“Data Governance is too expensive and highly complex which might not give us a good ROI, so we should probably wait a few more years.

Hold that thought immediately because no! If you weigh returns in saved time and mitigated risks, it is not expensive! It is only complex if planned with a framework unsuitable for your business model. Lastly, no, definitely don’t wait! Do your company’s future a favour and start now because you might be willing to wait for your decision on DG but your Data will definitely not. It will keep on growing and become more complex whilst also becoming more valuable.

But why should you bother?

Digital Transformation is on everyone’s agenda and data is that core asset which will allow you to achieve your Digital Transformation goals. This makes it crucial to deploy a data governance framework that will also suit your business objectives. It is more of a strategic tool that ensures that your organizational data assets are managed in the right manner, and also create policies and roles in the organization to ensure those policies are implemented. In short it means higher data quality standard, better analytics, accurate business decisions!

Is it relevant for Small Businesses?

As mentioned before, data is growing for everyone. Even for smaller businesses data will continue to grow and be more complex but valuable, and that makes it more exposed to risks due to privacy, security and compliance. However smaller businesses are more agile in implementing new methodologies and would face less integration challenges that huge organizations would normally face.

Implementation seems too complex, so how do you achieve it?

The scope of a complete Data Governance project is indeed huge and cannot be implemented right away across all data so the best practise is to take small steps by identifying main KPIs and the critical data assets required. For example if you are the Owner of a manufacturing plant and wish to include Carbon Emission as your KPI. Of all the data available in the company the data related to this KPI (Data from Energy, Production shop, Chemical Incineration) becomes your Critical Data Assets.

Remind you that the context here is not operational i.e. to reduce your Carbon Emission, but to ensure that the data collected every day for this KPI is accurate, consistent, complete and as per the defined policies.

Okay. So what does the framework do?

An effective DG framework includes the following pillars as the scope. But the most important ones are Meta Data Management, Data Quality and Data Ownership. The others can be achieved separately under the scope of Data Management.

Metadata is the data of your data. It should include the details about the flow of every data as per Business definition (Business Lineage) and also actual flow in the enterprise level (Data Lineage). It also serves an important function of having Business Glossary and Data Dictionary.

Let us assume an Auditor wants to check the correctness of the PBT of your Finance report. First she would have to access the Business Glossary in Finance cluster and find PBT and what it stands for (here Profit Before Tax). She then can access the definition and also see the actual flow of that PBT value (how it was calculated, aggregated and transformed) throughout the organization. Transparent and all in one view!

Data Ownership includes roles and responsibilities assigned to the people in the organization, who will be accountable for the set principles for the data cluster assigned to them. Let us say a Finance data owner is given a Power BI report which has their New Business Volume as KPI and it needs his approval. He has to approve the Business lineage for all the data. To reduce it to one data point let us consider PBT again. The data owner will only approve a Power BI report if there is a traceability of this PBT to the very first level as per the Business Lineage.

Similarly, Data Quality framework also sets KPIs based on the defined terms. If there the quality KPI alarm is set off, the Owner can quickly view the related metadata information and find the person responsible (Data Stewards) and contact them.

Overwhelming right? But this method of accountability ensures the correctness and standards. It may seem like a time exhaustive tasks at first but if you consider the time wasted in finding an issue without a proper governance, you tend to comprehend the benefits it brings.

Is Tool selection or Budget your concern?

There are DG tools available but with high Operational costs. But the introduction of cloud solutions and integration with services can reduce the operational costs by significant levels. Also you do not do DG over everything but rather focus first only on those assets which are of critical value. A good DG solution must gather metadata from different sources, manage a Data Dictionary and Organization’s business glossaries, enforce procedures and policies.
Microsoft’s ‘Azure Purview’ is one such tool that can provide seamless integration across many data sources. One can quickly find a data asset through the Purview catalogue and go through the definitions, glossary, the hierarchy of that particular data throughout the system and additional details of the person responsible for those data assets, all under one single view. In addition it also identifies sensitivity labels which help the Data Owners to have a quick glance at the location of their sensitive data (like Credit card information) and take actions accordingly. An effective Data Governance tool should ensure highest Data Quality through reduced effort and time taken, to scan across data assets or in creating lineage. Purview lets you can scan your Power BI workspaces and auto generate list of data assets and their data lineage. Your KPI data assets can be automatically listed and published in the Purview catalogue.

Are you still hesitant to implement your Data Governance Strategy?

We can help you achieve them based upon on your Business Models & Objectives. Our employees are experts in Business Intelligence, Data Analytics, Data Warehousing, Machine Learning, Production Management, Finance and Controlling. If you need support in the implementation of your Data Strategy, please contact us at any time!

Linus Trips HUBSTER.S

Tushar Poojary

Tushar Poojary​ ist Solution Architect bei den HUBSTER.S