Google Data Studio for Data Visualization

Section 1: Lab: Getting Started with Data Studio

• What Data Studio is, and what changed from its former name, Looker Studio

• Reports, data sources and components in the report editor

• Plan the dashboard first: who uses it, what they decide and which KPIs measure it

• Lab: build a first report from sales data in Google Sheets

Section 2: Connecting Data Sources

• Common connectors: Google Sheets, CSV upload, Google Analytics 4 and BigQuery

• Embedded versus reusable data sources, and partner connectors

• Owner's credentials versus viewer's credentials, and data freshness

• Preparing clean, tidy source tables before connecting

• Lab: bring Google Sheets, a CSV file and the GA4 demo account into one report

Section 3: Dimensions, Metrics and Calculated Fields

• Field data types and setting the right aggregation

• Calculated fields with common number, text and date functions

• Group values with CASE and build ratio metrics such as margin and conversion rate

• Lab: create profit, price band and region fields from sales data

Section 4: Lab: Combining Sources with Data Blending

• Blend data on join keys with the different join types

• Duplicated or missing figures after a blend, and how to check for them

• When to blend in the report and when to combine data at the source

• Lab: compare actual sales with targets kept in a separate file

Section 5: Choosing the Right Chart for the Question

• Scorecards for KPIs and time series for trends

• When to use bar, combo and pie charts, and when not to

• Tables, pivot tables and heatmaps for detail

• Geo charts and Google Maps for regional data

Section 6: Lab: Adding Depth to Charts

• Comparison date ranges against the previous period and the previous year

• Drill down and optional metrics so users can choose their own view

• Conditional formatting to highlight figures above or below a threshold

• Lab: build a monthly sales overview page with year-on-year comparison

Section 7: Lab: Controls and Filters

• Date range controls, drop-down lists and input boxes

• Chart-level, page-level and report-level filters

• Cross-filtering: click one chart to filter the others on the page

• Lab: a sales analysis page filtered by period, branch and product

Section 8: Parameters and What-if Analysis

• What parameters are and how they differ from filters

• Use parameters in calculated fields, for example to adjust targets or discounts

• Pass parameter values into BigQuery custom queries

• Lab: model profit as sales targets and discounts change

Section 9: Dashboard Design and Company Branding

• Design for readability: hierarchy, layout and use of colour

• Theme and layout with the company's logo, colours and fonts

• Multi-page reports, navigation and layouts that work on mobile

• Templates so new reports look consistent across the organisation

• Lab: restyle the sales report in the company brand

Section 10: Sharing and Automatic Report Delivery

• Share as viewer or editor, share by link, and embed reports in a website

• Filter by email so each user sees only their own data

• Scheduled delivery of reports by email, and downloading as PDF

• Lab: send a sales summary to management every Monday morning

Section 11: Performance and Use Across the Organisation

• Why reports load slowly, and cutting the number of charts and blends per page

• Extract data, caching, and summarising data in BigQuery before it reaches the report

• An overview of the Pro edition: team workspaces and organisation-owned reports

• The AI assistant in Data Studio for asking questions in natural language (depending on edition)

Section 12: Workshop: Capstone Sales Dashboard

• Take a brief from a fictional executive and define the KPIs and page layout

• Connect sales, target and customer data with the calculated fields needed

• Build a multi-page dashboard with controls and scheduled delivery

• Present the work, review it together and wrap up with a pre-publication checklist