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HomeData Engineering and Data WarehousingA Holistic Approach To Data Governance Through Self Reflection At Collibra

A Holistic Approach To Data Governance Through Self Reflection At Collibra


Data governance is a phrase that means many different things to many different people. This is because it is actually a concept that encompasses the entire lifecycle of data, across all of the people in an organization who interact with it. Stijn Christiaens co-founded Collibra with the goal of addressing the wide variety of technological aspects that are necessary to realize such an important and expansive process. In this episode he shares his thoughts on the balance between human and technological processes that are necessary for a well-managed data governance strategy, how Collibra is designed to aid in that endeavor, and his experiences using the platform that his company is building to help power the company. This is an excellent conversation that spans the engineering and philosophical complexities of an important and ever-present aspect of working with data.


Hello and welcome to the Data Engineering Podcast, the show about modern data management

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Your host is Tobias Macey and today I’m interviewing Stijn Christiaens about data governance in the enterprise and how Collibra applies the lessons learned from their customers to their own business


How did you get involved in the area of data management?
Can you start by describing what you are building at Collibra and the story behind the company?
Wat does “data governance” mean to you, and how does that definition inform your work at Collibra?
How would you characterize the current landscape of “data governance” offerings and Collibra’s position within it?

What are the elements of governance that are often ignored in small/medium businesses but which are essential for the enterprise? (e.g. data stewards, business glossaries, etc.)
One of the most important tasks as a data professional is to establish and maintain trust in the information you are curating. What are the biggest obstacles to overcome in that mission?
What are some of the data problems that you will only find at large or complex organizations?
How does Collibra help to tame that complexity?

Who are the end users of Collibra within an organization?
Can you talk through the workflow and various interactions that your customers have as it relates to the overall flow of data through an organization?
Can you describe how the Collibra platform is implemented?
How has the scope and design of the system evolved since you first began working on it?

You are currently leading a team that uses Collibra to manage the operations of the business. What are some of the most notable surprises that you have learned from being your own customer?
What are some of the weak points that you have been able to identify and resolve?
How have you been able to use those lessons to help your customers?

What are the activities that are resistant to automation?
How do you design the system to allow for a smooth handoff between mechanistic and humanistic processes?

What are some of the most interesting, innovative, or unexpected ways that you have seen Collibra used?
What are the most interesting, unexpected, or challenging lessons that you have learned while building and growing Collibra, and running the internal data office?
When is Collibra the wrong choice?
What do you have planned for the future of the platform?

Contact Info

@stichris on Twitter

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?


Collibra Data Office
Electrical Engineering
Resistor Color Codes
STAR Lab (semantics, technology, and research)
Microsoft Azure
Data Governance
Chief Data Officer
Dunbar’s Number
Business Glossary
Data Steward
ERP == Enterprise Resource Planning
CRM == Customer Relationship Management
Data Ownership
Data Mesh
Podcast Episode

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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