BUSINESS INTELLIGENCE BI : Data Visualization | Measures | 2025

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BUSINESS INTELLIGENCE BI : Data Visualization | Measures | 2025

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₦850,000.00 ₦595,000.00

 

Business Analytics and Visualization using Microsoft Power BI

Course Overview:

This 2-month course is designed to equip learners with essential business analytics skills, focusing on data analysis, reporting, and visualization using Microsoft Power BI and other related tools. Through practical hands-on assignments and projects, students will gain proficiency in transforming raw data into meaningful insights that drive decision-making. The course will cover key concepts, tools, and techniques used in the business analytics field, preparing participants for industry roles.

Prerequisites:

  • Basic understanding of Excel or spreadsheets.
  • Familiarity with data concepts (e.g., data types, tables, basic analysis).

Course Outline:

Week 1: Introduction to Business Analytics and Power BI

  • Lecture Topics:

    • Introduction to Business Analytics: Definition, Scope, and Importance.
    • Overview of Data Analytics Life Cycle.
    • Introduction to Microsoft Power BI: Features and Benefits.
    • Power BI Desktop vs Power BI Service vs Power BI Mobile.
    • Installation and Setup of Power BI Desktop.
    • Understanding Power BI Interface: Ribbon, Visualizations, Fields, and Report View.

  • Hands-on Activity:

    • Loading and importing data into Power BI.
    • Exploring sample datasets.
    • Simple data cleaning techniques in Power BI.

  • Assignment 1:

    • Import a dataset from Excel into Power BI and perform basic data exploration. Create a simple report displaying key metrics.

Week 2: Data Transformation and Cleaning in Power BI

  • Lecture Topics:

    • Data Transformation Basics: Introduction to Power Query Editor.
    • Data Cleaning Techniques: Removing duplicates, handling null values, splitting columns.
    • Working with Date and Time: Creating Date Tables and Time Intelligence.
    • Using Power Query to merge, append, and transform data from different sources.
    • Introduction to Data Types and Data Modeling in Power BI.

  • Hands-on Activity:

    • Data transformation using Power Query.
    • Working with different data sources (Excel, CSV, Database).
    • Building custom columns and measures.

  • Assignment 2:

    • Clean and transform a given dataset and prepare it for visualization.

Week 3: Data Modeling and Relationships

  • Lecture Topics:

    • Understanding Relationships: One-to-One, One-to-Many, Many-to-Many.
    • Designing a Data Model: Creating Relationships and Setting Cardinality.
    • Introduction to Star Schema and Snowflake Schema in Power BI.
    • Role of Fact and Dimension Tables.
    • Introduction to DAX (Data Analysis Expressions): Basic Calculations.

  • Hands-on Activity:

    • Create a basic data model with multiple tables.
    • Implement relationships between tables and use simple DAX functions.

  • Assignment 3:

    • Build a data model for a sales dataset and create relevant measures using DAX.

Week 4: Data Visualization Techniques in Power BI

  • Lecture Topics:

    • Introduction to Power BI Visuals: Types of Visualizations (Bar, Line, Pie, Table, etc.).
    • Choosing the Right Visual: When to use what type of visualization.
    • Custom Visuals and Marketplace in Power BI.
    • Advanced Visuals: Tree Maps, Waterfall Charts, KPI Indicators, and Combo Charts.
    • Formatting and Interactivity: Conditional formatting, slicers, drill-through.

  • Hands-on Activity:

    • Building various types of visualizations based on a sample dataset.
    • Applying filters and slicers to dashboards.

  • Assignment 4:

    • Create a dashboard using multiple visuals to show different perspectives of sales performance.

Week 5: Advanced DAX and Calculations

  • Lecture Topics:

    • Advanced DAX Functions: CALCULATE, FILTER, ALL, and Time Intelligence Functions.
    • Aggregation Functions in DAX: SUM, AVERAGE, COUNTROWS.
    • Creating Calculated Columns and Measures.
    • Working with Date Functions and Time Intelligence (Year-to-Date, Month-to-Date, Moving Averages).

  • Hands-on Activity:

    • Use DAX to create custom metrics and KPIs.
    • Practice working with time-based calculations and filtering data.

  • Assignment 5:

    • Implement time intelligence in a sales report (e.g., Year-to-Date, MTD, QTD calculations).

Week 6: Power BI Reports and Dashboards

  • Lecture Topics:

    • Building Interactive Reports and Dashboards.
    • Report Layout and Design Best Practices.
    • Utilizing Bookmarks and Buttons for navigation.
    • Embedding Reports and Dashboards in Power BI Service.
    • Introduction to Power BI Publishing and Sharing Reports.

  • Hands-on Activity:

    • Creating interactive reports and applying slicers for dynamic filtering.
    • Publishing reports to Power BI Service and sharing with others.

