Map the layers of a data stack
Understand source systems, ingestion, storage, transformation, orchestration, and consumption as one flow.
Open guide →Home / Guide Library
Browse by job to be doneGuides for building a data stack that holds together.
Use the search or topic filters to find practical starting points across ingestion, modeling, orchestration, governance, and delivery.
Choose a data ingestion pattern
Compare batch loads, change data capture, and event streams by need and constraint.
Open guide →Organize transformations into clear layers
Keep source cleanup, reusable logic, and business-facing models understandable.
Open guide →Warehouse, lake, or lakehouse?
Start with workload, data shape, governance needs, and operating model.
Open guide →Design a workflow that can recover
Plan dependencies, retries, backfills, and alert paths before production.
Open guide →Choose checks that reflect real risk
Test the fields and assumptions that matter to downstream users.
Open guide →Trace where a metric came from
Follow dependencies from source to model to report.
Open guide →Make data access intentional
Connect ownership, sensitivity, and permissions to how data is used.
Open guide →Read a slow or expensive query as a system clue
Check access patterns, model design, refresh cadence, and compute configuration.
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