Google Data Studio for Data Visualization is a practical course in building dashboards with Data Studio, from connecting Google Sheets, GA4 and BigQuery data to calculated fields, blending, interactive controls and scheduled email delivery. It suits sales, marketing and finance teams and data analysts who report regularly, and you leave with a sales dashboard you can reuse as a template.
Many organisations still build reports by copying data out of several systems into Excel every week and passing the files around by email. The numbers never quite match, managers wait for their reports, and the people who make them spend their time on repetitive work instead of analysis. Google's Data Studio (known as Looker Studio until Google restored the original name in April 2026) is a free dashboard tool that connects to many data sources and keeps the numbers up to date without rebuilding the report each time.
This course starts by planning a dashboard around business questions, then connects data from Google Sheets, CSV files, Google Analytics 4 and BigQuery, builds calculated fields, combines sources with data blending and picks the right chart for the data. Learners then make reports interactive with controls, filters and parameters, design them to be easy to read and on brand, share them securely, schedule email delivery and make them load quickly, before building a sales dashboard from start to finish. (2 days, 6 hours per day, 12 hours in total, Beginner to Intermediate level.)
Course Details
This course runs for 2 days, 6 hours per day (12 hours in total, 09:00-16:00), as lectures with labs built on one fictional company's sales data throughout. Beginner to Intermediate level, with no SQL or programming required. Data Studio is the current name of Looker Studio, restored by Google in April 2026, and existing reports keep working. All labs use the free edition with a Google account, and the Pro edition is summarised to help organisations decide whether they need it. Learners take home a lab guide, the sample data and the sales dashboard they build, ready to reuse as a template.
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
No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770
Start by deciding who will use the dashboard, what decisions they make and which KPIs measure them. Clean the source data into tidy tables, connect it as a data source such as Google Sheets or BigQuery, add the calculated fields you need and pick charts that answer each question, such as scorecards for KPIs and time series for trends. Finish with date controls and share it with users. The course works through every step with sample sales data.
Data blending combines data from several data sources in one chart using a join key, for example comparing actual sales with targets kept in a separate file. Choose the right join type and check that the keys match in format and level of detail, otherwise figures can be duplicated or go missing. For many sources or large data, combining at the source, such as in BigQuery, is usually more accurate and faster.
A filter removes rows that do not match a condition. A parameter is a value that report viewers can change themselves and that you use inside calculated fields, so it changes the result of a calculation without removing data, for example adjusting a sales target to see the effect on profit in a what-if analysis. Parameters can also be passed into a BigQuery custom query.
It suits staff who produce regular reports in Excel or Google Sheets, sales, marketing and finance teams who track KPIs, and analysts who want a free dashboard tool. You should be comfortable with Excel or Google Sheets, including basic formulas and pivot tables, and understand business figures such as sales, cost and profit. No SQL or programming is required.
You will be able to connect Google Sheets, CSV, GA4 and BigQuery data, build calculated fields and blend data correctly, choose charts with period comparisons, create interactive multi-page reports in your brand style, and schedule reports by email. Participants who complete the training receive a Certificate of Completion with its own number, which can be verified online.
Yes. It can be run in-house for your team, with examples adapted to your own work, such as dashboards built around the KPIs and reports your team already produces. You can request a quotation from this page, or contact us on LINE @itgenius or by phone on 02-570-8449.
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