Excel Data Analysis and Visualisation Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Financial Analyst, Business Analyst and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-DA-108

Before you join: Participants should be confident entering formulas, formatting worksheets, sorting and filtering lists, and creating basic charts in Microsoft Excel.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Teams in finance, operations, HR, procurement, programme delivery and customer service regularly receive large spreadsheet extracts but struggle to turn them into reliable management evidence. Manual copying, inconsistent formulas, weak data checks and poorly chosen charts can produce reports that look credible while masking duplicate records, incorrect joins, misleading comparisons or unexplained variances. Excel remains a practical analysis environment when data preparation, calculation logic and reporting controls are applied consistently.

This course develops the analytical methods needed to prepare data, analyse performance and communicate findings in Microsoft Excel. Participants work with Excel Tables, advanced formulas, Power Query, PivotTables, PivotCharts, Power Pivot, basic DAX measures, descriptive statistics, forecasting methods and dashboard design. They learn to structure source data, validate calculations, combine files, investigate exceptions, model scenarios and select visual forms that answer specific management questions. The course also addresses documentation, workbook protection, peer review and refresh procedures for recurring reports.

Teaching combines concise instructor briefings with guided case work, group analysis and individual workbook development. Cases reflect common reporting problems such as monthly budget variance, customer-service performance, procurement spend, grant delivery and operational demand forecasting. Participants leave with a reusable Excel analysis workbook containing a documented data-preparation process, calculation model, PivotTable report, forecast view and management dashboard. The course is particularly suitable for professionals who already use Excel regularly and need a more disciplined approach to converting operational data into decisions.

What you will be able to do

  • Prepare repeatable analytical datasets using Excel Tables and Power Query transformations
  • Apply advanced formulas to classify, aggregate, retrieve and validate business data
  • Build PivotTable reports with calculated measures, grouping, slicers and timelines
  • Create relational data models using fact tables, dimensions and Power Pivot relationships
  • Analyse distributions, correlations, outliers and trends using Excel statistical techniques
  • Develop forecasts and sensitivity models using moving averages, FORECAST.ETS and Data Tables
  • Design management dashboards using KPIs, PivotCharts, conditional formatting and visual hierarchy
  • Document, review and protect analytical workbooks using defined quality-control procedures

Benefits of attending

For you

  • Produce repeatable reports from raw exports rather than manually rebuilt spreadsheets
  • Diagnose formula, data-quality and relationship errors before reports are circulated
  • Present analysis through charts and dashboards that support management decisions
  • Reduce time spent updating recurring reports through queries, models and refresh procedures
  • Build a portfolio-quality Excel workbook for operational, financial or programme analysis

For your organisation

  • Faster production of monthly reporting from controlled, refreshable data processes
  • Fewer reporting errors caused by manual consolidation and unverified formulas
  • More consistent KPI definitions across finance, operations and programme teams
  • Clearer identification of service exceptions, cost drivers and performance trends
  • Better auditability through documented sources, assumptions, checks and workbook ownership

Course modules

10 modules over 5 days

Participants can structure analytical workbooks and check data quality before analysis begins.

  • Analytical questions translated into measures, dimensions, time periods and decision criteria
  • Excel Tables structured with meaningful names, data types and calculated columns
  • Data quality checks identify blanks, duplicates, invalid codes and outliers
  • Relative, absolute and mixed references applied to reusable analytical formulas
  • IF, IFS and SWITCH formulas classify records against stated business rules
  • Formula auditing traces precedents, dependents, errors and inconsistent calculations

Participants can use advanced Excel formulas to calculate, retrieve and standardise analytical data.

  • SUMIFS, COUNTIFS and AVERAGEIFS aggregate measures using multiple criteria
  • XLOOKUP and INDEX-MATCH retrieve attributes from controlled reference tables
  • Text functions standardise codes, names, dates and imported identifiers
  • Date functions calculate ageing, working days, month-end and reporting periods
  • Dynamic arrays use FILTER, SORT, UNIQUE and SEQUENCE for live outputs
  • LET formulas reduce repetition and expose calculation logic for review

Participants can create repeatable Power Query processes for importing and transforming source data.

  • Power Query imports CSV, workbook, folder and database extracts
  • Query steps set data types, remove errors and preserve source fields
  • Split, merge and replace operations standardise inconsistent transactional values
  • Append queries combine monthly files into a controlled reporting dataset
  • Merge queries join master data using verified key fields
  • Refresh settings maintain repeatable data preparation without manual rework

Participants can build interactive PivotTable reports and investigate performance exceptions.

  • PivotTables summarise revenue, cost, volume and service measures rapidly
  • Field placement distinguishes measures, categories, filters and reporting hierarchies
  • Grouping creates months, quarters, bands and management reporting ranges
  • Slicers and timelines filter reports through visible, controlled selections
  • Show Values As calculates shares, variances, rankings and running totals
  • Drill-down extracts supporting records for exception investigation and audit trails
  • PivotTable layouts improve readability with subtotals, labels and number formats

Participants can build Excel data models that combine related datasets without duplicating totals.

  • Power Pivot data models connect fact tables with shared dimensions
  • One-to-many relationships prevent duplicated totals across linked operational datasets
  • Star schema design separates transactions, dimensions and measures for analysis
  • Data Model measures use DAX SUM, CALCULATE and DISTINCTCOUNT expressions
  • Calendar tables support period comparisons and consistent time-based reporting
  • Relationship checks expose unmatched keys and ambiguous reporting logic

Participants can apply descriptive statistical methods and interpret findings with appropriate caution.

