Data Analytics
The Data Analytics course is designed to transform learners into industry-ready data professionals by mastering the complete analytics workflow—from data collection and cleaning to business intelligence and dashboard reporting. The curriculum follows a structured learning path through Advanced Excel, SQL, Python, and Power BI, enabling students to analyze business data, uncover actionable insights, and build interactive decision-making dashboards used across modern enterprises.
Course Overview
Advanced Excel for Data Analytics
SUMIFS, COUNTIFS, XLOOKUP, INDEX-MATCH, dynamic arrays, and logical functions.
Creating Pivot Tables, Pivot Charts, slicers, and calculated fields.
Handling missing values, duplicates, text manipulation, and formatting.
Automating data preparation, transformations, and recurring workflows.
Interactive reporting using charts, KPIs, slicers, and business metrics.
Streamlining repetitive tasks and improving analytical productivity.
SQL for Enterprise Data Extraction
SELECT, WHERE, ORDER BY, LIKE, IN, BETWEEN, and filtering operations.
DDL, DML commands, data management, and relational database concepts.
GROUP BY, HAVING, COUNT, SUM, AVG, and statistical summaries.
INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN operations.
Window functions, ranking, LEAD, LAG, and CASE statements.
Common Table Expressions, nested queries, and query optimization.
Python for Data Analysis & EDA
Variables, loops, functions, lists, tuples, dictionaries, and modules.
Interactive coding, documentation, and analytics workflow management.
DataFrames, filtering, grouping, aggregation, and transformation techniques.
Numerical computing, array handling, and mathematical processing.
Identifying trends, correlations, distributions, and anomalies.
Charts and graphical reporting using Matplotlib and Seaborn libraries.
Power BI & Business Intelligence
Importing data from Excel, databases, APIs, and cloud services.
Cleaning, transforming, and preparing analytical datasets.
Building Star Schemas, Snowflake Schemas, and relationships.
Creating KPIs, measures, calculated columns, and time intelligence.
Interactive reports, drill-down analysis, filters, and executive dashboards.
Publishing, sharing, collaboration, and report security management.
Recommended Learning Roadmap
- Weeks 1–3: Advanced Excel & Data Cleaning
- Weeks 4–7: SQL Querying & Database Analytics
- Weeks 8–11: Python Programming & EDA
- Weeks 12–15: Power BI Dashboard Development
- End-to-End Analytics Project Implementation
Practical Learning Approach
- Business Data Cleaning Projects
- SQL Database Query Challenges
- Python-Based Data Analysis Assignments
- Exploratory Data Analysis Case Studies
- Interactive Dashboard Development
- Power BI Reporting Projects
- Real-World Business Intelligence Scenarios
- Portfolio-Ready Analytics Projects
Capstone Analytics Project
Build a complete end-to-end Data Analytics solution by extracting customer and sales data using SQL, cleaning and analyzing the data with Python, and finally developing an interactive Power BI dashboard that presents key business insights and performance indicators for decision-makers.
Prerequisites
No prior programming experience is required. Basic computer knowledge and familiarity with spreadsheets are helpful. The course begins with Excel fundamentals and gradually progresses toward advanced analytics, programming, and business intelligence development.