This story was originally published on HackerNoon at: https://hackernoon.com/how-i-decoded-my-apple-watch-metrics-taking-a-look-at-the-raw-numbers-part-2.
Learn how to parse Apple Health XML & GPX files. A technical guide to "streaming" large CDA files and extracting workout kinematics using Python.
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This story was written by: @farzon. Learn more about this writer by checking @farzon's about page, and for more stories, please visit hackernoon.com.

Exporting Apple Health data results in massive, messy XML files that are difficult to process. By using a "streaming" parser to filter specific LOINC codes and extracting GPS kinematics from GPX files, I converted 300MB of raw records into clean CSVs. This structured data is now ready to be fed into a custom machine learning model to reverse-engineer VO2 Max.

This story was originally published on HackerNoon at: https://hackernoon.com/why-ai-agents-are-creating-a-new-kind-of-data-engineer.
The role of data engineers is evolving faster than ever and this is the advent of intelligence engineers who will not only build AI agents but create governance
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This story was written by: @engineervarun0012. Learn more about this writer by checking @engineervarun0012's about page, and for more stories, please visit hackernoon.com.

The role of data engineers is evolving faster than ever and this is the advent of intelligence engineers who will not only build AI agents but create governance around them along with strict guardrails.The blog sheds light on the next generation data leader

This story was originally published on HackerNoon at: https://hackernoon.com/the-architectural-limits-of-data-lakes-and-the-rise-of-lakehouses.
Data lakes solve storage but not reliability. Learn how lakehouse architecture adds transactions, metadata, and governance to fix the gap.
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This story was written by: @seshendranath. Learn more about this writer by checking @seshendranath's about page, and for more stories, please visit hackernoon.com.

Raw files on object storage are great for cheap retention but terrible as a system of record lakehouse architecture adds transactional tables, versioned metadata, and schema contracts on top of the same storage, turning a dumping ground into a reliable analytical platform.