In this Blogpost I will give a short introduction on User and Access management in AWS. More specifically I will focus on two AWS services which are built to fit this purpose: Identity and Access Management (IAM) and Lake Formation (LF).
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Machine learning & analytics on AWS – Sagemaker
In this blog, Jasper will tell you everything about AWS Sagemaker, explore the different features of this service together with pros & cons and give you a step-by-step approach for building your own machine learning algorithm on AWS.
Azure user and access management
Today, I’ll show you how we can do user and access management inside Azure. How do you secure a specific column? How do you deny people access to specific files? All answers below. Enjoy reading!
Reporting tools: which to pick?
In this blog, we’ll tackle one of the most-asked questions nowadays: which reporting tool should I pick? At the end of this blog, you’ll have a better idea of the option which suits you best. Thanks!
ETL on AWS – Time to face, a real-life case!
The goal of this second blog about ETL on AWS is to apply the theory that we’ve learned in the previous blog and experience what it’s like to build an ETL pipeline and how GLUE interacts with other AWS services.
ETL on AWS – Ain’t got a clue? Use AWS glue!
This blog tells you all you need to know to start building your ETL pipeline in AWS and tackles the next steps that are needed to extract, transform & load your data for analytics, reporting & machine learning.
Data Mess: Data Platform, -Warehouse, -Lake, -Lakehouse, -Mesh, … What’s the difference?
As the data world is very eager to come up with new concepts, it is very understandable that it’s hard to keep up. In this blogpost, we’ll try to explain all different concepts to you.