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5 reasons for an IT auditor to become a Data Governance Consultant

If you’ve been part of IT audit engagements over the past years, there’s no doubt you’ve developed such professional qualities while working behind the scenes in IT departments. But what if you could work with your clients in project mode and build on those skills to solve their business issues? Let me give you five reasons to become a Data Governance Consultant at Datashift!

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Power BI & Collibra: A match made in heaven?

If you’re using Collibra and Power BI without a connection, then this ‘how to’ guide is a must-read! We’ll share some of the synergies between the two platforms and walk you through the integration process step by step.

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5 reasons to move your BI environment to the cloud

More and more organizations are considering a move or partial move from an on-premise set-up to a cloud environment. But what's so special about the cloud? Should you migrate or not? In this blogpost we discuss 5 must-consider reasons to move your BI environment to the cloud.

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Why big data technologies are more accessible than ever

With the shift to the cloud, big data processing is more accessible and affordable than ever before. Frameworks like Hadoop and Spark have played a central role and can’t be ignored in a modern data stack. To understand how you can get the most out of these big data frameworks, we take you through the story behind the technologies and the crucial role they play today.

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Lots of freedom and opportunity to grow, but three non-negotiable rules: this is how we role.

When it comes to company culture and organizational structure, Datashift has always been a bit “the odd one out”. We don’t follow the classical format most companies have. We don’t have a layered organization. No one is interested in the big job titles (mind you, we’re still very ambitious!). And we’re all about reaching success as a team!

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What we learned from implementing a business glossary

A business glossary is the foundation that creates a common understanding of your organization’s vocabulary and data. While the concept isn’t anything complex, the implementation can be quite daunting. In this article we provide the key lessons we’ve learned while implementing a business glossary use case at our clients.

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Upon general request: six years of Datashift, three more lessons learned.

Two weeks ago, we posted a blog article about the three lessons we’ve learned in the past six years of Datashift. We received such great responses to our list of “don’ts,” I decided to share with you a list of three “do’s.” So, back by popular demand, here are another three important lessons six years of Datashift have taught us.


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Six years of Datashift, three lessons learned

Datashift’s story started on January 15th, 2015. From the get-go, it was clear we wanted to do great things with Datashift. But building a company from the ground up is never a straight line. There are bumps in the road, highs, and lows, but most importantly: lessons learned. As we celebrate six years of Datashift, I'd like to take a look back and share exactly some of those lessons.

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How to build a churn prediction model that actually works

The truth is, predicting churn is easy. The hardest part is making it actionable. With this approach you’ll retain only your valuable customers that are about to churn, with a personalized retention action at the right time.

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