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What Databases Are and How They Store Information
A plain-language introduction to databases: how tables, records and fields organize information, and why structured storage beats scattered files.
Artificial Intelligence and Data
Data and Databases
How data is stored, cleaned, queried and shown.
Correlation and Causation in Everyday Data
Why two trends moving together proves little: hypothetical examples of confounders, coincidence and reverse direction, plus questions to ask of any claim.
Data Cleaning: Why Messy Data Causes Wrong Answers
Common data problems such as duplicates, missing values and inconsistent formats, and the practical steps analysts use to find and fix them.
How Data Backups Work and Why They Fail
How backup copies, schedules and retention work, the common reasons backups fail when needed, and why regular restore testing makes them useful.
How Data Visualization Makes Numbers Understandable
How charts help readers see patterns in numbers, which chart types fit which questions, and the common ways graphs mislead through scale and framing.
SQL and NoSQL Databases Compared
How relational SQL databases and the broader family of NoSQL databases differ in structure, flexibility and scaling, and when each tends to fit.
Structured and Unstructured Data Explained
What separates neatly organized records from free text, images and audio, how semi-structured data fits in, and why the difference shapes storage and analysis.
What a Data Warehouse Is
A plain explanation of data warehouses: central stores built for reporting across many sources, how data gets loaded, and how they differ from everyday databases.
What Data Lakes Are and How They Differ From Warehouses
How a data lake stores raw data of many formats before anyone decides how to use it, how that differs from a warehouse, and the risk of a data swamp.
What Metadata Is and Why It Matters
Metadata is data about data. Learn what file details photos, documents and web pages carry, how they help find and manage files, and the privacy tradeoffs.
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