Data Visualisation and Reporting Training Course

Duration 10 days 16 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Data Analysts, Business Intelligence Analysts and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-DA-065

Before you join: Participants should be comfortable working with spreadsheets, tables, filters and basic formulas, and should have experience reading business, operational, financial or programme reports.

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

Many reports contain correct figures but still fail to support decisions. Readers struggle to identify the main message, compare performance, understand change over time or spot material exceptions. Poor chart selection, inconsistent definitions, crowded dashboards and unclear commentary can lead senior leaders, regulators and operational teams to act on partial or misleading evidence. Data visualisation is therefore a reporting discipline, not a formatting task.

This course develops the methods needed to turn operational, financial, customer, programme and risk data into clear visual reports. Participants learn to define reporting questions, assess data quality, select suitable chart forms, apply visual perception principles, build informative dashboards and write decision-focused commentary. The syllabus covers data preparation in Excel and Power BI, infographic design, KPI design, statistical charting, geospatial displays, accessibility, dashboard governance and reporting controls.

Participants work with realistic reporting cases such as branch performance, public-service delivery, fraud monitoring, project portfolios, sales pipelines and NGO programme indicators. They create report components from the first week, then improve them through peer review and stakeholder testing. Each participant leaves with a completed reporting product, supported by a KPI dictionary, chart-selection rationale, dashboard wireframe and quality-control checklist that can be adapted for their own workplace.

The course suits professionals who prepare, review or commission management information and need reports that enable timely, defensible action. It is particularly relevant where reporting must serve both specialist analysts and non-technical decision-makers.

What you will be able to do

  • Define reporting questions, decisions and audience needs using a reporting brief
  • Assess dataset fitness through profiling, reconciliation and data-quality checks
  • Select chart types using task-based chart-selection principles
  • Build Excel and Power BI visualisations with accurate scales and labels
  • Design KPI frameworks, metric definitions and exception thresholds
  • Create dashboard wireframes using visual hierarchy and information architecture
  • Write analytical commentary that links evidence, implications and recommended actions
  • Present a complete data story with documented controls and stakeholder feedback

Benefits of attending

For you

  • Produce reports that make priority actions visible within minutes
  • Explain chart choices and metric definitions with professional confidence
  • Reduce rework caused by unclear briefs and inconsistent reporting requests
  • Build a portfolio-quality dashboard and reporting case for career progression
  • Review supplier, analyst and team outputs using defined visual standards

For your organisation

  • Faster management decisions through clearer performance and exception reporting
  • Fewer reporting disputes through documented metric definitions and source checks
  • More consistent dashboards across business units, programmes and functions
  • Improved detection of trends, outliers and emerging operational risks
  • Reduced manual reporting effort through reusable templates and review controls

Course modules

16 modules over 10 days

Participants can frame a reporting assignment around audience decisions, questions and evidence needs.

  • Decision-led reporting briefs linking users, decisions, measures and reporting cadence
  • Primary and secondary audiences mapped through stakeholder analysis
  • Management information questions separated from routine data requests
  • SMART reporting objectives written for specific decisions and actions
  • Reporting cadence matched to operational, tactical and strategic decisions
  • Evidence hierarchies distinguishing indicators, analysis, narrative and recommendations

Participants can assess whether source data is fit for a stated reporting purpose.

  • Data profiling checks for completeness, uniqueness, validity and consistency
  • Reconciliation of source totals against approved operational or financial records
  • Missing-value treatment documented using explicit reporting rules and assumptions
  • Outliers investigated through distribution checks, business context and source tracing
  • Data lineage recorded from source system through transformation to report
  • Quality thresholds defined for publication, escalation and corrective action

Participants can define measurable KPIs with clear calculation, ownership and interpretation rules.

  • KPI trees connecting strategic objectives, drivers, outcomes and measures
  • Leading and lagging indicators distinguished for performance management
  • Metric definitions specify formula, grain, source, owner and refresh frequency
  • Numerators and denominators tested for meaningful rate calculations
  • Targets, baselines and thresholds set using historical and policy evidence
  • Metric dictionaries prevent conflicting interpretations across report users

Participants can apply visual perception principles to make data easier to interpret accurately.

