Data Analytics Champion

• Basics of Spreadsheets: Overview and Navigation. • Excel Formulas: Basic Functions (SUM, AVERAGE, etc.). • Excel Functions: Advanced Functions (VLOOKUP, HLOOKUP). • Lab 1: Excel Basics and Functions o Practice Spreadsheet Navigation. o Apply Basic and Advanced Formulas. o Use Functions to Analyze Sample Data. • Use Case: Create a sales report to calculate total sales, average sales per month, and use VLOOKUP to find sales figures for specific products.

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• Data Entry Techniques: Efficient Data Input. • Data Validation: Creating Drop-down Lists, Restricting Entries. • Conditional Formatting: Highlighting and Formatting Data. • Lab 2: Data Entry and Validation o Practice Efficient Data Entry. o Set Up Data Validation and Conditional Formatting. • Use Case: Set up a data entry form for customer feedback with validation to ensure accurate data entry, and use conditional formatting to highlight entries based on satisfaction ratings.

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• Sorting and Filtering: Techniques for Organizing Data. • Data Cleaning: Removing Duplicates, Handling Errors. • Working with Tables: Creating and Managing Data Tables. • Lab 3: Data Management in Excel o Implement Sorting, Filtering, and Data Cleaning. o Create and Manage Tables for Data Analysis. • Use Case: Organize a large dataset of customer orders by sorting and filtering to identify top customers and clean the data to remove duplicates and correct errors.

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• Pivot Tables: Creating and Customizing Pivot Tables. • Pivot Charts: Visualizing Data with Pivot Charts. • Introduction to Macros: Recording and Running Macros. • Lab 4: Advanced Excel Techniques o Build and Customize Pivot Tables and Charts. o Record and Run Macros for Automation. • Use Case: Analyze company performance by creating pivot tables to summarize sales data by region and product category and use macros to automate repetitive data processing tasks.

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• Database Concepts: Basics of Relational Databases. • Writing Basic SQL Queries: SELECT, WHERE, ORDER BY. • Aggregate Functions: Using COUNT, SUM, AVG. • Lab 5: SQL Basics o Execute Basic SQL Queries. o Apply Aggregate Functions to Analyze Data. • Use Case: Query a customer database to retrieve a list of customers who made purchases in the last month and calculate the total and average purchase amounts.

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• Data Insertion: Using INSERT to Add Data. • Data Updates: Using UPDATE to Modify Data. • Data Deletion: Using DELETE to Remove Data. • Lab 6: SQL Data Manipulation o Practice Data Insertion, Updates, and Deletion. • Use Case: Update a product inventory database by adding new product entries, modifying existing product details, and deleting discontinued products.

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• Joins: Combining Data from Multiple Tables (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN). • Subqueries: Writing Nested Queries. • Indexes and Optimization: Improving Query Performance. • Lab 7: Advanced SQL Queries o Create Joins and Write Subqueries. o Optimize Queries Using Indexes. • Use Case: Generate a report combining customer and order data to show detailed order histories for each customer, including total amounts spent and average order value.

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• Table Creation: Defining Schema with CREATE TABLE. • Altering Tables: Adding and Modifying Columns with ALTER TABLE. • Working with Views and Stored Procedures: Managing Data Access. • Lab 8: SQL Tables and Procedures o Create and Modify Tables. o Work with Views and Stored Procedures. • Use Case: Design a new database schema for an e-commerce application, create tables for products, customers, and orders, and implement views and stored procedures to streamline data access and reporting.

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• Power BI Overview: Interface and Navigation. • Connecting to Data Sources: Importing and Linking Data. • Data Transformation: Using Power Query Editor. • Lab 9: Power BI Basics o Navigate Power BI Interface. o Connect to Data Sources and Transform Data. • Use Case: Connect Power BI to a sales database, transform the data to clean and structure it, and prepare it for analysis.

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• Creating Visuals: Designing Charts, Maps, and KPIs. • Customizing Visuals: Adjusting Settings and Formatting. • Building Interactive Dashboards: Combining Visuals into Dashboards. • Lab 10: Power BI Visualizations o Create and Customize Visuals. o Build Interactive Dashboards. • Use Case: Create an interactive sales dashboard in Power BI that includes charts and KPIs to monitor sales performance across different regions and product categories.

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• Introduction to DAX: Basics of Data Analysis Expressions. • Advanced DAX Functions: Creating Complex Measures and Calculations. • Power BI Service: Publishing Reports, Sharing, and Collaboration. • Lab 11: Advanced Power BI o Practice DAX Functions and Measures. o Publish and Share Reports Using Power BI Service. • Use Case: Develop advanced DAX calculations to create custom metrics for sales analysis, publish the dashboard to the Power BI Service, and share it with stakeholders for collaborative decision-making.

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• Tableau Overview: Interface and Navigation. • Connecting to Data Sources: Importing and Preparing Data. • Creating Basic Visualizations: Charts, Maps, and Graphs. • Lab 12: Tableau Basics o Navigate Tableau Interface o Connect to Data Sources and Create Basic Visualizations. • Use Case: Connect Tableau to a marketing data source, prepare the data for analysis, and create basic visualizations to track campaign performance.

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• Designing Dashboards: Combining Visuals and Adding Interactivity. • Advanced Visualizations: Using Calculations and Parameters. • Data Storytelling: Crafting Compelling Narratives with Data. • Lab 13: Tableau Dashboards o Design and Build Interactive Dashboards. o Create Advanced Visualizations and Data Stories. • Use Case: Build a comprehensive marketing performance dashboard in Tableau, using advanced visualizations and interactive elements to tell the story of campaign success and areas for improvement.

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• Tableau Server: Publishing and Managing Dashboards. • Tableau Mobile and Public: Expanding Accessibility. • Optimizing Performance: Tips for Efficient Dashboards. • Lab 14: Advanced Tableau o Publish and Manage Dashboards on Tableau Server. o Optimize Dashboard Performance. • Use Case: Publish the marketing performance dashboard to Tableau Server, make it accessible via Tableau Mobile, and optimize it for fast performance and user accessibility.

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• Excel Data Analysis Project: Applying Excel Skills to Real-World Data • SQL Data Querying Project: Using SQL for Complex Data Queries • Power BI Dashboard Project: Building a Comprehensive Power BI Dashboard • Tableau Data Visualization Project: Developing Advanced Tableau Dashboards • Final Project Presentations: Organizing, Presenting, and Reviewing Projects • Lab 15: Final Projects o Work on Real-World Projects Using Excel, SQL, Power BI, and Tableau o Prepare and Present Final Projects o Receive and Act on Feedback • Use Case: Apply all learned skills to complete comprehensive projects for each tool (Excel, SQL, Power BI, and Tableau), culminating in a final presentation showcasing the ability to analyze data, draw insights, and present findings effectively.

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• Basics of python. • Data types. • Conditional statements. • Data Structures – String, List, Tuple, Set, Dictionaries. • Functions, Modules and Packages. • Object Oriented Programming and Exceptional Handling. • File Handling. • Data Structures using Pandas and Mathematical Operations using NumPy. • Data analysis using matplotlib and seaborn.

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