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Entendre i Representar Dades

FP DAM · CFGS · FP Illes Balears · IB1103

Every app you will ever build produces data. In four units you learn to get it out of where it lives, clean it up, and turn it into charts and dashboards people can read in two seconds.

Start with Unit 1 Calendar Learning outcomes
Units
4
extract, clean, visualise, publish
Lessons
30
each with a quick check
Hours
40
2 a week, September to March
Tools
Superset
plus Power BI and SQL on real datasets

Units

Open · RA = learning outcome

ID Unit RA Hours Status
UT1 Data sources and extraction

Where data lives and how to bring it home: connect Superset to a database, load files, and write the SQL that returns exactly what you need.

 RA1 10 Open
UT2 Cleaning and transforming data

Real data is dirty. Audit it, fix types and formats, remove duplicates, fill the gaps, add new columns, and describe what you have in a report.

 RA2 12 Open
UT3 Data visualisation

How the eye reads a chart, what each chart is for, how to pick the right one — and how to spot a chart that lies.

 RA3 8 Open
UT4 Dashboards and reports

Put the charts together: KPIs, filters and cross-filters, publishing and permissions, Power BI reports, and telling a story with data.

 RA3 10 Open

How this site works

  1. 01Read the lesson

    Every page starts from something you already do, explains the idea with one analogy, and defines every term — each bold word is in the glossary.

  2. 02Take the quick check

    Self-graded quiz at the bottom of every lesson. Your scores stay in your browser — no account, no server.

  3. 03Try it on real data

    Lessons use the class datasets (Pokémon, Steam games). Download them from Resources and run every query yourself in Superset.

AI policy: the only AI assistant authorised in this course is cs50.ai. Learning outcomes Calendar Resources Glossary