  • Preattentive attributes direct attention through position, length, colour and size
  • Gestalt principles organise related values without unnecessary chart decoration
  • Visual hierarchy established through layout, contrast, grouping and whitespace
  • Cognitive load reduced by removing redundant labels, borders and effects
  • Colour palettes distinguish categories, sequences, divergence and alert states
  • Data-ink ratio applied without removing essential explanatory context

Participants can select and justify chart forms for common analytical questions.

  • Comparison tasks shown with sorted bars, dot plots and lollipop charts
  • Time-series patterns displayed using lines, areas and indexed comparisons
  • Part-to-whole relationships tested before using stacked bars or treemaps
  • Distribution analysis uses histograms, box plots, density plots and strip charts
  • Correlation and clusters investigated with scatterplots, bubble charts and trendlines
  • Chart junk identified through an evidence-based visual review checklist

Participants can prepare structured data and create accurate Excel reporting visuals.

  • Excel Tables establish controlled ranges, field names and refreshable calculations
  • PivotTables summarise transaction data by period, category and owner
  • Calculated fields create rates, variances, shares and period comparisons
  • Conditional formatting flags exceptions using threshold and ranking rules
  • Sparklines show compact trends beside operational performance measures
  • Dynamic chart ranges update visual outputs as reporting data changes

Participants can communicate actual performance, variance drivers and forecast scenarios clearly.

  • Variance bridges explain movement between budget, actual and forecast values
  • Waterfall charts isolate positive and negative contributors to change
  • Run charts distinguish common-cause variation from special-cause signals
  • Rolling averages smooth volatile patterns while retaining underlying observations
  • Forecast bands communicate uncertainty through ranges, assumptions and scenarios
  • Period comparisons control for seasonality, calendar effects and base sizes

Participants can build a simple Power BI report from prepared relational data.

  • Star schema separates fact tables, dimensions and descriptive attributes
  • Power Query applies repeatable cleaning, typing and transformation steps
  • Relationships checked for cardinality, filter direction and ambiguous paths
  • DAX measures calculate totals, ratios, variances and time intelligence
  • Report pages organise summary, diagnostic and detailed analytical views
  • Slicers and drillthrough support controlled exploration without visual clutter

Participants can design dashboard structures that support scanning, diagnosis and action.

  • Dashboard purpose defined as monitoring, analysis, planning or accountability
  • F-pattern and Z-pattern layouts guide attention through priority information
  • KPI cards paired with context, trend, target and comparison values
  • Overview-first structure supports drilldown from summary to contributing details
  • Wireframes specify page zones, interactions, filters and annotation requirements
  • Progressive disclosure prevents dense pages from overwhelming report users

Participants can write concise commentary that explains evidence and prompts action.

  • Situation-complication-question-answer structure frames an analytical reporting narrative
  • Headlines state the finding rather than describe the chart
  • Annotations identify inflection points, exceptions, events and decision implications
  • Claim-evidence-reasoning links conclusions to visible and traceable data
  • Recommendation statements assign action, owner, timing and expected result
  • Narrative qualifiers distinguish observed facts, estimates, assumptions and risks

Participants can create single-page infographics that communicate key evidence responsibly.

  • Message hierarchy prioritises one central finding and supporting evidence
  • Pictograms used only when icon counts accurately represent quantities
  • Small multiples compare repeated measures using consistent visual scales
  • Callout statistics retain source, period, unit and denominator details
  • Editorial grids align charts, text blocks, icons and explanatory notes
  • Executive one-pagers balance brevity, evidence, caveats and recommended actions

Participants can choose and interpret location-based visuals without overstating geographic patterns.

  • Choropleth maps normalise counts using population, exposure or service bases
  • Proportional symbols display magnitude without implying false area comparisons
  • Geographic boundaries checked for changes, overlap and reporting consistency
  • Location privacy protected through aggregation, suppression and controlled precision
  • Spatial patterns tested against data quality, coverage and denominator differences
  • Map legends communicate units, classification method and missing-data treatment

Participants can review reports for accessibility, fairness and potential misinterpretation.

  • WCAG 2.2 contrast ratios applied to text, marks and interfaces
  • Colour-blind-safe palettes avoid reliance on colour alone for meaning
  • Alternative text describes purpose, trend, comparison and key exceptions
  • Axis truncation assessed for distortion, emphasis and legitimate analytical purpose
  • Sensitive categories reviewed for disclosure risk, stigma and unfair inference
  • Source notes document provenance, limitations, transformations and update dates

Participants can establish repeatable controls for publishing trusted visual reports.

