Tableau / Power BI / Looker
The BI and data visualisation platforms that turn database queries and spreadsheet data into dashboards, reports, and charts that non-technical stakeholders can navigate.
What it is
About Tableau / Power BI / Looker
Tableau, Power BI, and Looker are the three dominant business intelligence platforms, each providing a drag-and-drop interface for connecting to data sources, building visualisations, and publishing interactive dashboards without writing code. Tableau (now Salesforce-owned) is the most powerful visualisation tool — its calculation language and dual-axis charts handle complex analytical views that other platforms struggle with, and its Tableau Public community has built a culture of high-quality analytical storytelling. Tableau Server and Tableau Cloud provide enterprise publishing and governance. Power BI (Microsoft) is the dominant choice in Microsoft-ecosystem organisations — native integration with Excel, Azure, SharePoint, and Teams means stakeholders can embed reports directly in their existing workflows. Power BI Desktop is free; Power BI Service provides sharing and collaboration. Its DAX calculation language is powerful but has a steep learning curve. Looker (now Google Cloud Looker, distinct from Looker Studio) is the semantic layer BI platform — LookML defines the data model and business logic centrally, and business users query it through a self-service explore interface without needing SQL knowledge. Looker is the choice for organisations that want a "single source of truth" metric layer that business users can explore without writing queries. For a Data Analyst or Financial Analyst, these tools are the bridge between SQL or Excel-level analysis and the stakeholder-facing reporting layer — the place where analytical conclusions become charts and dashboards that drive business decisions.
What you can do with it
Capabilities
Connect Tableau to a PostgreSQL database, drag dimensions and measures onto a view, build a bar chart sorted by descending revenue, add a reference line at the budget target, and publish it to Tableau Server as an interactive dashboard with a date filter
Build a Power BI report with a matrix visual showing actual vs. budget variance by cost centre, add conditional formatting so negative variances appear in red, and publish it to a shared Power BI workspace that refreshes nightly from the data warehouse
Write a Power BI DAX measure for year-to-date revenue using `TOTALYTD()`, compare it to the same period last year using `SAMEPERIODLASTYEAR()`, and surface both figures in a KPI card visual on the executive summary page
Create a Tableau calculated field that classifies customers into high/medium/low value segments based on their last 12 months of spend, use it as a colour dimension on a scatter plot of spend vs. frequency, and add tooltips showing account name and last order date on hover
Set up a Power BI incremental refresh policy that processes only the last 30 days of data on each scheduled refresh — reducing a 4-hour full refresh to under 10 minutes and making daily reporting practical on a large dataset
How to learn it
Learning Resources
Tableau's free training at tableau.com/learn/training — "Getting Started with Tableau Desktop" is a genuine 6-hour structured course; Tableau Public provides a free environment to practise on public data immediately after
Microsoft's Power BI learning path at learn.microsoft.com/power-bi — the "PL-300: Microsoft Power BI Data Analyst" learning path is the best structured path to the professional certification; Power BI Desktop is free to install and practise with
Workout Wednesday (workout-wednesday.com) — weekly Power BI and Tableau challenges using real datasets; one of the fastest ways to develop practical skills in a community context
"Storytelling with Data" by Cole Nussbaumer Knaflic — the best book on the principles of data visualisation; essential before building dashboards so you understand what makes a chart communicate rather than confuse
Pro Tip
Start every dashboard by writing down the three decisions a stakeholder needs the dashboard to support — before opening the tool. The most common BI failure is a dashboard with 30 charts that answers every question except the one the stakeholder actually needs. Three decision questions give you the filter for which charts belong on page one versus which belong in an appendix drill-through, and they give you the metric definitions before any DAX or table calculation is written.
Skills that use this tool
Roles that use this tool
Alternatives