  • Descriptive statistics quantify central tendency, spread, distribution and unusual observations
  • Histograms and box plots reveal skew, variation and potential outliers
  • Correlation analysis distinguishes association from causation in business datasets
  • Scatter charts assess relationships between drivers, outcomes and data quality
  • Percentiles and quartiles establish service thresholds and performance benchmarks
  • Sampling considerations identify bias, population limits and unreliable conclusions
  • Trendlines report fit, equation and R-squared without overstating certainty

Participants can build forecasts and test the effect of changing business assumptions.

  • Time-series charts separate trend, seasonality, volatility and exceptional events
  • Moving averages smooth operational demand data for short-term forecasting
  • FORECAST.ETS generates seasonal projections with confidence intervals
  • Forecast accuracy uses actual-versus-forecast variance, MAD and MAPE
  • Scenario inputs model price, volume, staffing and exchange-rate assumptions
  • Data Tables test one-variable and two-variable sensitivity ranges
  • Goal Seek solves target margin, volume or budget constraints

Participants can select and construct Excel visuals that communicate analytical findings accurately.

  • Chart selection matches comparison, composition, distribution, relationship and trend questions
  • Bar, line, scatter and waterfall charts communicate distinct analytical messages
  • Titles, labels and annotations state the decision-relevant finding directly
  • Axis scales, baselines and units prevent misleading visual interpretation
  • Conditional formatting highlights exceptions through rules, data bars and icon sets
  • Small multiples compare business units without overloading a single chart
  • Accessible colour choices distinguish categories while retaining grayscale readability

Participants can design controlled Excel dashboards for recurring management reporting.

  • Dashboard requirements define audience, decisions, refresh frequency and success measures
  • KPI cards present actuals, targets, variance and directional status
  • Linked PivotTables and PivotCharts create interactive management reporting views
  • Layout grids establish visual hierarchy, alignment and consistent reading paths
  • Controlled input cells separate assumptions from formulas and displayed results
  • Protection settings secure formulas, worksheet structure and approved user inputs
  • Dashboard testing verifies filters, calculations, labels and refresh behaviour

Participants can review, document and plan the deployment of reliable Excel analysis workbooks.

  • Reconciliation checks compare source totals, query outputs and dashboard measures
  • Documentation records sources, transformations, assumptions, owners and refresh procedures
  • Version control conventions distinguish draft, reviewed and approved workbooks
  • Peer review checklists test formulas, logic, visuals and decision claims
  • Workbook performance techniques reduce recalculation delays and unnecessary file size
  • An individual application plan defines a workplace analysis and stakeholders

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Excel data-quality checklist
  2. Power Query transformation template
  3. Advanced formula reference model
  4. PivotTable and PivotChart reporting template
  5. Forecast and sensitivity analysis model
  6. Management dashboard design checklist

Who should attend

  • Financial Analyst — needs reliable variance analysis, forecasts and management reporting
  • Business Analyst — needs structured methods for converting extracts into decision evidence
  • Operations Manager — needs clearer performance measures, exception reporting and demand analysis
  • Monitoring and Evaluation Officer — needs consistent reporting from programme and beneficiary data
  • Procurement Specialist — needs spend analysis, supplier comparisons and category reporting
  • Project Manager — needs practical dashboards for delivery milestones, resources and risks

Skills and tools covered

Excel data preparationFormula-based analysisPivotTable reportingData modellingStatistical analysisDashboard design

Tools and standards

Excel Tables, Power Query, PivotTables, Power Pivot and DAX

How the course runs

Training methodology

The course uses short technical briefings followed by guided analysis of realistic spreadsheet datasets. Participants prepare and combine extracts, build formulas and PivotTable reports, test relationships, interpret statistical outputs, create forecasts and assemble dashboards. Group discussions examine chart choice, reporting controls and decision claims. Trainers use financial, operational, procurement and service-reporting cases, adapting examples to the cohort where appropriate. Individual application planning helps participants identify a recurring workplace report that can be redesigned using the methods covered.

Requirements and prerequisites

Participants should be confident entering formulas, formatting worksheets, sorting and filtering lists, and creating basic charts in Microsoft Excel. Experience working with business data such as transactions, budgets, customer records, survey results or operational logs is assumed. Participants should understand common measures such as totals, percentages, averages and variances. Prior use of PivotTables is useful but not essential. Programming, database administration, statistics qualifications, VBA and Power BI experience are not required. Participants should bring a laptop with a current desktop version of Excel where possible.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

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

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should already be comfortable with basic formulas, sorting, filtering, formatting and simple charts. The course begins with workbook structure and data checks, then progresses to advanced formulas, Power Query, PivotTables and dashboards.

Bring a laptop with a current desktop version of Microsoft Excel if possible. Excel for Microsoft 365 is preferred because it includes Power Query, dynamic arrays and current data-model features.

It suits professionals who analyse business, financial, operational, programme, procurement or service data in Excel. It is intended for regular Excel users who need more reliable methods for recurring analysis and reporting.

Basic Excel courses focus on worksheet skills such as formatting, simple formulas and charts. This course focuses on analytical workflow, repeatable data preparation, PivotTable reporting, modelling, forecasting and dashboard design within Excel; it does not teach Power BI report development.

Participants can redesign a recurring report such as a budget variance pack, procurement spend report, service-performance dashboard or programme tracker. The course includes application planning, quality checks and documentation methods for transferring the approach to workplace data.

Each training day runs from 08:30 to 16:30 and includes about 6.5 contact hours, with time for breaks and lunch. The five days move from data structure and formulas through preparation, reporting, modelling, forecasting, visualisation and workbook quality control.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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