuses on what happens with that data at a less technical business level. It’s how the data is moving through processes to complete a business function. The physical data flow diagram focuses on the data flow at the system level. It details how the hardware, software, files, and people are involved in the data flow. If you’re working with an integration consultant, they will likely provide this information or help you personalize the data flows based on your integration goals.
Ensure data flow information is stored with your other data governance documentation on the project. If your internal team is handling the integration, request that they create data flows as part of the formal integration governance process.
Build in monitoring and performance management.
After the integration is up and running, it’s easy to forget about the data governance standards it should maintain. The ongoing monitoring of the integration’s performance is especially crucial if you have data moving between your solutions in real-time. To maintain the integrity of the integration and keep data governance standards in-check, make sure IT managers have the tools they need to visualize and report on the integration processes.
Data governance during an integration project has multiple benefits. It improves the communication around the project and results in better documentation of both business and technical insights that can be called upon for future projects.
Integration stakeholders often represent many of the same individuals who play a role in the organization’s data governance strategy. Bringing the governance mindset into the data integration strengthens these stakeholders’ relationship to the policies and advances the goals of data governance across the organization. StarfishETL offers services around data governance. You can find out more information on those services and request a free consultation, here.