Google Looker Studio Performance Dashboard Training Course

Course overview

Business teams often receive reports that look polished but cannot answer the operational questions behind revenue, cost, service, marketing, or delivery performance. Data sits across Google Analytics, spreadsheets, CRM exports, BigQuery tables, and advertising platforms; definitions vary between teams; and dashboards become slow, manually maintained, or distrusted. This course equips participants to design Google Looker Studio dashboards that give decision-makers a reliable view of performance, drill into exceptions, and act on agreed measures rather than disconnected charts.

Participants build advanced Looker Studio reports from the data model outward. They connect and prepare data from Google Sheets, BigQuery, Google Analytics 4, and common connectors; define calculated fields and date comparisons; use parameters, controls, filters, blends, and scorecards; and select visualisations that expose trends, targets, cohorts, contribution, and variance. The course also addresses semantic consistency, report navigation, dashboard performance, access control, refresh behaviour, and testing so that dashboards remain credible after publication.

Instruction combines short demonstrations with structured build exercises using a realistic multi-source business-performance case. Participants progressively create an executive performance dashboard and supporting diagnostic pages, documenting KPI definitions, data sources, assumptions, and intended actions. They leave with a reusable dashboard blueprint, a KPI specification template, and an improvement plan for applying Looker Studio to a live reporting requirement in their organisation.

The course is designed for analysts, reporting specialists, digital teams, and managers who already work with business data and need to move from static reporting to governed, interactive performance dashboards. It is particularly valuable where teams need a practical reporting standard that can be adopted across functions.

Course objectives

By the end of this course, participants will be able to:

• Design a stakeholder-led KPI framework that links business objectives, measures, targets, owners, and dashboard actions
• Connect Google Looker Studio to Google Sheets, BigQuery, Google Analytics 4, and approved partner data connectors
• Build calculated fields, conditional logic, date ranges, comparison periods, and parameter-driven metrics
• Create interactive dashboard navigation using controls, filter interactions, drill-downs, report-level settings, and reusable components
• Blend compatible data sources to analyse performance across campaign, web, sales, and operational datasets
• Select and configure scorecards, time series, tables, bullet charts, and scatter charts for specific management questions
• Diagnose slow or unreliable reports by reviewing query scope, connector behaviour, extract data, field design, and filter use
• Produce a publish-ready performance dashboard with KPI definitions, testing checks, access settings, and a stakeholder handover plan

Benefits of attending

Target competencies

Who should attend

• Business Intelligence Analysts — who need to turn multi-source data into trusted management dashboards
• Data Analysts — who prepare performance reporting and want stronger interactive visualisation capability
• Digital Analytics Specialists — who need to combine GA4, campaign, and conversion data for commercial reporting
• Marketing Performance Managers — who must monitor channel results, budget efficiency, and campaign contribution
• Operations Managers — who need timely dashboards for service levels, throughput, exceptions, and target tracking
• Reporting and Insights Managers — who set reporting standards and need teams to build maintainable Looker Studio assets

Requirements and prerequisites

Participants should be comfortable working with tabular business data and interpreting common measures such as totals, rates, averages, targets, and period-on-period change. Prior use of spreadsheets, including filters, basic formulas, and pivot-style analysis, is expected. Familiarity with at least one reporting source such as Google Sheets, GA4, BigQuery, CRM exports, or advertising data is useful. Participants should already understand the business area whose performance they report. SQL and prior Looker Studio experience are not required, although the course includes BigQuery concepts and calculated-field logic that experienced analysts can apply immediately.

Training methodology

The course is delivered through instructor-led demonstrations, guided dashboard builds, and review discussions using a multi-source business-performance case. Participants configure real Looker Studio reports rather than work only from slides, progressing from KPI requirements and data connections to calculated metrics, interactive pages, and publication controls. Short case critiques show why dashboards fail or mislead. Teams review each other's layouts against decision-use criteria, then complete an individual application plan that identifies a live dashboard, source data, stakeholders, and validation steps for their workplace.

Course outline

Day 1: Dashboard strategy, KPI design and data foundations

• Decision-led dashboard requirements and stakeholder question mapping
• KPI trees, targets, thresholds, and metric ownership
• Looker Studio report architecture, pages, components, and themes
• Data source types, connector selection, and refresh behaviour
• Connecting Google Sheets and managing source-field types
• GA4 and BigQuery connection fundamentals
• Data quality checks for grain, completeness, duplicates, and date coverage

Workshop: Participants create a dashboard requirements canvas and connect a supplied business dataset, producing an agreed KPI inventory and source map.

Day 2: Calculated metrics and analytical data preparation

• Field dimensions, metrics, aggregation, and default aggregation rules
• Calculated fields using arithmetic, CASE logic, text, and date functions
• Rate, ratio, conversion, and variance metric design
• Date range dimensions and comparison-period calculations
• Parameters for user-selected targets, scenarios, and metric switches
• Data blending joins, join keys, and grain compatibility
• Extract data sources and refresh-performance trade-offs

Workshop: Participants build a calculated KPI layer and blended performance dataset, producing a validated margin, conversion, and target-variance view.

Day 3: Visual analysis and interactive report design

• Scorecards with comparison labels, sparklines, and conditional styling
• Time series analysis with date granularity and reference lines
• Tables, pivot tables, heatmaps, and conditional formatting
• Bullet charts, scatter charts, and contribution visualisations
• Chart selection for trend, ranking, distribution, relationship, and exception analysis
• Filter controls, date controls, and control scope
• Drill-down dimensions, cross-filtering, and interactive navigation

Workshop: Participants build an executive summary page and diagnostic analysis page, producing a clickable dashboard with controls and drill paths.

Day 4: Trust, performance and dashboard governance

• Metric definition documentation and semantic consistency
• Validation methods for dashboard totals and calculated fields
• Report-level versus page-level filters and common filtering errors
• Query reduction through date ranges, field selection, and chart design
• Data freshness, connector limits, caching, and refresh troubleshooting
• Sharing permissions, owner credentials, and viewer access models
• Accessibility, layout hierarchy, mobile viewing, and dashboard usability testing

Workshop: Participants audit a deliberately flawed report, producing a prioritised remediation log covering accuracy, speed, access, and usability.

Day 5: Publication and workplace dashboard application

• Executive dashboard storytelling and management meeting workflows
• Report templates, reusable components, and brand-consistent design
• KPI commentary, annotations, and action-oriented insight prompts
• Dashboard release checklists and stakeholder acceptance criteria
• Embedding reports and selecting secure sharing methods
• Monitoring adoption, feedback, and report change requests
• Personal dashboard implementation planning and peer review

Workshop: Participants complete and present a publish-ready performance dashboard package, including KPI definitions, test results, sharing approach, and a 30-day implementation plan.

Tools & standards covered

Google Looker Studio, Google BigQuery, Google Analytics 4, Google Sheets

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions