Data Visualization Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Data Analysts, Business Intelligence Analysts and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 7 Nov 2026 Course code SD-DA-049

Before you join: Participants should be comfortable reading tables, percentages, averages and basic charts, and should have experience working with spreadsheets, reports, dashboards or business data.

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

Business decisions often depend on reports and dashboards that are difficult to read, poorly matched to the question, or misleading through weak chart choices. Analysts may have accurate data but still fail to show the trend, comparison, exception or risk that decision-makers need. This course addresses the practical work of turning data into clear, defensible visual communication for management reporting, operational monitoring, policy analysis and customer insight.

Participants learn to define the decision question, assess the audience, prepare data for display and select chart forms that fit the analytical task. The course covers comparisons, distributions, relationships, composition, time series and geospatial data; visual encoding; colour and layout; dashboard design; data storytelling; accessibility; uncertainty; and visual quality assurance. Participants apply principles from Gestalt theory, WCAG 2.2 guidance and IBCS notation principles while working with common reporting tools including Excel, Power BI and Tableau.

Instruction combines short practitioner briefings, annotated examples, case work and group critique of reports drawn from banking, public services, NGOs and corporate operations. Participants produce a visualisation design brief, chart selection matrix, dashboard wireframe and quality checklist that can be adapted to their own reporting work. The five-day course is available as classroom training in more than 50 cities or live online. Training runs from 08:30 to 16:30 each day, providing approximately 6.5 contact hours daily. Participants receive a certificate of completion.

The course is suited to professionals who already work with data, reports or performance measures and need to present findings with greater clarity, accuracy and decision relevance.

What you will be able to do

  • Define decision-focused visualisation requirements using audience and question briefs
  • Profile data grain, measures, dimensions, quality issues and calculation assumptions
  • Select appropriate chart types using comparison, distribution, composition and relationship questions
  • Apply visual encoding principles for position, length, colour, size, labels and scales
  • Design accessible dashboards using hierarchy, KPI definitions, filters and interaction rules
  • Construct data narratives using message-first storyboards, annotations and recommended actions
  • Evaluate charts for misleading scales, uncertainty, privacy, accessibility and source traceability
  • Create a workplace visualisation improvement plan with review and publication controls

Benefits of attending

For you

  • Produces clearer management reports and dashboards with defensible chart choices
  • Explains analytical findings to non-technical stakeholders with greater precision
  • Identifies misleading charts, weak scales and unsupported visual claims
  • Builds a reusable process for reviewing visual quality before publication
  • Creates portfolio-ready dashboard wireframes and visualisation design materials

For your organisation

  • Improves decision speed through reports focused on actions, exceptions and trends
  • Reduces reporting errors caused by misleading scales, unclear labels and weak denominators
  • Establishes more consistent dashboard standards across teams and functions
  • Strengthens accessibility and readability of internal and external reporting
  • Provides traceable visual reporting supported by source notes and quality checks

Course modules

10 modules over 5 days

Participants can define a visualisation brief that connects audience needs to a decision question.

  • Decision questions, audiences and actions defined before selecting visual forms
  • Analytical, explanatory and exploratory views matched to stakeholder needs
  • Information density balanced against attention, time and decision risk
  • Chart purpose statements written using question, measure, comparison and action
  • Audience literacy assessed through role, context, urgency and data familiarity
  • Visualisation requirements captured in a concise design brief

Participants can assess whether data is suitable for accurate visual communication.

  • Data grain, unit of analysis and aggregation levels identified
  • Data types classified: categorical, ordinal, temporal, quantitative and geospatial
  • Missing values, duplicates and outliers profiled before chart construction
  • Calculated measures documented with numerator, denominator, filters and time basis
  • Data dictionaries record field definitions, owners, refresh dates and caveats
  • Source-to-visual traceability checked using reconciliation totals and sample records

Participants can choose chart forms that answer a defined analytical question.

  • Comparison, distribution, composition and relationship questions mapped to chart families
  • Bar, line, scatter and histogram charts selected by data structure
  • Part-to-whole displays tested against denominator stability and category count
  • Small multiples reveal subgroup patterns without overloaded single charts
  • Tables retained when exact values matter more than visual pattern
  • Chart selection matrix documents purpose, encodings, limitations and alternatives

Participants can apply perceptual principles to make charts easier to interpret accurately.

  • Marks and channels assigned using position, length, colour, size and shape
  • Gestalt proximity, similarity and enclosure direct attention to related values
  • Pre-attentive attributes used sparingly to signal priority, exception and change
  • Ordinal and categorical colour scales matched to data semantics
  • Axis baselines, intervals and aspect ratios checked for honest comparison
  • Direct labels reduce legend scanning and decoding errors

Participants can design readable, accessible visual reports for intended viewing conditions.

