Data Architect

Software systems are increasingly based on data, rather than code. A new class of tools and technologies have emerged to process data for both analytics and ML.

This post goes over what the term data warehousing means. This post provides a simple e-commerce relational data model and how it has to be changed to fit analytical queries. It also covers the reasoning behind wanting to use a data warehouse and how to choose an appropriate database for your project.

The transformations to mold the data from an application in a form that is better suited for data analysis is done in a data warehouse.

What is data versioning? When is data versioning appropriate? We review the various tools and use-cases needed for the best implementation.

Confused by all the "data lake vs data warehouse" articles? Struggling to understand what the differences between data lakes and warehouses are? Then this post is for you. We go over what data lakes and warehouses are. We also cover the key points to consider when choosing your lake and warehouse tools.

Data Lake and the Data Warehouse. They seemed similar, but there are differences.

When I talk to people who are not deep into the Power BI world, I often get the impression that they think of Power BI as a visualization tool exclusively. While that is true to a certain extent, it seems to me that they are not seeing the bigger picture – or maybe it’s better to say – they see just

Discover the most used messaging patterns and how data movement affects operational complexity, costs, and sustainability.

Read writing about Data Architecture in Data Engineer Things. Things learned in our data engineering journey and ideas on data and engineering.