Bad data leads to bad outcomes. We can say the same sentence a la Scott Taylor "Good decisions based on bad data are just bad decisions you don't know about yet." A data management program is how we bring trust and structure to this data mess.

Note that I said "program" not "project", because DM is a strategic initiative that impacts the organisation as a whole, and requires strong leadership support. Data management is complex enough when we have the luxury of building a modern data architecture from scratch. Imagine when you are forced to work with legacy systems.

No one knows this better than my friend Vlad Ardelean. Vlad works for Growth from Knowledge - GfK is a German company founded almost 90 years ago in 1934 in Nuremberg. Their proposition is very attractive to the many seeking to gain insights from their messy data: whatever the shape or form, you give your data to GfK along with a business question, and you get back the best possible answer.

As you can imagine, they have seen them all, and they wouldn't be in business without an excellent data management program.

Today we speak about creating structure from chaos, the perception of data management, the business vs technical divide, and how data practitioners need to be a lot closer to the business.

Dr. Vlad has expertise in statistics and machine learning and is the data science lead at GfK where he worked for the past 7 years. Vlad focuses on developing end-to-end solutions with a cross-functional team, especially in the area of data quality

He completed his studies in mathematics/economics at the Friedrich Alexander University in Erlangen-Nuremberg. There he also did his doctorate at the chair for statistics on the identification of outliers in time series

Vlad is very Interested in the Impact of AI on society and how we should mitigate risks, in the context of recommendation systems and filter bubbles. Vlad is also a Husband and Father of 3 boys.