Course Objectives
This comprehensive course is designed to provide participants with the skills and knowledge
required to analyze, interpret, and visualize data for business intelligence and decision-making.
By the end of the course, participants will be able to:
• Develop a strong understanding of data analytics and business intelligence concepts.
• Utilize Microsoft Excel for data manipulation, visualization, and analysis.
• Write and optimize SQL queries for data retrieval, transformation, and management.
• Leverage Python for advanced data analytics, automation, and visualization.
• Design interactive dashboards and reports using Power BI.
• Apply business intelligence techniques to extract actionable insights from data.
• Implement best practices for data-driven decision-making in real-world scenarios.

Course Outline
Module 1: Introduction to Data Analytics and Business Intelligence
• Understanding the role of data analytics in business
• Key concepts of business intelligence and decision-making
• Overview of Microsoft Excel, Python, Power BI, and T-SQL
• Data analytics lifecycle and methodologies

Module 2: Data Analysis Using Microsoft Excel
• Data cleaning, transformation, and preparation techniques
• Advanced Excel functions for data analysis (VLOOKUP, INDEX-MATCH, etc.)
• PivotTables and Pivot Charts for data summarization
• Conditional formatting and data visualization techniques
• Introduction to Power Query for ETL (Extract, Transform, Load)

Module 3: SQL for Data Analysis (T-SQL)
• Fundamentals of relational databases and SQL
• Writing SELECT queries and using filtering techniques
• Joins, aggregations, and subqueries for data extraction
• Common Table Expressions (CTEs) and window functions
• Data manipulation using INSERT, UPDATE, and DELETE
• Query optimization techniques for performance improvement

Module 4: Python for Data Analytics
• Introduction to Python and its role in data analytics
• Data handling with Pandas and NumPy
• Exploratory Data Analysis (EDA) using Python
• Data visualization with Matplotlib and Seaborn
• Automating data processing tasks with Python scripts

Module 5: Business Intelligence with Power BI
• Introduction to Power BI and data modeling concepts
• Connecting Power BI to multiple data sources (Excel, SQL, APIs)
• Data transformation and preparation using Power Query
• Creating interactive dashboards and visual reports
• Implementing DAX (Data Analysis Expressions) for custom calculations
• Publishing and sharing Power BI reports

Module 6: Advanced Data Analytics and Business Intelligence Applications
• Forecasting and predictive analytics in business decision-making
• Designing Key Performance Indicators (KPIs) and business metrics
• Developing end-to-end business intelligence solutions
• Case studies and hands-on real-world projects

Participant Outcomes
Upon successful completion of this course, participants will:
• Gain proficiency in data analytics and business intelligence tools and techniques.
• Analyze, interpret, and visualize data effectively using Excel, Python, Power BI, and
SQL.
• Build dynamic, interactive dashboards and reports for business insights.
• Write optimized SQL queries for efficient data retrieval and management.
• Automate data analysis processes using Python.
• Apply data-driven decision-making to solve business challenges.
• Enhance career opportunities in data analytics, business intelligence, and data science.