Course Introduction
Google Sheets and Looker Studio Data Analytics Training Course provides a practical foundation for transforming spreadsheet-based information into structured analysis, interactive dashboards, and decision-ready business insights. Google Sheets provides collaborative spreadsheet capabilities for organizing, cleaning, calculating, filtering, summarizing, and visualizing data, while Data Studio, formerly known as Looker Studio, provides customizable reports and dashboards that can connect to spreadsheets and other data sources.
The course is designed for professionals who need to analyze operational, financial, sales, marketing, customer, project, or performance data without relying exclusively on specialized programming environments. Participants learn how to structure raw datasets correctly, apply formulas and functions, clean inconsistent information, create reusable analytical calculations, summarize records with pivot tables, and develop meaningful charts. Google Sheets includes analytical capabilities such as FILTER, QUERY, SORTN, SPARKLINE, IMPORTRANGE, pivot tables, and charting tools that can support increasingly sophisticated spreadsheet-based analysis.
A major focus of the training is moving from spreadsheet calculations to systematic data analytics. Participants learn how to distinguish dimensions from measures, establish consistent field definitions, create calculated metrics, manage dates and categories, analyze trends, and build summary tables that support business questions. The course emphasizes analytical accuracy and maintainability by encouraging structured source data, clearly defined formulas, controlled transformations, and reusable reporting logic rather than disconnected manual calculations.
The Data Studio component of the course develops practical dashboard-development skills using connected data sources, calculated fields, filters, charts, tables, scorecards, and interactive controls. Google documentation describes data sources as the layer that connects external data such as Google Sheets to reports while providing structured dimensions, metrics, calculated fields, and other modeling capabilities. This allows analysts to turn spreadsheet data into reusable reporting models rather than recreating calculations independently in every visualization.
Participants also learn advanced analytical techniques for creating business-ready dashboards. Data Studio supports calculated fields that can create new metrics and dimensions using mathematical, text, date, logical, and other functions. Calculated fields can be created at the data-source level for reuse across reports or at the chart level for analysis specific to an individual visualization. The course therefore teaches participants how to decide where analytical logic should reside and how to build metrics that remain understandable and maintainable.
By the end of the course, participants will be able to take a realistic business dataset from raw spreadsheet records through cleaning, transformation, analysis, visualization, and interactive dashboard delivery. The final project combines Google Sheets and Data Studio into an integrated analytics workflow in which participants prepare reliable source data, create analytical calculations, develop meaningful KPIs, build interactive dashboards, apply filters and controls, and communicate findings to decision-makers through clear and accessible reports.
Duration
5 days
Who Should Attend
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Data analysts who use Google Sheets for operational, financial, sales, marketing, or performance analysis.
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Business analysts seeking practical spreadsheet and dashboard development skills.
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Reporting professionals responsible for recurring management reports and performance dashboards.
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Marketing analysts working with campaign, customer acquisition, engagement, and conversion data.
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Sales professionals analyzing revenue, pipeline, customer, product, and sales-performance information.
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Finance professionals developing spreadsheet-based financial analysis, KPIs, forecasts, and management reports.
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Operations analysts working with service delivery, productivity, inventory, logistics, or process-performance data.
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Project managers who need to monitor project activities, budgets, milestones, resources, and performance indicators.
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Small-business professionals who need accessible tools for data analysis and interactive reporting.
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Managers and supervisors who need to interpret analytical dashboards and develop their own business reports.
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Researchers and administrative professionals working with structured datasets and collaborative spreadsheet environments.
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Professionals transitioning from manual spreadsheet reporting toward automated, interactive, and reusable analytics workflows.
Course Objectives
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Build well-structured Google Sheets datasets that provide a reliable foundation for analysis, visualization, reporting, and downstream dashboard development.
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Apply advanced Google Sheets formulas and functions to clean, transform, filter, aggregate, categorize, and analyze business data efficiently.
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Use QUERY, FILTER, SORT, pivot tables, conditional logic, lookups, and other analytical techniques to answer complex business questions.
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Develop accurate KPIs, calculated metrics, summary tables, and analytical measures that clearly represent business performance and trends.
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Create effective spreadsheet-based charts and visual summaries that communicate patterns, comparisons, distributions, trends, and exceptions.
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Connect Google Sheets datasets to Data Studio and configure data sources with appropriate dimensions, metrics, field types, and analytical definitions.
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Build reusable calculated fields in Data Studio to create business metrics, ratios, classifications, date calculations, and other analytical measures.
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Design interactive dashboards using appropriate charts, scorecards, filters, date controls, tables, and other report components for different audiences.
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Apply data-quality, dashboard-design, performance, sharing, and governance practices that improve reliability and usability of analytical reports.
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Complete an end-to-end analytics project that transforms raw Google Sheets data into a professional, interactive, decision-ready Data Studio dashboard.
Comprehensive Course Outline
Module 1: Google Sheets for Modern Data Analytics
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Understanding the role of Google Sheets in collaborative data analysis, reporting, business intelligence, and lightweight analytical workflows.
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Designing structured datasets with appropriate headers, records, data types, identifiers, dates, categories, and measures for reliable downstream analysis.
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Navigating spreadsheet workbooks, worksheets, ranges, named ranges, filters, sorting, formatting, data validation, and collaborative editing features.
