, ,

Reading Excel (.xlsx) Files with Polars

I make it my duty in life to never have to open an Excel file (xlsx); I feel like if I do, then I made a critical error in my career trajectory. But, I recently had no choice but to open an Excel on a Mac (or try) to look at some sample data from […]

Read more
,

dbt on Databricks.

Context and Motivation dbt (Data Build Tool): A popular open-source framework that organizes SQL transformations in a modular, version-controlled, and testable way. Databricks: A platform that unifies data engineering and data science pipelines, typically with Spark (PySpark, Scala) or SparkSQL. The post explores whether a Databricks environment—often used for Lakehouse architectures—benefits from dbt, especially if […]

Read more
, , ,

Apache XTable. Delta vs Iceberg vs Hudi.

The blog post reviews an Apache Incubating project called Apache XTable, which aims to provide cross-format interoperability among Delta Lake, Apache Hudi, and Apache Iceberg. Below is a concise breakdown from some time I spend playing around this this new tool and some technical observations:

Read more
, ,

What is a Healthy Lake House?

Maybe I’m the only one who thinks about it, not sure. The Lake House has become the new Data Warehouse, yet when I ask this question “What makes a health Lake House?” no one is sure what the answer is, or you get different answers. It seems like a pretty important question considering that Lake […]

Read more
, , , , ,

AWS Lambda + DuckDB + Polars + Daft + Rust

When it comes to building modern Lake House architecture, we often get stuck in the past, doing the same old things time after time. We are human; we are lemmings; it’s just the trap we fall into. Usually, that pit we fall into is called Spark. Now, don’t get me wrong; I love Spark. We […]

Read more
, ,

PySpark Data Quality on Databricks with DQX.

A Deep Dive into Databricks Labs’ DQX: The Data Quality Game Changer for PySpark DataFrames Recently, a LinkedIn announcement caught my eye—and honestly, it had me on the edge of my seat. Databricks Labs has unveiled DQX, a Python-based Data Quality framework explicitly designed for PySpark DataFrames. Finally, a Dedicated Data Quality Tool for PySpark […]

Read more

Testing and Development for Databricks Environment and Code.

Every once in a great while, the question comes up: “How do I test my Databricks codebase?” It’s a fair question, and if you’re new to testing your code, it can seem a little overwhelming on the surface. However, I assure you the opposite is the case.

Read more
, ,

What is a Data Platform?

You know, for all the hoards of content, books, and videos produced in the “Data Space” over the last few years, famous or others, it seems I find there are volumes of information on the pieces and parts of working in Data. It could be Data Quality, Data Modeling, Data Pipelines, Data Storage, Compute, and […]

Read more

Building a Fast, Light, and CHEAP Lake House with DuckDB, Delta Lake, and AWS Lambda

Building fun things is a real part of Data Engineering. Using your creative side when building a Lake House is possible, and using tools that are outside the normal box can sometimes be preferable. Checkout this video where I dive into how I build just such a Lake House using Modern Data Stack tools like […]

Read more

Using DuckDB to read JSON files in S3

I’ve been playing around more and more lately with DuckDB. It’s a popular SQL-based tool that is lightweight and easy to use, probably one of the easiest tools to install and use. I mean, who doesn’t know how to pip install something and write SQL? Probably the very first thing you learn when cutting your […]

Read more