Data governance projects are often looked at as a huge exercise that might take years. It feels like a big mountain that can't be overcome, but it shouldn't have to be that way. What organizations fail to see is that it's possible to start managing data very gradually, with minimal impact on daily operations.
Your data is an opportunity to get a competitive edge, to mitigate risks and to grow your business in a sustainable way by making the right decisions. Our advice? Start small, but start now. The sooner you start organizing and managing your data, the sooner you'll see the effects.
Datashift geared us up with the required architecture, knowledge and tools to be able to steer our business with insights. They clearly understood the importance of a hands-on approach at the start, evolving into a strategic and future-proof data roadmap later on.
Bart Van Den Langenbergh,
Head of Marketing & Sales, Streamz
"Too many organizations spend their time and money on the end product of data (e.g. reports, apps, algorithms) while they forget to take care of the raw material (= data). What gets measured, gets managed. So start by measuring your data assets."
Great Expectations, an open-source Python library, provides an excellent framework to kickstart your Data Quality by Design projects, creating visibility for data quality issues, and triggering calls to action for everyone involved.
Data Governance is a collaborative process, and its implementation hinges on user adoption. Fortunately, much can be done to boost Data Governance user adoption. Check out our 3 priceless tips.
Can semantic data discovery deliver on its promise to provide a better understanding of your data and facilitate the automation of your business processes? We know it can. Learn from our experience to understand how it works and what you can achieve.
Chances are you have recently heard a lot about data mesh, a decentralized approach to sharing, accessing, and managing analytical data. So, let's dive into a practical example to help you understand what a data mesh stands for.
Soda is a new kid on the block when it comes to data quality. It excels in making it easy for business users to monitor the health of their data, enabling them to define data quality rules without a high level of technical knowledge.
As Microsoft released new APIs and Collibra has kept up with numerous new developments, the integration between Power BI and Collibra offers several new possibilities. Check out more details and download our guide with tricks and tips to facilitate this new integration.
Artificial Intelligence & Machine Learning technologies have been on the rise throughout several industries. But what about AI & ML in data governance? What developments can strengthen data governance practices, and how will they most likely do that? And what is possible today?
We polled our Collibra consultant Evert on Collibra DQ, the newest extension to the Collibra data intelligence platform. How does Evert see the future of Collibra DQ and Data Quality in general? And what are the most significant opportunities for Collibra DQ, in his opinion?
When a football team is struggling to win games and a new manager is appointed, the first thing they aim to improve is often the defense. This makes sense... you can’t win games if you’re conceding 5 goals every game. Banks often tackle data governance in the same fashion, because of data regulations. But we want to encourage them to not stop there and go from defense to offense.
Imagine, you have launched your Data Governance program 5 years ago. Over those years a lot happened: your team designed and implemented a complete Data Governance strategy. You can proudly call yourself GDPR compliant, your knowledge workers (e.g. data scientists) have access to data they trust and data is managed on a daily basis. You might think of taking the foot off the accelerator, but why not gear up? Automated data quality checks, data monetization opportunities and/or making your data management more efficient. Think big!
No one likes misunderstandings. We've all been in a "the Italian man who went to Malta" situation before. Annoyingly enough, this situation happens in a lot of businesses too. Many discussions between departments have the same root challenge: different people speaking different 'languages'. In this article, we’ll set the stage to take on this challenge.
Data governance is no longer optional. Businesses are on a path to data-driven decision-making and privacy laws are dictating the need for data integrity, security and compliancy. Choosing the right data governance software is an essential part of the road to data mastery. In this article we discuss why we believe Collibra is the best data governance tool in the market.
Many organizations struggle with ongoing data issues and are missing the opportunity to use data as a means to profoundly impact their business. What's usually missing is a comprehensive data strategy. Let's have a look at the 5 ingredients a successful long-term data strategy can't do without.
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!
What is the most challenging part of a Data Governance program? We believe that getting your organization to participate in the program and creating buy-in is the most challenging obstacle on your road to success. In this article we focus on the question: How to build a thriving Data Governance end-user community?
You weren’t able to attend Data Citizens 2020 this year? No worries, we got you covered! Collibra Data Intelligence Cloud, the next generation of Collibra, will furtherbe built on their 4 pillars: Cloud Native, API First Approach, Edge Computing & Everywhere! In this blog post, we will give you insights in the first pillar: Cloud Native.
