Why the reports of software’s demise are greatly exaggerated.

Learn about the Data Tech Stack used by Netflix to process trillions of events every day.

The application of analytics to people data empowers organizations to harness the full potential of their most important asset: their people.

And implementation architectures.

Introduction

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

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

In recent years, I’ve done dozens of training on various data platform topics, for all kinds of audiences. When teaching various data platform concepts and techniques, I find one of the concepts particularly intimidating for many business analysts, especially those who are just starting their journe

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.

What is Multidimensional schemas? Multidimensional schema is especially designed to model data warehouse systems. The schemas are designed to address the unique needs of very large databases designed

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Learn the key steps of deploying databases and stateful workloads in Kubernetes and meet cloud-native technologies that can streamline Apache Cassandra for K8s.

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

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

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.

I got sucked into a data mesh Twitter thread this weekend (it’s worth a read if you haven’t seen it). Data meshes have clearly struck a nerve. Some don’t understand them, while others believe they’r

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.

Data powers Uber Uber has revolutionized how the world moves by powering billions of rides and deliveries connecting millions of riders, businesses, restaurants, drivers, and couriers. At the heart of this massive transportation platform is Big Data and Data Science that powers everything that Uber does, such as better pricing and matching, fraud detection, lowering ETAs, and experimentation. Petabytes of data are collected and processed per day and thousands of users derive insights and make decisions from this data to build/improve these products. Problems beyond scale While we are able to scale our data systems, we previously didn’t focus enough