Understanding databases, SQL fundamentals, and basic commands to create and manage tables.

Using SELECT, WHERE clause, and filtering techniques to retrieve specific data.

Learning how to summarize and group data using GROUP BY and filter grouped data with HAVING.

Using ORDER BY to sort data and understanding Query Execution Order.

Exploring INNER JOIN, LEFT JOIN, RIGHT JOIN, NATURAL JOIN, UNION, and INTERSECT.

Understanding SELF JOIN, CROSS JOIN, nested queries, and Common Table Expressions (CTEs).

Using string, numeric, and date functions along with CASE WHEN for conditional statements.

Exploring temp tables, views, PIVOT, and partitioning techniques.

Understanding stored procedures, triggers, and optimizing queries for performance.

Applying SQL skills to analyze data, create reports, and solve a real-world problem.

Understanding Python's role in data analysis, setting up the environment, and basic syntax.

Lists, Tuples, Dictionaries, and their applications in data handling.

Using NumPy for numerical operations, arrays, and performance optimization.

Reading, cleaning, and transforming datasets using Pandas DataFrames.

Creating meaningful charts and visual representations of data.

Techniques to understand data distribution, patterns, and outliers.

Connecting to databases, running SQL queries with Python using SQLite and Pandas.

Automating repetitive tasks like data cleaning and report generation using Python.

Basic statistical concepts, measures of central tendency, and correlation.

Applying Python skills to analyze real-world datasets and present insights.

Overview of Power BI, installation, interface navigation, and basic workflow.

Importing data from Excel, databases, web, and APIs into Power BI.

Cleaning, shaping, and transforming raw data using Power Query Editor.

Merging, appending, filtering, pivoting, and creating custom columns.

Understanding relationships, cardinality, and star schema modeling.

Creating calculated tables, hierarchies, and optimizing data models.

Fundamentals of DAX, measures vs calculated columns, and basic functions.

Using FILTER, SUMX, RANKX, and context transition for deep analysis.

Implementing YTD, MTD, QTD, running totals, and other time-based calculations.

Building bar charts, line charts, slicers, maps, and KPI indicators.

Working with custom visuals, conditional formatting, and storytelling techniques.

Designing professional dashboards, page navigation, and user experience best practices.

Publishing reports to Power BI Service, setting up workspaces, and sharing dashboards.

Optimizing queries, incremental refresh, and automating data updates.

Applying Power BI skills to build a complete data-driven dashboard and business report.

Understanding business fundamentals, key business drivers, and decision-making processes.

Exploring industry structures, competitive landscapes, and market dynamics.

Learning guestimation techniques for business scenarios and case interviews.

Analyzing real-world business growth strategies using structured problem-solving.

Interpreting financial statements, budgeting, and profitability analysis.

Learning about major industries: Retail, Finance, Healthcare, and IT.

Understanding Porter’s Five Forces, SWOT analysis, and strategic frameworks.

Identifying and tracking key performance indicators across different industries.

Understanding demand forecasting, data-driven decision making, and risk management.

Exploring how businesses leverage technology to drive innovation and efficiency.