Every company produces data, but data on its own does not make decisions. Business intelligence (BI) is the practice of collecting that data, organising it, and presenting it as reports and dashboards that people can act on. The BI analyst is the person who sits in the middle, translating between the questions the business asks and the data that can answer them.
You'll start with what BI actually is and where it fits, then look at the four types of analytics: descriptive, diagnostic, predictive, and prescriptive. From there the module maps out how data flows through a BI architecture, from source systems through a warehouse to the dashboards at the end, and clarifies how the work of an analyst differs from that of a data engineer or data scientist.
With the big picture in mind, you'll be ready for the next module, Spreadsheets & Data Literacy, where you start working hands-on with data.
An introduction to BI: what it is, the steps involved in turning raw data into insight, where it's applied in business, and the tools used.
The four levels of analytics, from reporting what happened to explaining why, forecasting what's next, and recommending what to do about it.
How a BI system fits together: data sources, the ETL process, storage layers (warehouse, data lake, data mart), OLAP, and the BI tools at the end.
How the three roles differ: what each one does, the skills they rely on, and what they typically earn, so you can see where a BI analyst fits.
A look at a typical working day in a BI-focused data role: meetings to understand business needs, checking data jobs, and building data solutions.