PyData Tallinn

What an exciting evening! I recently attended my very first PyData Tallinn event. The energy was fantastic, and the topics were deeply engaging, focusing on the cutting-edge intersection of Extended Reality (XR) and Graph Computing.

💡 Session Highlights

The main focus of the evening was on these two fascinating areas. You can find more details about the talks here: PyData Tallinn X Wise.

✨ My Top Picks & Key Takeaways

I walked away with two standout resources I’m keen to explore further:

• GraphFrames:

  • This is an impressive graph API for Apache Spark.
  • It offers a scalable and efficient way to work with graph algorithms.
  • It presents a compelling alternative to dedicated graph databases like Neo4j, especially when integrating with existing Spark pipelines.

• marimo notebook:

  • A promising, lightweight alternative to traditional Jupyter Notebooks.
  • I’m looking forward to diving in and seeing how it improves the interactive data exploration and sharing workflow.

Last time I check some big data stuffs, were Handoop and Hives, it was a great experience connecting with the local data science community and getting a glimpse into the latest developments in these fields.