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Establishing spreadsheet organization standards that reduce manual errors and make analytical datasets easier to maintain, audit, and connect to reporting tools.
Module 2: Data Cleaning and Preparation in Google Sheets
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Identifying missing values, duplicate records, inconsistent categories, incorrect data types, malformed dates, unexpected values, and other common spreadsheet-quality problems.
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Applying formulas and spreadsheet functions to standardize text, clean values, transform dates, classify records, and prepare datasets for analysis.
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Using filters, filter views, sorting, conditional formatting, data validation, and structured ranges to identify and control data-quality issues.
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Building repeatable data-preparation workflows that separate raw source information from transformed analytical datasets and reporting outputs.
Module 3: Advanced Google Sheets Formulas and Functions
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Applying logical, mathematical, statistical, text, date, lookup, and array-oriented functions to develop sophisticated analytical calculations.
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Using QUERY to select, filter, group, pivot, and order spreadsheet data using Google Visualization API Query Language syntax.
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Combining FILTER, SORT, SORTN, UNIQUE, ARRAYFORMULA, lookup functions, and conditional logic to create flexible analytical workflows.
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Developing formula structures that remain readable, maintainable, efficient, and reusable as datasets grow and business requirements change.
Module 4: Pivot Tables, Summaries, and Spreadsheet Analytics
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Creating pivot tables to summarize dimensions, measures, categories, time periods, and performance indicators across large spreadsheet datasets.
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Applying rows, columns, values, filters, and aggregation settings to answer business questions without manually constructing extensive summary formulas.
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Building analytical summaries for sales, finance, marketing, customers, operations, inventory, projects, and other common business scenarios.
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Combining pivot tables, formulas, charts, conditional formatting, and supporting calculations to create practical spreadsheet-based analytical reports.
Module 5: Spreadsheet Visualization and KPI Development
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Selecting appropriate chart types for trends, comparisons, distributions, rankings, proportions, and other analytical questions within Google Sheets.
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Designing KPI calculations for revenue, growth, conversion, productivity, customer performance, costs, margins, targets, and operational measures.
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Using conditional formatting, sparklines, summary tables, and visual indicators to highlight important changes, exceptions, and performance patterns.
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Developing spreadsheet-based analytical summaries that provide a clear transition from detailed source data to executive-level reporting requirements.
Module 6: Connecting Google Sheets to Data Studio
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Connecting Google Sheets data sources to Data Studio and understanding how spreadsheet fields become dimensions and metrics within reports.
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Configuring field names, data types, aggregations, date settings, and other data-source properties to support accurate dashboard calculations.
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Understanding the distinction between source data, data sources, reports, charts, dimensions, metrics, and calculated fields in the Data Studio architecture.
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Designing source spreadsheets specifically for dashboard consumption by applying consistent schemas, field definitions, identifiers, and analytical structures.
Module 7: Calculated Fields and Advanced Data Modeling
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Creating calculated fields that derive new dimensions and metrics from existing fields using arithmetic, text, date, aggregation, and logical functions.
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Understanding when to create calculations at the data-source level for reuse and when to create chart-specific calculations for localized analytical requirements.
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Developing ratios, percentages, margins, growth measures, classifications, conditional metrics, and other business calculations for dashboard analysis.
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Applying data modeling concepts involving dimensions, metrics, filters, aggregation, calculated fields, and parameters to improve the consistency of analytical reports.
Module 8: Interactive Dashboard Design and Reporting
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Designing professional dashboards using scorecards, tables, pivot tables, charts, controls, filters, date-range controls, and other available reporting components.
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Applying visual hierarchy, spacing, consistent formatting, meaningful titles, clear labels, and appropriate chart selection to improve dashboard comprehension.
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Creating interactive reports that allow viewers to filter information, investigate trends, compare segments, and explore business performance without editing source data.
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Developing dashboard layouts for executives, managers, analysts, marketing teams, sales teams, finance departments, and operational stakeholders with different information needs.
Module 9: Dashboard Optimization, Sharing, and Governance
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Diagnosing calculation errors, incorrect aggregations, mismatched data types, missing fields, unexpected filters, and other common spreadsheet-to-dashboard reporting problems.
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Improving dashboard performance and usability by reducing unnecessary calculations, simplifying source structures, controlling visual complexity, and applying appropriate data models.
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Applying practical sharing and access considerations when distributing dashboards and spreadsheet data to internal teams, external stakeholders, or management audiences.
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Establishing documentation and governance practices for data definitions, KPI formulas, dashboard ownership, refresh expectations, source-data quality, and report maintenance.
Module 10: End-to-End Google Sheets and Data Studio Analytics Project
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Designing a complete analytical workflow beginning with raw Google Sheets data and progressing through cleaning, transformation, KPI development, analysis, and visualization.
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Building a structured data source and configuring dimensions, metrics, calculated fields, filters, aggregation rules, and other modeling requirements for dashboard delivery.
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Creating an interactive management dashboard that combines KPIs, trends, comparisons, detailed tables, filters, and analytical controls appropriate to the selected business scenario.
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Presenting the final project and demonstrating how Google Sheets and Data Studio can support repeatable, collaborative, accessible, and decision-focused data analytics.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
