Build Resilient, Scalable Data Platforms with A Data Architect (Apache Contributor)

Slowly Changing Dimension (SCD) is critical to dimensional modeling. We will discuss the eight types of SCDs. By the end, you will clearly understand each type and be able to differentiate between SCDs in dimensional modeling.

Sometimes writing SQL can be frustrating, especially when encountering NULL values. This article can help you better understand NULL in SQL

My main goal is to enable people without programming experience to use the powerful Sankey Diagram by simply uploading the transaction CVS file from the popular site Mint.com.

One key learning I had while chasing the latest tool is: Tools are great, but many data engineering problems cannot be resolved by using the newest tool but by human — Data Engineers. I want to share my thoughts on Why data engineering is about much more than just the tools you ...

Let's bring the data community's attention to the essential- Building Better Data Warehouses with Dimensional Modeling: A Guide for Data Engineers.

We will focus on the Apache Spark Union Operator Performance with examples, show you the physical query plan, and share techniques for optimization in this story.

R could add potential benefits to help the data engineering community. Let's discuss about Why R for Data Engineering is More Powerful Than You Thought.

I want to share 5 hidden facts about Apache Spark that I learned throughout my career. Those can be helpful to you to save you some time reading the Apache Spark source code.

We will discuss a neglected part of Apache Spark Performance between coalesce(1) and repartition(1), and it could be one of the things to be attentive to when you check the Spark job performance.

The data engineering space is evolving. Here are the resources I collected for practical data engineering resource.

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