Why this is in my collection

From the publisher:

Learn how to manage a modern data stack and get the most out of data in your organization! Thanks to the emergence of new technologies and the explosion of data in recent years, we need new practices for managing and getting value out of data. In the modern, data driven competitive landscape the best guess approach--reading blog posts here and there and patching together data practices without any real visibility--is no longer going to hack it. The Informed Company provides definitive direction on how best to leverage the modern data stack, including cloud computing, columnar storage, cloud ET

Highlights

  • Data maturity as staged architecture — the book walks a company from source-connected BI to lake, to warehouse, to curated marts, making the point that structure should grow in deliberate stages as the organization's questions mature rather than arrive as a big-bang design.
  • ELT: land raw first, transform inside the warehouse — preserving untransformed source data and applying logic downstream is the modern-stack echo of the raw-vault principle: never let interpretation destroy the original, keep rules replayable.
  • The transformation layer is where business logic becomes code — version-controlled, SQL-based transformation (the dbt-style layer) turns definitions and derivations into reviewable artifacts; business rules finally live somewhere inspectable instead of in analysts' heads.
  • Cloud columnar economics changed the trade-offs, not the questions — cheap storage and elastic compute reshuffled what is expensive, yet naming, meaning, and model design remain the hard part; platforms churn while the modeling problems persist, which is the MDDE reading of every stack generation.
  • Self-service stands on curated structure — the "informed company" works only when marts are cleaned, documented, and intentionally shaped for consumers; without that curation layer, self-service is just distributed confusion.
  • A challenge worth keeping — the book's start-simple, add-structure-when-it-hurts pragmatism is right for startups but inverts at enterprise scale, where retrofitting a model under load is the most expensive move available; knowing where each advice regime applies is the real skill.

Highlights on this page are generated with the help of AI.