Data governance: Definition

In the race for digital transformation organizations are looking to become “data-driven”.

The influx of information and the massive amount of stored data are forcing 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) and control over data management. The aim of data governance 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. Our aim is to highlight the key attributes for a successful data governance, capable of meeting the challenges of this new era 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.

Bottom up

gouvernance des données bottom up

“Data governance must be as close as possible to your company’s operational reality.”

A bottom-up data governance strategy encourages putting individuals and their interactions ahead of processes and tools

A data governance approach is only successful when it involves all the members of an organization, thus benefiting from collective intelligence.

Non intrusive

gouvernance des données non intrusive

“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 must give your collaborators freedom to use the tools adapted to their uses.


gouvernance des données automatisée

Data governance must reflect your data assets accurately.”

Automating metadata collection on your data assets allows your tools to reflect reality accurately.  This automation ensures that such governance is kept up-to-date and able to scale up.


gouvernance des données collaborative

“Data governance must involve and federate all employees of an organization.” 

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.


gouvernance des données itérative


“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.

Why start an agile Data governance?


For the past few years, on the trails of GAFA (Google, Apple, Facebook, and Amazon), data is perceived as a crucial asset for enterprises.

How does Data Democracy strengthen agile data governance?

In this second edition, we decided to tackle the organization of this new, agile data governance and its scaling process using this same mindset.

Start metadata management in 6 weeks


The effective guide to start metadata management in 6 weeks.

Find out more about data governance

Why Data Privacy is essential for successful data governance?

Why Data Privacy is essential for successful data governance?

Data Privacy is a priority for organizations that wish to fully exploit their data. Considered the foundation of trust between a company and its customers, Data Privacy is the pillar of successful data governance. Understand why in this article.Whatever the sector of activity or the size of a company, data now plays a key role in the ability for organizations to adapt to their customers, ecosystem, and even competitors. The numbers speak ...
What is the difference between data governance and data management?

What is the difference between data governance and data management?

In a world where companies aspire to become data-driven, data management and data governance are concepts that must be mastered at all costs. Too often perceived as related or even interchangeable disciplines, the differences are important. A company wanting to become data-driven must master the disciplines, concepts, and methodologies that govern the collection and use of data. Among those that are most often misunderstood are data ...
Data literacy: the foundation for effective data governance

Data literacy: the foundation for effective data governance

On September 28th and 29th, we attended several conferences during the Big Data & AI Paris 2021. One of these conferences particularly caught our attention around a very trendy topic: data literacy. In this article, we will present best practices for implementing data literacy that Jennifer Belissent, Analyst at Forrester and Data Analyst at Snowflake, shared during her presentation. She also detailed why this practice is essential ...

Discover all of Zeenea's values

Let's get started
Make data meaningful & discoverable for your teams
Learn more >