Kevin's Data Governance Workshop

In my Daily Work, I Help Customers to Have Data which They Can Use

My Name is Kevin Straub. My wife and I live in Stuttgart (Germany). When friends or family ask me what my job is, I usually answer that "I help other companies to have data that they can actually use…".

I learned about the importance of Data Quality more than 11 years ago when I started at IBM as a junior consultant in the area of data warehouse management. The reports that were created based on the existing data in the systems always needed to be reworked or enhanced due to a lack of quality. Since than I always thought, that there must be a more sustainable way of getting good data. Today I know how!

In my daily job I help customers to manage their data, so they get actually value out of this asset. Typically, I support companies with initiatives like:

  • Clean up and maintain clean data with our managed cloud services for customer and vendor data
  • Design and deployment of data management processes, organization & roles for different data domains
  • Design and deployment of data lifecycle processes for different data domains
  • Design and implementation of a corporate data governance & data quality management framework incl. roles, responsibilities and KPIs
  • Design and deployment of holistic data strategy incl. reference use cases in the areas of IoT, digitization, manufacturing and AI

#SharingDataExcellence: Data Governance Basics

From my experience, also in times of new trends and buzzwords like IoT or artificial intelligence, basics like data governance maintain important. We recently answered some frequently asked questions regarding data governance. As for example

  • What is a robust data governance mandate?
  • What is data governance? What are typical data management (data governance) roles?
  • Why do we need data governance?
  • How to develop a data governance framework?
  • What are typical data governance boards?

These and other question are answered here for you: Data Governance

Kevin's Free Data Governance Workshop

But for sure there are much more open questions, so we would like to raffle one free data governance workshop. Usually a short workshop helps to…

  • understand the impact of data quality for your business processes and analytics capabilities, e.g. on an enterprise analytics platform or a data lake
  • evaluate your current data governance capabilities
  • identify fields of action and recommend good practices

To participate, contact us via the contact form in the info box until the 31th of December 2019 24:00 CET and tell us why you think you need help regarding data governance. Please check out the details of our promotion in our terms of participation below.*

About the author

Kevin Straub
Data Management Expert

"Think in data assets and business processes, not in fancy software or applications!"

My gift to you

We are raffling a Data Governance Workshop in the DACH area with one of our data management experts for four people. Just fill in the online form and take part in the raffle!*

 The following rules apply for this promotion:

  • Each organization/person may only request one data governance workshop
  • We award one data governance workshop in the DACH region (Germany, Switzerland or Austria) at the customer site with one CDQ Expert and a max. of 4 participants
  • We raffle the workshop among all submissions via our specially provided online form, which will reach us by 31 December 2019 24:00 CET. The winner will be notified by email within 7 working days
  • The winner will be determined by lot
  • The personal data collected for this promotion will be processed in accordance with our privacy policy and will only be used for the purpose of contacting you regarding the data governance workshop
  • The data governance one-day workshop will be delivered on customer site within Germany, Austria or Switzerland at the latest until 31.03.2020
  • This promotion is aimed exclusively at companies and is not intended for private purposes
  • The legal recourse is excluded
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