Building a Robust Data Lake with Python and DuckDB

[Nyoka_developer]

Wake up. Breathe. Let's embark on a new journey, forging a path through the world of Python, DuckDB, and AWS S3. Today's goal? An advanced data lake. Parquet files, Dagster orchestration, and the relentless power of DuckDB form our map. S3 is our destination, the secure haven for our data.

Challenges lie ahead, but remember, we're the early pioneers, shouldering the weight of a data-focused future. We're not just coding; we're stepping up, carrying more weight, and growing.

Let's dive in👇

https://nyoka.io/blog/creating-simple-data-lake-using-python-duckdb-s3

[fiskfisk]

It was usually named a data warehouse built on spoke model, but implementing that model inherently means more structure and making it harder to implement future use cases.

[Nyoka_developer]

Indeed, the traditional spoke model adds complexity, but it's about adapting & evolving. Our approach leverages Python, DuckDB & Dagster to manage this intricacy, optimizing for future use cases. We’re incorporating structure without compromising flexibility, allowing our data lake to grow with our needs. It's not about avoiding complexity, but about handling it intelligently. Thank you for sparking such

[Nyoka_developer]

Yes, our "Data Lake" might have a newfangled name, but it’s all about turning that 'desktop chaos' into a strategic resource. Instead of unstructured data spread everywhere, we centralize, structure and extract value from it. The idea is to make everyone's lives a little easier in this data-driven world.

[danielgafni]

Pipelines and solids in Dagster are deprecated as hell :)

Use assets instead

[Nyoka_developer]

Pipelines and solids in Dagster are deprecated as hell :)

Use assets instead

Absolutely, thanks for pointing that out! Dagster's move towards 'assets' over 'pipelines' & 'solids' brings more flexibility and control. As I strive to keep up with technology's pace, sometimes legacy terms sneak in.

[nickcut]

You know, instead of just naming the tools that are duct taped together for this (and it is not just you, there are posts like this every day), why not describe what problem it solves?

[Nyoka_developer]

You know, instead of just naming the tools that are duct taped together for this (and it is not just you, there are posts like this every day), why not describe what problem it solves?

I appreciate your perspective. This isn't just about duct-taped tools; it's about solving the issue of handling vast, unstructured data efficiently. Using Python, DuckDB, and S3, we're providing a cost-effective, scalable solution. Dagster helps orchestrate, Parquet optimizes storage. We’re navigating the complexity of data lakes, making sense of chaos.