Data lineage refers to the ability to trace how and where data sources are used.
As datasets become more complex and the number of contributors grow, it becomes more and more difficult to understand the relationships between different data sources.
Having a solid understanding of data lineage makes operational maintenance much easier. e.g. a common request of data engineering teams is to backfill a table after a bug is fixed in its source data.
Questions to ask to manage hybrid strategy:
every line of code is a liability: you need to maintain it
Profile image: https://github.com/user.png
Publish SSH keys: https://github.com/user.keys
Publish GPG keys: https://github.com/user.gpg
User feeds: https://github.com/user.atom
How slack classifies email into internal/external.
Realtime data are feed in to provide domain knowledge while maintaining low compute footprint.
Self-healing (periodic full data fetch) are performed to prevent data drift
When you visit a website, you generally make a judgement about its trustworthiness and reliability within a minute. Footer signaling is a big part of that.
User Embeddings + MLP Classifiers
onboarding impacts retention, new hire productivity and manager satisfaction. The article outlines the common practice and milestones of new joiners’ onboarding journey.
The author tells a story of how he tries to uncover the attacker through fake websites, fake SQL dump and Tor exit nodes
The PM(Pickle Machine) contains two opcodes that can execute arbitrary Python code outside of the PM, pushing the result onto the PM’s stack:
GLOBAL is used to import a Python module or class, and
REDUCE is used to apply a set of arguments to a callable, typically previously imported through…