Introduction

In today's hyper-competitive and data-rich business landscape, the ability to transform raw data into actionable intelligence is no longer a luxury but a fundamental imperative for organizational success. Data-Driven Decision Making using Business Intelligence (BI) Tools empowers professionals to move beyond intuition, leveraging powerful analytical platforms to uncover hidden patterns, predict future trends, and make informed strategic choices that drive efficiency, profitability, and innovation. This training course is meticulously designed to equip business analysts, managers, data professionals, marketing specialists, financial analysts, and executives with cutting-edge knowledge and practical skills in understanding the principles of data-driven decision making, mastering the functionalities of leading BI tools (e.g., Tableau, Power BI, Qlik Sense), developing compelling dashboards and reports, performing advanced data visualization and analysis, integrating data from diverse sources, and communicating insights effectively to stakeholders. Participants will gain a comprehensive understanding of how to harness the power of data to gain a competitive advantage, optimize operations, and foster a culture of evidence-based decision making within their organizations.

Duration

10 days

Target Audience

• Business Analysts
• Managers & Team Leaders
• Data Analysts & Scientists (Beginner/Intermediate)
• Marketing & Sales Professionals
• Financial Analysts
• Operations Managers
• IT Professionals (supporting BI initiatives)
• Executives & Decision Makers
• Anyone seeking to improve decision-making through data

Objectives

• Understand the fundamental concepts of data-driven decision making and business intelligence.
• Master the process of data extraction, transformation, and loading (ETL) for BI.
• Develop proficiency in using leading BI tools (e.g., Tableau, Power BI, Qlik Sense) for data analysis.
• Learn to create compelling and interactive dashboards and reports.
• Understand various data visualization best practices for effective communication.
• Explore advanced analytical techniques within BI tools (e.g., forecasting, what-if analysis).
• Develop skills in integrating data from diverse sources for comprehensive insights.
• Learn about data governance, quality, and security in BI environments.
• Understand the role of storytelling with data in influencing decisions.
• Formulate strategies for implementing and scaling BI initiatives within an organization.
• Apply data-driven approaches to solve real-world business problems.

Course Content

Module 1. Introduction to Data-Driven Decision Making and Business Intelligence

• Defining Data-Driven Decision Making (DDDM): Principles and benefits
• What is Business Intelligence (BI)?: Components, architecture, and evolution
• The data-to-information-to-insight-to-action continuum
• Role of data in strategic, tactical, and operational decisions
• Case studies of successful DDDM implementations

Module 2. Data Fundamentals for BI

• Data Types: Structured, unstructured, semi-structured
• Data Sources: Databases (SQL, NoSQL), spreadsheets, APIs, cloud data
• Data Quality: Accuracy, completeness, consistency, timeliness
• Data governance and data ethics
• Introduction to data warehousing and data lakes

Module 3. Data Extraction, Transformation, and Loading (ETL) for BI

• Extraction: Connecting to various data sources
• Transformation: Cleaning, normalizing, aggregating, enriching data
• Loading: Storing prepared data for analysis
• ETL tools and processes
• Best practices for data preparation

Module 4. Introduction to Tableau: Interface and Basic Visualizations

• Tableau Desktop Interface: Worksheets, dashboards, stories
• Connecting to Data: Various data connectors
• Basic Chart Types: Bar charts, line charts, pie charts, scatter plots
• Dimensions and Measures: Understanding their roles
• Creating calculated fields

Module 5. Tableau: Advanced Visualizations and Dashboards

• Advanced Chart Types: Dual-axis charts, treemaps, heatmaps, geographical maps
• Dashboard Design Principles: Layout, interactivity, filters, parameters
• Storytelling with data in Tableau
• Publishing and sharing Tableau workbooks
• Performance optimization for Tableau dashboards

Module 6. Introduction to Microsoft Power BI: Interface and Data Modeling

• Power BI Desktop Interface: Reports, data, model views
• Connecting to Data: Power Query Editor for data transformation
• Data Modeling: Relationships, DAX (Data Analysis Expressions) fundamentals
• Creating measures and calculated columns
• Introduction to Power BI Service

Module 7. Power BI: Reports, Dashboards, and Collaboration

• Creating Visualizations: Various chart types, custom visuals
• Report Design: Layout, interactivity, slicers, drill-through
• Power BI Dashboards: Pinning visuals, Q&A feature
• Publishing and sharing reports and dashboards
• Power BI Apps and collaboration features

Module 8. Introduction to Qlik Sense: Interface and Associative Model

• Qlik Sense Hub and App Overview: Creating and managing apps
• Data Load Editor: Scripting for data loading and transformation
• Associative Data Model: Understanding its unique benefits
• Smart Search and global selections
• Creating basic visualizations

Module 9. Qlik Sense: Advanced Analytics and Storytelling

• Advanced Charting: Custom objects, extensions
• Dashboarding in Qlik Sense: Layout, responsiveness, master items
• Storytelling: Creating data stories from insights
• Collaboration and sharing in Qlik Sense
• Qlik Sense on mobile devices

Module 10. Data Visualization Best Practices

• Principles of Effective Visualization: Clarity, accuracy, impact
• Choosing the right chart type for your data and message
• Color Theory and Typography: Enhancing readability
• Avoiding misleading visualizations and common pitfalls
• Designing for different audiences and purposes

Module 11. Advanced Analytics in BI Tools

• Forecasting: Time series analysis, trend lines
• What-If Analysis: Parameters, scenarios
• Clustering and Segmentation
• Regression analysis within BI tools
• Introduction to integrating R/Python with BI tools

Module 12. Integrating Data from Diverse Sources

• Connecting to Databases: SQL Server, Oracle, MySQL
• Cloud Data Sources: Azure, AWS, Google Cloud
• Web Data Connectors: APIs, web scraping
• Combining disparate datasets for holistic views
• Data blending techniques

Module 13. Data Governance, Security, and Compliance

• Data Governance Frameworks: Roles, policies, standards
• Data Security: Row-level security, data encryption, access control
• Data privacy regulations (e.g., GDPR, CCPA)
• Audit trails and data lineage
• Ensuring compliance in BI environments

Module 14. Storytelling with Data and Communication of Insights

• Narrative Structure: Crafting a compelling story from data
• Audience Engagement: Tailoring insights to stakeholder needs
• Presenting data effectively: Visuals, verbal communication, written reports
• Influencing decisions through data-driven narratives
• Handling questions and objections

Module 15. Implementing and Scaling BI Initiatives

• BI Strategy Development: Aligning BI with business goals
• Team Roles: Data engineers, analysts, BI developers, business users
• Deployment Models: On-premise, cloud, hybrid
• User adoption strategies and training
• Measuring ROI of BI initiatives and continuous improvement.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.