For a FAIR data
Over the last months, I wrote several articles about data governance. One aspect of data governance is also the principle of FAIR data. FAIR in the context of data stands […]
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Over the last months, I wrote several articles about data governance. One aspect of data governance is also the principle of FAIR data. FAIR in the context of data stands […]
Python is one of the most used tools for Data Science. Since its incarnation, Python received a lot of attention from both Data Scientists and Data Engineers. In a modern […]
I am talking a lot to different people in my domain – either on conferences or as I know them personally. One thing most of them have in common is […]
In our last tutorial for Data Governance, we now look at Master Data Management. This is the last of our four pillars. Master Data is the core data in the […]
Next to Data Security & Privacy as well as Data Quality Management, there is a huge importance in Data Access and Search. This topic focuses on finding and accessing data […]
We started our tutorial with a general intro to Data Governance and then went a bit deeper into data security and data privacy. In this post, we will have a […]
In our previous tutorial intro, we outlined the four pillars that are relevant to data governance. In this post, I will go for a deeper dive into the data security […]
Everybody is talking about Data Science and Big Data, but one heavily ignored topic is Data Governance and Data Quality. Executives all over the world want to invest into doing […]
A college of mine, Vivien Roussez, wrote a nice library in R to predict time series. The package is called “autoTS” and provides a high level interface for univariate time series predictions. […]
In one of my last posts, I wrote about the fact that Cloud is more PaaS/FaaS then IaaS already. In fact, IaaS doesn’t bring much value at all over traditional […]