Session 1: Introduction to Data Analytics
Provide a strong foundation on what data analysis is, where it fits in organizations, and different career paths in analytics.
- What is Data Analytics?
- Difference between Data Analytics, Business Intelligence (BI), and Data Science
- Types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive
- The Data Analyst workflow
- Tools used in data analysis (Excel, SQL, Power BI, Tableau, Python—optional introduction)
- The role and responsibilities of a Data Analyst
- Importance of data-driven decision making
Session 2: Data Collection & ETL Fundamentals (Using Power BI)
Introduce how analysts acquire, clean, and prepare data using ETL concepts and Power BI.
- Understanding the ETL (Extract, Transform, Load) process
- Data sources (Excel, CSV, Databases, APIs)
- Using Power Query for:
- Data extraction
- Data cleaning (removing duplicates, handling NULLs, formatting)
- Data transformation (joins, merges, splits, derived columns)
- Loading cleaned data into Power BI
- Best practices for data preparation
Session 3: Data Modeling & Analysis in Power BI
Learn how to structure and relate data for efficient analysis and reporting.
- Star schema and relational modeling for analytics
- Understanding tables, relationships, cardinality, and data granularity
- Calculated columns vs. measures
- Introduction to DAX for:
- Basic calculations
- Time intelligence
- KPIs
- Building interactive dashboards:
- Slicers, filters, drill-through
- Designing intuitive report pages
- Data storytelling in Power BI
Session 4: Data Visualization with Tableau
Alternative visualization tool and strengthen dashboarding skills.
- Tableau interface and workspace overview
- Connecting Tableau to various data sources
- Building core visualizations:
- Bar & line charts
- Geographic maps
- Scatter plots
- Highlight tables
- Dashboard creation:
- Filters, actions, interactivity
- Layout and design principles
- Publishing and sharing Tableau dashboards
Session 5: Introduction to SQL for Data Analysts
Essential SQL skills that every data analyst needs.
- What is SQL and why analysts use it
- Database structures (Tables, Rows, Fields, Schemas)
- Basic SQL syntax
- SELECT statements
- Filtering with WHERE
- Sorting with ORDER BY
- Working with basic functions (COUNT, SUM, MIN, MAX)
- Simple hands-on query exercises
Session 6: Intermediate SQL for Analysis
Advance SQL proficiency for real analytical tasks.
- GROUP BY and HAVING for aggregation
- Joins (INNER, LEFT, RIGHT, FULL)
- Subqueries and Common Table Expressions (CTEs)
- Data cleaning with SQL (CASE statements, string functions)
- Combining SQL with BI tools
- Writing queries for reporting and business insights
