Data Science & Analytics · PPL

Data Storytelling & Visualization Certification

A practical program designed to develop skills in data visualization, visual storytelling, dashboard design, and communicating complex insights clearly to business audiences.

  • ⏱3 DaysDuration
  • ◈PPLAccredited
  • ◐3 LanguagesArabic · English · Hindi
  • ◆₹7,499.00 Per delegate

This course is accredited by PPL

This is for all ppl accredited courses
2M+ Delegates trained worldwide
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— The journey

Course Outline

What the programme covers, module by module.

Module 1: Introduction to Data Storytelling

  • Data storytelling fundamentals
  • Data versus information
  • Insights and narratives
  • Business communication
  • Storytelling objectives
  • Data-driven decision-making

Module 2: Fundamentals of Data Visualization

  • Visualization principles
  • Visual perception
  • Data representation
  • Visual hierarchy
  • Clarity and simplicity
  • Effective communication

Module 3: Understanding Your Audience

  • Audience identification
  • Stakeholder expectations
  • Information requirements
  • Technical versus business audiences
  • Communication objectives
  • Audience-focused design

Module 4: Understanding Data Types

  • Categorical data
  • Numerical data
  • Time-series data
  • Geographic data
  • Hierarchical data
  • Relationship data

Module 5: Choosing the Right Chart

  • Bar charts
  • Line charts
  • Scatter plots
  • Histograms
  • Area charts
  • Chart selection principles

Module 6: Advanced Chart Selection

  • Waterfall charts
  • Heatmaps
  • Treemaps
  • Bubble charts
  • Funnel charts
  • Combination charts

Module 7: Visual Design Principles

  • Layout
  • Alignment
  • Spacing
  • Contrast
  • Typography
  • Visual consistency

Module 8: Colour in Data Visualization

  • Colour theory
  • Sequential palettes
  • Diverging palettes
  • Categorical colours
  • Accessibility
  • Highlighting insights

Module 9: Exploratory Data Visualization

  • Data exploration
  • Distribution analysis
  • Trend identification
  • Relationship analysis
  • Outlier detection
  • Pattern discovery

Module 10: Explanatory Data Visualization

  • Insight selection
  • Visual emphasis
  • Annotation
  • Context
  • Simplification
  • Key-message communication

Module 11: Data Storytelling Frameworks

  • Narrative structure
  • Context
  • Conflict and change
  • Insight development
  • Recommendations
  • Story flow

Module 12: Building a Data Narrative

  • Business question
  • Data evidence
  • Key findings
  • Supporting visuals
  • Recommendations
  • Call to action

Module 13: Dashboard Design Fundamentals

  • Dashboard objectives
  • KPI selection
  • Dashboard layouts
  • Information hierarchy
  • Visual organization
  • User experience

Module 14: Interactive Dashboards

  • Filters
  • Slicers
  • Drill-down
  • Drill-through
  • Tooltips
  • Interactive exploration

Module 15: KPI Visualization

  • KPI cards
  • Targets
  • Variance visualization
  • Trend indicators
  • Performance comparisons
  • Executive summaries

Module 16: Visualization with Python

  • Matplotlib fundamentals
  • Data preparation
  • Chart creation
  • Chart customization
  • Analytical visualizations
  • Visualization workflows

Module 17: BI Tools for Data Storytelling

  • Power BI concepts
  • Tableau concepts
  • Dashboard development
  • Interactive reporting
  • Visual analytics
  • Business reporting

Module 18: Presenting Data to Stakeholders

  • Presentation structure
  • Executive communication
  • Explaining visualizations
  • Presenting insights
  • Handling questions
  • Recommendation delivery

Module 19: Avoiding Misleading Visualizations

  • Distorted scales
  • Inappropriate charts
  • Missing context
  • Visual bias
  • Data integrity
  • Transparent communication

Module 20: AI-Assisted Data Storytelling

  • AI-assisted insight generation
  • Narrative summaries
  • Visualization suggestions
  • Automated explanations
  • Presentation assistance
  • Responsible AI usage

Module 21: Data Visualization Best Practices

  • Visual simplicity
  • Consistent formatting
  • Accessibility
  • Data accuracy
  • Story consistency
  • Quality review

Module 22: Practical Data Storytelling Project

  • Business problem definition
  • Data exploration
  • Visualization selection
  • Dashboard development
  • Narrative creation
  • Insight presentation
— 01.2 · Is it right for you?

Who it's for & what's included

Pick a delivery method to see exactly who it suits and everything you receive.

Who it's for

Classroom

Best for learners who want face-to-face tuition and to network with peers in person.

What's included

Everything you get

  • ✓ Live instructor on-site
  • ✓ Printed workbook & materials
  • ✓ Group exercises & case studies
Who it's for

Online Instructor-Led

Best for learners who want a live instructor and a fixed schedule, without the travel.

What's included

Everything you get

  • ✓ Live instructor via video call
  • ✓ Digital workbook & resources
  • ✓ Session recordings
Who it's for

Self-Paced

Best for self-motivated learners who need maximum flexibility around work and life.

What's included

Everything you get

  • ✓ On-demand video lessons
  • ✓ Interactive quizzes
  • ✓ 24/7 access on any device
— What you will master

Course Objectives

01

Understand the principles of effective data storytelling and visualization.

02

Select appropriate charts and visual formats for different types of data.

03

Apply visual design principles to create clear and engaging visualizations.

04

Transform analytical findings into structured and compelling data narratives.

05

Design interactive dashboards that communicate business performance effectively.

06

Present complex analytical insights clearly to technical and non-technical stakeholders.

07

Identify and avoid misleading or ineffective visualization practices.

08

Apply visualization and storytelling techniques to practical business scenarios.

— Your learning path

Where this fits in your Data Science & Analytics journey

Click any stage to open its detail page. You are at Data Storytelling & Visualization Certification.

Start Build Advanced Mastery
— Questions answered

Frequently Asked Questions

What is Data Storytelling?
Data storytelling combines data, visualizations, and narrative techniques to communicate insights clearly and help audiences understand important findings and decisions.
Who should attend this course?
The course is suitable for data analysts, business analysts, data scientists, BI professionals, reporting professionals, and working professionals who communicate data-driven insights.
Do I need previous data visualization experience?
No. The program begins with visualization fundamentals before progressing to dashboards, storytelling frameworks, interactive reporting, and stakeholder presentations.
Which tools are covered?
The course introduces visualization workflows using Python and explores practical business intelligence concepts using tools such as Power BI and Tableau.
What practical skills will I develop?
You will develop skills in chart selection, visual design, dashboard development, data storytelling, KPI visualization, stakeholder communication, and presenting actionable insights.
— Trusted by learners

What our delegates say

★★★★★

"The structure, the practice exams, the instructor — all top tier. Passed first try."

AS
Aarti SharmaSenior Project Manager · TCS
★★★★★

"Best training I have attended. The content is exactly what modern projects need."

JD
James DonovanProgramme Director · Capgemini
★★★★★

"24/7 support actually means 24/7 — got help on my mock exam at 2am. Worth every dollar."

MO
Maya OkaforPMO Lead · Standard Bank

★ 4.8 / 5 from 12,000+ verified learner reviews on Trustpilot & Google.

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