Data Analytics & Business Intelligence
| Location | Duration | Kenyan Cost | Non-Kenyan Cost | Upcoming Schedules |
|---|---|---|---|---|
| Nairobi, Kenya | 5 Days | KES 100,000 | USD 1,300 |
| Location | Duration | Non-Kenyan Cost | Register |
|---|---|---|---|
| Online | 5 Days | USD 550 |
| Register |
|---|
Data Analytics & Business Intelligence
About the Course
This course equips professionals with the skills to collect, analyse, and interpret data to support
informed business decision-making. Participants will explore the data analytics process, business
intelligence tools, and visualisation techniques that transform raw data into actionable insights
for organisational performance.
Target Participants
- ● Business analysts and data analysts
- ● Managers and decision-makers across departments
- ● Finance, sales, and operations professionals
- ● IT professionals supporting BI initiatives
- ● Strategy and planning professionals
- ● Professionals transitioning into data-focused roles
What You Will Learn
- ● Understand the principles and value of data analytics and business intelligence
- ● Apply the data analytics process: collection, cleaning, and analysis
- ● Use descriptive, diagnostic, predictive, and prescriptive analytics approaches
- ● Build and interpret data visualizations and dashboards
- ● Use business intelligence tools for reporting and analysis
- ● Apply statistical concepts relevant to business analysis
- ● Develop key performance indicators and metrics
- ● Communicate data insights effectively to stakeholders
- ● Use analytics to support strategic and operational decisions
Course Duration
- ● Face-to-face workshops: 5 days
- ● Virtual Training: 7 days
- ● LMS: Self-paced learning
Course Outline
Foundations of Data Analytics and BI
- ● What is data analytics and business intelligence
- ● The data-to-insight value chain
- ● Types of analytics: descriptive, diagnostic, predictive, prescriptive
- ● The role of data in modern decision-making
- ● Building a data-driven culture
Data Collection and Preparation
- ● Sources of business data
- ● Data quality, cleaning, and validation
- ● Structuring and organizing data for analysis
- ● Handling missing and inconsistent data
- ● Data governance and ethical considerations
Data Analysis Techniques
- ● Descriptive statistics for business analysis
- ● Identifying trends, patterns, and outliers
- ● Comparative and trend analysis
- ● Correlation and basic predictive techniques
- ● Segmentation and cohort analysis
Business Intelligence Tools and Dashboards
- ● Overview of common BI tools and platforms
- ● Connecting and importing data into BI tools
- ● Building interactive dashboards and reports
- ● Automating reporting and data refresh
Data Visualisation and Storytelling
- ● Principles of effective data visualisation
- ● Choosing the right chart for the right data
- ● Designing dashboards that drive decisions
- ● Data storytelling techniques
- ● Avoiding common visualisation mistakes
Applying Analytics for Decision-Making
- ● Defining and tracking key performance indicators (KPIs)
- ● Using analytics to support strategic planning
- ● Communicating insights to non-technical stakeholders
- ● Building a culture of data-informed decision-making
- ● Trends in analytics: AI and machine learning in BI
Training Approach
This course will be delivered through a coaching-first approach that goes beyond traditional
instruction. Whether in our Nairobi classroom, live virtual cohorts, or through our White Label
LMS, participants engage in a safe and nonjudgmental learning environment designed for
meaningful transformation.
We focus on the individual behind the professional title, connecting with the heart before
training the mind. This approach encourages reflection, practical application, and deeper
engagement, ensuring that learning is not only understood but also internalized and applied with
confidence.
Customized Training Solutions
This course can also be delivered as a tailor-made program, designed to address the specific
needs, priorities, and operational challenges of your organization.