  • Visual hierarchy established through layout, whitespace, contrast and annotation
  • WCAG 2.2 contrast guidance applied to text, marks and backgrounds
  • Colour-blind-safe palettes tested with redundant labels and patterns
  • Titles state the finding, comparison period and relevant population
  • Annotation layers distinguish facts, interpretation, assumptions and source notes
  • Mobile and projected displays assessed for legibility at realistic viewing distances

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

  • Dashboard objectives converted into measurable user tasks and decision paths
  • Single-screen layouts group overview, diagnosis and action-oriented detail
  • KPI cards specify metric definition, target, period and comparison basis
  • Filters, slicers and drill-through interactions constrained to useful questions
  • Information hierarchy separates primary signals from supporting context
  • Dashboard wireframes document layout, interactions, refresh cadence and ownership

Participants can structure visual evidence into concise decision-focused narratives.

  • Data narratives connect context, evidence, implication and recommended action
  • Message-first storyboards sequence claims before chart production begins
  • Annotations identify inflection points, drivers, uncertainty and decision thresholds
  • Before-and-after comparisons show change without concealing baseline conditions
  • Executive briefings distinguish observed facts from proposed interpretations
  • Callouts frame decisions, owners, deadlines and follow-up measures

Participants can identify and correct visual practices that misstate evidence or create risk.

  • Sampling error, confidence intervals and uncertainty bands displayed appropriately
  • Truncated axes, dual axes and area distortions detected and corrected
  • Rates, counts and percentages contextualised with denominators and population sizes
  • Data suppression rules protect small groups and confidential records
  • Accessibility and inclusive language considered when labelling sensitive populations
  • Source, transformation and refresh notes support auditability and trust

Participants can use common reporting tool features to implement sound visual design choices.

  • Excel tables, PivotCharts and conditional formatting support rapid exploratory views
  • Power BI visuals use fields, filters, tooltips and report pages
  • Tableau worksheets apply shelves, marks cards, filters and calculated fields
  • Calculated fields separate presentation logic from source data transformations
  • Export settings preserve readable labels, fonts and contrast in PDF
  • Tool choice considers governance, refresh, sharing and audience access

Participants can review visual outputs systematically and plan improvements for a workplace report.

  • Visual QA checks data accuracy, encoding, labels, accessibility and interpretation
  • Peer review uses a structured critique against stated decision questions
  • Publication checklists confirm source notes, permissions, privacy and version control
  • Stakeholder feedback distinguishes preference comments from decision-critical defects
  • Revision logs record changes, rationale, approver and release date
  • Application plan identifies a workplace report, audience and delivery milestone

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

What you take back to work

  1. Visualisation design brief template
  2. Chart selection matrix
  3. Dashboard wireframe template
  4. Data storytelling storyboard
  5. Visual quality assurance checklist
  6. Workplace visualisation application plan

Who should attend

  • Data Analysts — need to turn analysis into clear decision-ready reports
  • Business Intelligence Analysts — design dashboards used for operational and management reporting
  • Performance Managers — communicate KPIs, trends and exceptions to senior stakeholders
  • Financial Analysts — present budgets, forecasts and variance analysis without visual distortion
  • Monitoring and Evaluation Officers — report programme indicators, outcomes and data limitations clearly
  • Policy Analysts — explain evidence, comparisons and uncertainty to non-technical decision-makers

Skills and tools covered

Visual requirements analysisChart selectionDashboard designData storytellingVisual accessibilityVisual quality assurance

Tools and standards

Excel, Power BI, Tableau, WCAG 2.2

How the course runs

Training methodology

The course uses short instructor briefings followed by worked examples, case analysis, group exercises and structured critique. Participants examine operational dashboards, financial reports, programme indicator packs and executive presentations to diagnose chart selection, hierarchy, accessibility and interpretation issues. Trainers demonstrate methods in Excel, Power BI and Tableau where appropriate, while keeping core principles transferable between tools. Participants develop application plans for a real reporting need and receive feedback against decision relevance, visual accuracy and publication quality.

Requirements and prerequisites

Participants should be comfortable reading tables, percentages, averages and basic charts, and should have experience working with spreadsheets, reports, dashboards or business data. Familiarity with Excel, Power BI or Tableau is useful but not essential; the course explains transferable design principles rather than assuming advanced software expertise. Participants should bring awareness of one or two reporting tasks from their workplace. Programming, statistics beyond basic descriptive measures, database design and prior graphic design training are not required.

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 reading basic charts, tables, percentages and averages. Experience with reports, spreadsheets or dashboards is expected, but advanced statistics, coding and graphic design experience are not required.

Bring a laptop if attending in person, along with examples of reports or dashboards you would like to improve. You do not need to bring confidential data; anonymised examples or descriptions of reporting problems are sufficient.

The course is designed for analysts, reporting specialists, performance managers, finance professionals, monitoring and evaluation staff, and policy professionals. It is most useful for people who already work with data and need to communicate findings to others.

This course focuses on visual reasoning, chart choice, communication, accessibility and quality assurance rather than detailed software operation. Demonstrations use common tools, but the methods apply whether your team uses Excel, Power BI, Tableau or another reporting platform.

Participants leave with templates and review methods that can be used on recurring reports, executive packs and dashboards. The final module helps participants identify a specific workplace report and define practical improvements, stakeholders and a delivery milestone.

Each day runs from 08:30 to 16:30 and provides approximately 6.5 contact hours. The course progresses from requirements and data readiness through chart design, dashboards, storytelling, responsible presentation and visual quality assurance.

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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