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Data Analytics Champion

Transform Data into Insights | Master the Art of Data Analytics

  • Leading Training Partner for Aspiring Data Analysts Worldwide
  • Earn 45 Learning Hours | 12 Real-world Projects | 1500+ Analytical Questions
  • Master Data Visualization, Statistical Analysis, and SQL Techniques
  • Comprehensive Cheat Sheets | Personalized Study Plans for Certification Success
  • Guaranteed to Run 25+ Live Cohorts in the Next 90 Days
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Course Overview

Evani’s Data Analytics Champion program is designed to equip learners with essential data analytics skills. Covering Excel, SQL, Power BI, and Tableau, it combines theory with practical experience. You'll master data modeling, preparation, querying, and visualization through realworld case studies and projects. By the end, you'll have a strong grasp of data analytics tools and principles, ready to make impactful business decisions

Course Description

This intensive four-month course is crafted to equip participants with advanced skills in data analysis, data querying, and data visualization using Excel, SQL, Power BI, and Tableau. Through hands-on sessions and practical projects, students will learn to manage, analyze, and visualize data effectively, preparing them for roles in data analysis, business intelligence, and related fields.

Course Outcomes

Master advanced Excel functions and data visualization techniques.
Perform complex data queries and manipulations using SQL.
Develop interactive dashboards and reports in Power BI.
Create sophisticated data visualizations and stories using Tableau.
Integrate and apply knowledge from different tools through comprehensive projects.

Pre-requisite

Basic understanding of spreadsheets.
Familiarity with basic database concepts.
No prior experience with Power BI or Tableau required.

Target Audience

Aspiring Data Analysts and Business Intelligence professionals.
Individuals looking to enhance their data handling and visualization skills.
Professionals aiming to integrate data analysis into their current roles.

This course includes:

