Kosterijland 40, 3981 AJ Bunnik
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It is now generally accepted that data is not a technical thing in itself. Data should be seen as an economic asset for any organization and hence be managed as such. This is where sound data management comes in.
It is our view that you can only realize truly predictive algorithms or data science models by making sure that you know what your data is about, that you’re sure that it has the right quality and that the data can be trusted as a source for making decisions.
So if you want to be a data driven company, get your data management basics right.
Reading The Data Management Body of Knowledge (DMBOK) can be quite daunting. `Do I really need to implement all that’, clients sometimes ask us. Our answer usually is : you only need to implement that fits your company, your culture and your type of business and of course what is needed to be compliant. Very often that doesn’t mean the whole enchilada of DMBOK at the beginning.
When implementing a data management framework, we look at your data strategy to begin with. And if you don’t have one we will help you set one up. The tool we use to create a data strategy is our ‘Target to data-model’.
You need to know what types of data are part of your business, you need to know the quality and the relevance of the data in relation to your data strategy. Because that is the data that matters. In other words, your data needs to classified. So you don’t necessarily need to know all the data, only the data that matters in your processes, which is given by your data strategy.
Knowing what data is used in what process really helps getting a grip on things. So what are the business processes within your organization, what processes interface with what kind of data, how is data integrated and in what applications and last, do you have a clear view on your data lineage?
Knowing who’s responsible for what kind of data is key in a data management framework. We will help you create a data management organization by setting up a company data dictionary and by specifying who needs to take ownership of what data entities.
Data Governance also implies various roles and skills. Many various roles can be defined but we want to keep it practical and manageable. So we will talk about data ownership, data stewards (functional and technical) and the data governor. Important is to know who does what and why, which is the fundament of ownership.
Implementing data management tooling can be part of our activities. Although our knowledge of tooling covers a wide range, we are a Microsoft first company and hence specialized in applying Purview.
We have been realizing data management frameworks for data privacy, security and compliance purposes for a large number of clients over the past 21 years. Our approach is knowledgeable and practical. Our experience ranges from government, insurance and finance to telecom, retail and media.