Career

Data analyst

  • 2 learning paths
  • 13 labs
  • 23 h 25 min

Make a company's data talk with SQL, then protect it: backups, restore, recovery to the minute. Useful wherever there is a database, which is everywhere.

The roles this career prepares you for

  • Junior data analyst
  • SQL developer
  • Junior database administrator

Every lab makes you practise what these roles call for, on a real company case: experience you can talk through in an interview.

The learning paths, in order

  1. Step 1
    Learning path

    SQL and PostgreSQL: from your first query to optimisation

    Mama Ngo has run a shop in Yaoundé for twenty years. In the spring, her nephew set up a computerised till for her. Since then, everything is recorded, and she no longer knows anything. The notebook answered her questions; the database does not. You are going to learn to answer them. How much did I sell this month? What really brings money in, once the wholesaler is paid? Who still owes me money? Each workshop starts from a question she really asks, and ends when you know how to handle it, on real data, never on a made-up example. We start by opening a database and looking at what is inside: no prerequisite, not even having used a terminal before. Then the shop grows, and so do the questions: a niece who enters anything, a cooperative with a million sales, two tills selling the same bottle. You will end up on the other side of the server, finding the session that freezes a till one Saturday morning. Nine workshops and a challenge, seventeen hours of practice: the SQL queries expected in an entry-level job, then what sets apart someone who writes queries from someone you trust with a database. It is just as useful in an SME running an ERP as for reconciling a mobile money account.

    • 10 labs
    • 17 h 15 min
    • Beginner → Intermediate
    Explore the path
  2. Step 2
    Learning path

    PostgreSQL: backup, restore and PITR

    A backup that nobody has ever restored is not a backup. Three missions on a fintech's payments database: automating dumps to S3, replaying them under pressure the day the database goes down, then bringing data loss down from twenty-four hours to the minute with continuous archiving.

    • 3 labs
    • 6 h 10 min
    • Intermediate → Advanced
    Explore the path

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