  • Report production workflows define roles, approvals, deadlines and version control
  • Quality assurance checklists test calculations, labels, filters and refresh dates
  • Peer review separates visual critique from metric and source validation
  • Change logs record definition amendments, fixes and material report revisions
  • Release criteria require owner sign-off, documentation and accessibility checks
  • Dashboard adoption metrics track usage, unanswered questions and improvement requests

Participants can test reporting products with users and prioritise evidence-based improvements.

  • Usability test scripts ask users to find specific decisions and insights
  • Think-aloud sessions reveal ambiguous labels, filters and visual cues
  • Feedback categorised by accuracy, usefulness, usability and presentation quality
  • Prioritisation matrices rank changes by decision impact and implementation effort
  • Before-and-after comparisons test whether redesigned reports improve task completion
  • Reporting backlogs convert feedback into owned, scheduled improvement actions

Participants can build, review and present a complete visual report that answers a defined business decision.

  • Capstone reporting brief defines decision, audience, measures and source data
  • Prepared dataset documented through lineage, profiling and quality findings
  • KPI dictionary records definitions, targets, owners and calculation logic
  • Dashboard or infographic applies justified chart, layout and annotation choices
  • Quality review checks accessibility, accuracy, narrative and publication controls
  • Stakeholder presentation explains findings, limitations, recommendations and next actions

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

What you take back to work

  1. Decision-led reporting brief template
  2. KPI dictionary and metric-definition model
  3. Chart-selection and visual-review checklist
  4. Dashboard wireframe and page architecture template
  5. Data storytelling and commentary framework
  6. Completed capstone visual reporting product

Who should attend

  • Data Analysts — need to convert analysis into decision-ready visual reporting
  • Business Intelligence Analysts — build dashboards and recurring management information
  • Finance Managers — explain performance, variance and forecast evidence clearly
  • Monitoring and Evaluation Officers — communicate programme indicators to funders and leaders
  • Operations Managers — use visual controls to identify service and process exceptions
  • Project Managers — report portfolio progress, risks and delivery milestones credibly

Skills and tools covered

Chart selectionDashboard designKPI reportingData storytellingVisual quality assuranceReporting governance

Tools and standards

Microsoft Excel, Microsoft Power BI, Tableau, WCAG 2.2

How the course runs

Training methodology

Instructor briefings introduce a method, followed by guided analysis of reports from finance, operations, public services and development programmes. Participants critique charts, prepare data, build visual components and test dashboard decisions in pairs and small groups. Short simulations require teams to respond to executive reporting requests, changing definitions and incomplete data. Facilitated reviews focus on evidence, audience needs, accessibility and actionability. Participants apply each stage to a chosen reporting case and receive structured feedback before the final presentation.

Requirements and prerequisites

Participants should be comfortable working with spreadsheets, tables, filters and basic formulas, and should have experience reading business, operational, financial or programme reports. Familiarity with Excel charts is useful but not essential. Participants should be able to interpret percentages, averages, rates and simple comparisons. No programming, statistics degree, prior Power BI or Tableau experience, graphic-design background or advanced mathematics is required. Those attending should bring examples of reporting questions or non-sensitive datasets from their work where organisational policy permits.

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 be comfortable using spreadsheets and interpreting routine business or operational data. Prior Power BI, Tableau, programming and graphic-design experience are not required.

Bring a laptop with Excel and, where possible, Power BI Desktop installed. You may also bring non-sensitive reports, reporting questions or approved sample data from your workplace.

It is designed for analysts, managers, finance staff, programme staff and reporting professionals who create, review or commission reports. It suits people who need to communicate findings to decision-makers rather than only analyse data.

The course uses Excel and Power BI as reporting tools, but its main focus is making defensible visual reporting decisions. It covers audience needs, chart selection, KPI definitions, narrative, accessibility and governance alongside tool use.

You will leave with reusable templates and a completed reporting product that can be adapted to a live reporting requirement. The methods apply to recurring dashboards, board papers, project reports, service-performance packs and donor reporting.

Each day runs from 08:30 to 16:30 and provides about 6.5 contact hours. The first week establishes reporting, visual and tool foundations; the second week develops dashboards, storytelling, controls and the capstone presentation.

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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