Unit 03: LO 5 - 5.4 - Data (source, cleanse, save)

Remember to capture screenshots of the process you take with the installation

Source, cleanse and save a data set for analysis

Use this link to do the work (ACTUAL LESSON) to teach yourself how to use Power BI (GDP web instructions), then download the Spotify file below to do the same work (but different import (Load). It's about ETL, but mainly 'Transforming' the data in whatever way you want and whatever graphs/charts you want. There is no correct answer here. It's about learning something new (hopefully).

1a. Your actual screenshots for the Word document will come from using the Spotify file below.

1b. The charts and graphs (data visualisations) you create at the end of this lesson are your screenshots for Unit 03: LO 6 - 6.3 - Present Data Visualisations

Assessment

Source, must include:

Cleanse, must include:

appropriate software to cleanse and validate the data (for example, MS Excel or Power BI)

Save, must include:

spotify-2023.csv

Where to Look: Visit secondary data sources like Kaggle or government websites (e.g., gov.uk).
What to Look For: Make sure the dataset you choose has at least 500 data entry points to fulfill your requirement.

Choose Your Tool: Open the data file using an appropriate software tool. You can use MS Excel if the data size is manageable or Python libraries like Pandas for larger datasets.
- MS Excel:
  - Remove duplicate rows by going to Data > Remove Duplicates.
  - Fill or remove any missing values by selecting the range and choosing Home > Find & Select > Go To Special > Blanks then filling/deleting.

Validation: Validate the data types and constraints. For example, make sure that age columns contain only numerical data, or that email columns contain valid email addresses.

Choose File Format: Decide on a file format that suits your needs. Both .csv and .xls are commonly used.
- MS Excel:
  - Go to File > Save As and choose the format you need.