  • Duration 100 hours

  • Lectures 88 lessons

  • Certificate of Completion

  • Full lifetime access

Upcoming Cohort Class

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Course Curriculum

  • 1 Use Case: Create a sales report to calculate total sales, average sales per month, and use VLOOKUP to find sales figures for specific products.
  • 2 Lab 1: Excel Basics and Functions
  • 3 • Excel Functions: Advanced Functions (VLOOKUP, HLOOKUP).
  • 4 Excel Formulas: Basic Functions (SUM, AVERAGE, etc.)
  • 5 Basics of Spreadsheets: Overview and Navigation.
  • 1 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.
  • 2 Lab 2: Data Entry and Validation
  • 3 Conditional Formatting: Highlighting and Formatting Data.
  • 4 Data Validation: Creating Drop-down Lists, Restricting Entries.
  • 5 Data Entry Techniques: Efficient Data Input.
  • 1 Data Cleaning: Removing Duplicates, Handling Errors.
  • 2 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.
  • 3 Lab 3: Data Management in Excel
  • 4 Working with Tables: Creating and Managing Data Tables.
  • 5 Sorting and Filtering: Techniques for Organizing Data.
  • 1 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.
  • 2 Lab 4: Advanced Excel Techniques
  • 3 Introduction to Macros: Recording and Running Macros.
  • 4 Pivot Charts: Visualizing Data with Pivot Charts.
  • 5 Pivot Tables: Creating and Customizing Pivot Tables.
  • 1 Writing Basic SQL Queries: SELECT, WHERE, ORDER BY.
  • 2 Database Concepts: Basics of Relational Databases.
  • 3 Aggregate Functions: Using COUNT, SUM, AVG.
  • 4 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
  • 5 Lab 5: SQL Basics
  • 1 Use Case: Update a product inventory database by adding new product entries, modifying existing product details, and deleting discontinued products.
  • 2 Lab 6: SQL Data Manipulation
  • 3 Data Deletion: Using DELETE to Remove Data.
  • 4 Data Updates: Using UPDATE to Modify Data.
  • 5 Data Insertion: Using INSERT to Add Data.
  • 1 Lab 7: Advanced SQL Queries
  • 2 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.
  • 3 Indexes and Optimization: Improving Query Performance.
  • 4 Subqueries: Writing Nested Queries
  • 5 Joins: Combining Data from Multiple Tables (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN)
  • 1 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
  • 2 Lab 8: SQL Tables and Procedures
  • 3 Working with Views and Stored Procedures: Managing Data Access.
  • 4 Altering Tables: Adding and Modifying Columns with ALTER TABLE.
  • 5 Table Creation: Defining Schema with CREATE TABLE
  • 1 Use Case: Connect Power BI to a sales database, transform the data to clean and structure it, and prepare it for analysis.
  • 2 Lab 9: Power BI Basic
  • 3 Data Transformation: Using Power Query Editor.
  • 4 Connecting to Data Sources: Importing and Linking Data.
  • 5 Power BI Overview: Interface and Navigation.
  • 1 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.
  • 2 Lab 10: Power BI Visualization
  • 3 Building Interactive Dashboards: Combining Visuals into Dashboards.
  • 4 Customizing Visuals: Adjusting Settings and Formatting.
  • 5 Creating Visuals: Designing Charts, Maps, and KPIs.
  • 1 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 deci
  • 2 Lab 11: Advanced Power BI
  • 3 Power BI Service: Publishing Reports, Sharing, and Collaboration
  • 4 Advanced DAX Functions: Creating Complex Measures and Calculations.
  • 5 Introduction to DAX: Basics of Data Analysis Expressions.
  • 1 Tableau Overview: Interface and Navigation
  • 2 Use Case: Connect Tableau to a marketing data source, prepare the data for analysis, and create basic visualizations to track campaign performance.
  • 3 Lab 12: Tableau Basics
  • 4 Creating Basic Visualizations: Charts, Maps, and Graphs
  • 5 Connecting to Data Sources: Importing and Preparing Data
  • 1 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 improv
  • 2 Lab 13: Tableau Dashboards
  • 3 Advanced Visualizations: Using Calculations and Parameters
  • 4 Designing Dashboards: Combining Visuals and Adding Interactivity
  • 1 Tableau Mobile and Public: Expanding Accessibility
  • 2 Tableau Server: Publishing and Managing Dashboards
  • 3 Lab 14: Advanced Tableau
  • 4 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
  • 1 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 analyz
  • 2 Lab 15: Final Projects
  • 3 Final Project Presentations: Organizing, Presenting, and Reviewing Project
  • 4 Tableau Data Visualization Project: Developing Advanced Tableau Dashboards
  • 5 Power BI Dashboard Project: Building a Comprehensive Power BI Dashboard
  • 6 SQL Data Querying Project: Using SQL for Complex Data Queries
  • 7 Excel Data Analysis Project: Applying Excel Skills to Real-World Data
  • 1 Conditional statements
  • 2 Data analysis using matplotlib and seaborn
  • 3 Object Oriented Programming and Exceptional Handling.
  • 4 Functions, Modules and Packages.
  • 5 Data Structures – String, List, Tuple, Set, Dictionaries.
  • 6 Data types.
  • 7 Basics of python.
  • 1 Regression Modelling.
  • 2 Data Clustering
  • 3 Statistical Inference.
  • 4 Probability and its uses
  • 5 Understanding the Data .

Why Choose Us?

Excellent Mentors: Industry-experienced instructors with deep expertise in their respective fields.
Hands-on Projects: Practical hands-on projects and assignments that reinforce learning and facilitate skill application.
Customer Success: Dedicated customer support and learning assistance throughout the learning journey.
Lifetime Access: Lifetime access to course materials and updates, ensuring continuous learning and skill enhancement. One-time investment for lifetime access.
Cost-Effective Solutions: Affordable pricing models to fit varying budgets while maintaining high standards of education.

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Learning Path

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