Stores data at scale

Stores data at scale means the tool itself holds and queries very large datasets, as a data warehouse or database does, rather than only displaying data kept elsewhere. For example, you can load years of order and web traffic records into it and ask questions across all of them. Google BigQuery is one tool that offers this.

Dashboard tools often read from other systems, which can be slow or limited when the data grows. A warehouse keeps the history in one place and answers large questions quickly. It matters when you have millions of rows, many sources or a need to keep long histories. A small business with modest data can usually do without one, and a spreadsheet or the reporting inside its existing tools will serve.

• Ask how storage and queries are charged, and whether you can set limits to avoid surprise bills.
• Check how data gets in, for example by connectors, file uploads or code.
• Test how fast a query over your real data runs.
• Find out who will maintain it, as warehouses usually need someone comfortable with SQL.