Module
Module 6 of 6Lesson 1 of 3~13 min

Access real data without risk, for the product and for people

Querying your company's real data comes with responsibility, toward the product and toward the people behind the data. The lesson helps you write an access request the engineering team will approve without hesitation and write queries that respect privacy. You gain autonomy without creating a security or compliance risk.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will be able to request data access that follows least privilege (analytics database, read-only, scope, excluded columns, duration), write queries that expose only the personal data needed and know what to do with a result that contains some.

Topics covered

  • read-only access
  • least privilege
  • GDPR
  • personal data
  • data minimization

Where it fits

Query safely, with AI

How do I access real data without risk to production or to privacy, and how do I have an AI write SQL without getting it wrong?

Lessons in this module

  1. Access real data without risk, for the product and for people (this lesson)
  2. Have an AI write SQL, and check it
  3. Final workshop: your feature's data model and your ten queries

What you will learn in the course

This lesson is part of the course Model your product’s data and query it with SQL

  • Read a data model (tables, primary and foreign keys, cardinalities, entity-relationship diagram) and connect it to the product's screens and rules.
  • Model the data of a feature (entities, attributes, relationships, keys, cardinalities) and get the model validated by the engineering team.
  • Compare a relational database and a document (NoSQL) database for a product need and justify the choice based on expected queries, consistency and change.
  • Write queries that filter, sort and aggregate (SELECT, WHERE, ORDER BY, GROUP BY, HAVING) while handling NULL values and dates correctly.
  • Combine several tables with INNER and LEFT joins, and check that the result neither loses nor duplicates any row.
  • Turn a product question into a verifiable query, using CTEs and simple window functions (ROW_NUMBER, LAG, SUM OVER).
  • Query data read-only while protecting personal data, and have an AI draft SQL while checking every query before using its result.

Related courses