Data governance: Definition
In the race for digital transformation that we have seen in recent years, enterprises are looking to become “data-driven”.
The influx of information and the massive amount of stored data are leading companies to initiate data governance and to consider it as a strategic area of focus.
We like to define data governance as an exercise of authority with decision-making powers (planning, surveillance, and rule enforcement) as well as having control over data management. Its main objective is to transform data assets into a set of shared and shareable assets in the enterprise.
Towards a new data governance
In the past, implementing data governance within organizations were rarely successful. Zeenea’s aim is to pragmatically shed some light on data governance attributes that are capable of taking on this new era’s challenges, and this, with the help of our data catalog.
We want it to be a bottom-up, non-invasive, automated, collaborative, and iterative data governance. In one word, agile.
“Data governance must be as close as possible to your enterprise’s operational reality.”
A bottom-up data governance strategy encourages putting individuals and their interactions in front of processes and tools. A data governance approach can only be successful by involving all the employees of an organization, thus benefiting from collective intelligence.
“Data governance must adapt to your enterprise’s context and not the other way around.”
Data governance must not be an obstacle to innovation in your enterprise. It is a matter of giving your collaborators freedom to use the tools adapted to their usages.
“Data governance must accurately reflect your data assets.”
Automating metadata collection on your data assets allows your tools to accurately reflect reality. This automation ensures that such governance is kept up-to-date and it can scale up.
“Data governance must involve and federate all employees of an enterprise.”
The practice of having one person or group arbitrate data governance has fallen into disuse. We believe that sustaining data governance is done by creating communities around various data-related domains within your organization.
“Data governance must deal with changes quickly.”
To best match your company’s expectations and operations, data governance must be built step-by-step. Adapting to change must be at the heart of the company’s data governance strategy.
In this second edition, we decided to tackle the organization of this new, agile data governance and its scaling process using this same mindset.
Learn more about data governance
Before implementing a data governance strategy, it is essential for enterprises to evaluate their maturity around this topic. It is simply impossible to make good decisions without knowing where you sit on the data governance spectrum.
Zeenea’s Data Governance Maturity Matrix helps data leaders identify their current situation by asking the relevant questions.
In our previous article we explained why data governance is critical for enterprises. We also talked about the differences between defensive and offensive data governance to achieve your data strategy.
In this new article, we want to focus on what kind of data governance you need and its trend according your business sector.
Whether you may like it or not, data concerns all structures and all sectors!
Regardless of your company’s industry, your competitive and regulatory environment, or your overall strategy, watch this webinar to learn more about: what is the concept of data governance and how can it help achieve your data strategy?
Join Guillaume Bodet, VP Product at Zeenea, and Dina Kim, Inside Sales at Zeenea