  • Assignment 6:

    • Create and share a dashboard using Power BI Service.

Week 7: Advanced Reporting and Custom Visuals

  • Lecture Topics:

    • Introduction to Power BI Themes and Customization.
    • Custom Visualizations in Power BI: Custom Visuals Gallery and Custom Visuals SDK.
    • Using Power BI with Excel: Integration and Analysis.
    • Power BI Embedded: Embedding Power BI Reports in applications.
    • Power BI Performance Optimization Techniques.

  • Hands-on Activity:

    • Customize reports using themes and custom visuals.
    • Integrate Power BI reports into Excel and SharePoint.

  • Assignment 7:

    • Design a custom Power BI visual and integrate it into an existing report.

Week 8: Power BI Service, Sharing, and Publishing Reports

  • Lecture Topics:

    • Power BI Service Overview: Dashboards, Reports, Workspaces.
    • Scheduling Data Refreshes and Data Gateways.
    • Power BI Pro vs Power BI Premium: Understanding Licensing and Cost.
    • Collaboration and Sharing Reports in Power BI Service.
    • Power BI Mobile App: Features and Publishing to Mobile.

  • Hands-on Activity:

    • Publishing, refreshing data, and sharing reports in Power BI Service.
    • Creating dashboards in Power BI Service and sharing them with team members.

  • Assignment 8:

    • Publish and share a dashboard via Power BI Service. Set up automatic data refresh.

Projects (15 Projects)

  1. Project 1: Sales Dashboard
    Create a sales performance dashboard for a retail store using Power BI with key metrics such as total sales, average order value, and sales by region.

  2. Project 2: Customer Segmentation
    Use clustering techniques to segment customers based on purchasing behavior and visualize the results.

  3. Project 3: Financial Reporting
    Build a financial reporting dashboard showing profit margins, revenue growth, and cost analysis over time.

  4. Project 4: Marketing Campaign Analysis
    Analyze the performance of marketing campaigns across different channels and present results in a Power BI report.

  5. Project 5: HR Analytics Dashboard
    Build a dashboard to analyze employee retention, satisfaction, and department performance.

  6. Project 6: Retail Store Performance Dashboard
    Track key metrics like foot traffic, conversion rates, and sales per employee.

  7. Project 7: E-commerce Website Analysis
    Analyze website traffic and sales performance over time.

  8. Project 8: Inventory Management Dashboard
    Create a dashboard to track inventory levels, turnover rates, and order fulfillment efficiency.

  9. Project 9: Customer Satisfaction Analysis
    Analyze customer feedback and survey data to understand satisfaction levels.

  10. Project 10: Supply Chain Optimization
    Build a Power BI model to visualize key supply chain metrics and identify bottlenecks.

  11. Project 11: Market Share Analysis
    Compare company performance against competitors over time.

  12. Project 12: Budgeting and Forecasting
    Build a financial forecasting dashboard using historical data.

  13. Project 13: Risk Management Dashboard
    Analyze risk indicators (e.g., financial, operational, compliance risks) and display them on a dashboard.

  14. Project 14: Social Media Analytics
    Analyze social media metrics and track trends over time.

  15. Project 15: Sales and Marketing Integration
    Create an integrated dashboard combining sales data with marketing efforts.

Final Project

  • Objective:
    Develop a complete Power BI report/dashboard for a company, integrating data from multiple sources (sales, marketing, finance, HR) to provide comprehensive business insights.

  • Deliverables:

    • A fully interactive report/dashboard.
    • A detailed analysis of the data with key insights.
    • A presentation summarizing the findings and recommendations.

Job Opportunities and Average Salary

Job Titles:

  1. Business Intelligence Analyst

    • Responsibilities: Data analysis, report building, dashboard creation, business insights.
    • Average Salary: $70,000 – $100,000 per year.

  2. Data Analyst

    • Responsibilities: Data cleansing, modeling, visualization, and reporting.
    • Average Salary: $60,000 – $90,000 per year.

  3. Power BI Developer

    • Responsibilities: Developing Power BI reports, dashboards, and implementing DAX calculations.
    • Average Salary: $80,000 – $120,000 per year.

  4. Data Scientist

    • Responsibilities: Advanced analytics, machine learning models, predictive analysis.
    • Average Salary: $90,000 – $130,000 per year.

  5. Business Analyst

    • Responsibilities: Identifying business requirements, analyzing data, creating reports.
    • Average Salary: $70,000 – $110,000 per year.

Conclusion:

By the end of this course, participants will have a strong command of Microsoft Power BI and other analytics tools, along with a comprehensive portfolio of projects. The course aims to prepare learners for immediate job placement in business intelligence, analytics, or related fields. With solid experience in hands-on projects and a final capstone, participants will be well-positioned to secure lucrative roles in the analytics domain.