Snapshot
Understand a snapshot as a defined data state, and distinguish it from a consistent export, event history, and backup.
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Lakehouse
Understand how a lakehouse combines lake storage with reliable table management and analytical query capabilities.
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Data Warehouse
Learn why warehouses organize data for analysis and how their role differs from operational databases and lakes.
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Data Lake
Understand what a data lake stores, how readers interpret it, and why metadata and governance remain necessary.
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Reconciliation
Learn how reconciliation compares data with a reference and why matching row counts or totals can hide errors.
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Data Freshness
Understand what data freshness measures and why one recent timestamp cannot prove that a dataset is complete.
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Stream Processing
Learn how streaming handles ongoing input, event time, windows, and late arrivals without assuming zero delay.
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Batch Processing
Understand bounded input, repeatable batch runs, and why batch processing does not necessarily mean a daily job.
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Change Data Capture (CDC)
Understand how CDC captures database changes and what snapshots, deletes, and replay mean for downstream data.
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Schema
Learn how a schema defines record structure, required fields, and types without proving business correctness.
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Data Ingestion
Learn how data enters a target environment and why successful ingestion does not guarantee complete data.
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Source System
Understand source systems, authoritative records, and why an upstream source is not automatically correct.
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Data Product
Define a data product through its users, purpose, ownership, meaning, and service expectations.
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Data Platform
Learn what a data platform provides and how shared capabilities support pipelines and usable data products.
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Data Pipeline
Understand how a data pipeline moves and transforms data, and how it differs from a platform or product.