Business_Analytics_Course_Slide_2_Introduction_to_Data_Science


COURSE INSTRUCTOR

Data_Science_Instructor_Sandip_Gadekar

Sandip Gadekar

Business_Analytics Instructor
★★★★★ (4.9)

Sandip Gadekar has over 1+ year of experience in Business Analytics, specializing in Excel, SQL, Power BI, Python, Data Visualization, Business Intelligence, and Reporting. With a strong understanding of data analysis and business processes, he helps transform raw data into meaningful insights for informed decision-making. His expertise includes dashboard creation, KPI analysis, data reporting, and business performance tracking. Passionate about teaching, he focuses on practical learning, real-world case studies, and hands-on projects to help students build job-ready business analytics skills.

BASIC INFORMATION


  • Duration : 3 Months
  • Level : Basic to Advanced
  • Category : Technology
  • Class Mode : Online/Offline
  • Started : 1st / 15th Every Month
  • Daily Time : 10:00 AM to 4:00 PM
  • Days : Mon - Fri
  • Class Strength: 10 / Per Batch


Course Description

The Business Analytics Course helps learners develop skills in data analysis, business reporting, and decision-making. Students learn how to collect, analyze, and interpret data to solve real-world business problems and support organizational growth.

The course provides hands-on training in tools such as Excel, SQL, Power BI, and Python. Learners gain practical experience in data visualization, dashboard creation, and intelligence techniques used across industries.

Through projects and case studies, students build analytical and problem-solving skills while preparing for careers as Business Analysts, Data Analysts, and Business Intelligence professionals.

Course Syllabus

Module 1: Introduction to Business Analytics

  1. Introduction to Business Analytics
  2. Importance of Business Analytics in Organizations
  3. Data-Driven Decision Making
  4. Types of Business Analytics
  5. Business Analytics Lifecycle
  6. Role and Responsibilities of a Business Analyst
  7. Business Analytics vs Data Analytics
  8. Understanding Business Problems and Requirements
  9. Key Business Metrics and KPIs
  10. Introduction to Data Sources and Data Collection
  11. Overview of Business Intelligence and Reporting
  12. Introduction to Analytics Tools (Excel, SQL, Power BI, Python)
  13. Business Analytics Applications Across Industries
  14. Career Opportunities in Business Analytics
  15. Case Studies and Real-World Business Scenarios
  1. Introduction to Databases and DBMS
  2. Understanding Relational Databases
  3. Database Tables, Rows, and Columns
  4. SQL Fundamentals and Syntax
  5. Creating and Managing Databases
  6. Data Types and Constraints
  7. CRUD Operations (Create, Read, Update, Delete)
  8. Filtering Data with WHERE Clause
  9. Sorting Data Using ORDER BY
  10. Aggregate Functions (SUM, AVG, COUNT, MIN, MAX)
  11. GROUP BY and HAVING Clauses
  12. Joins (INNER, LEFT, RIGHT, FULL)
  13. Subqueries and Nested Queries
  14. Views, Indexes, and Stored Procedures
  15. Database Management Project and Case Study
  1. Introduction to Power BI
  2. Installing and Setting Up Power BI Desktop
  3. Understanding Power BI Interface and Components
  4. Connecting to Various Data Sources
  5. Data Import and Data Transformation with Power Query
  6. Data Cleaning and Preparation Techniques
  7. Data Modeling and Relationships
  8. Introduction to DAX (Data Analysis Expressions)
  9. Creating Calculated Columns and Measures
  10. Building Interactive Reports and Dashboards
  11. Creating Charts, Graphs, and Visualizations
  12. Using Filters, Slicers, and Drill-Down Features
  13. KPI Tracking and Business Performance Reporting
  14. Publishing and Sharing Reports in Power BI Service
  15. Real-World Business Analytics Dashboard Project
  1. Introduction to Tableau and Data Visualization
  2. Understanding Tableau Interface and Workspace
  3. Connecting to Various Data Sources
  4. Data Preparation and Cleaning in Tableau
  5. Working with Dimensions and Measures
  6. Creating Basic Charts and Graphs
  7. Building Interactive Dashboards
  8. Creating Stories and Presentations
  9. Applying Filters, Parameters, and Calculated Fields
  10. Data Blending and Joins in Tableau
  11. Advanced Visualizations and Analytics
  12. Geographical Maps and Location-Based Analysis
  13. Dashboard Design Best Practices
  14. Publishing and Sharing Tableau Reports
  15. Real-World Projects and Case Studies
  1. Introduction to Python for Business Analytics
  2. Python Installation and Development Environment Setup
  3. Python Basics: Variables, Data Types, and Operators
  4. Control Statements and Loops
  5. Functions and Modules in Python
  6. Working with NumPy for Numerical Computing
  7. Data Manipulation with Pandas
  8. Data Cleaning and Preprocessing Techniques
  9. Exploratory Data Analysis (EDA)
  10. Data Visualization with Matplotlib
  11. Data Visualization with Seaborn
  12. Working with Excel and CSV Files
  13. Introduction to Statistical Analysis in Python
  14. Business Analytics Case Studies Using Python
  15. Hands-on Projects and Practical Applications
  1. Introduction to Artificial Intelligence (AI)
  2. Overview of Advanced Analytics
  3. Machine Learning Fundamentals
  4. Supervised and Unsupervised Learning
  5. Predictive Analytics Techniques
  6. Introduction to Generative AI
  7. AI Applications in Business Analytics
  8. Customer Segmentation and Recommendation Systems
  9. Forecasting and Trend Analysis
  10. Natural Language Processing (NLP) Basics
  11. Working with AI-Powered Analytics Tools
  12. Automation and Intelligent Decision-Making
  13. Ethics and Responsible Use of AI
  14. Real-World AI & Analytics Case Studies
  15. Capstone Project: AI-Driven Business Insights
  1. Introduction to Real-World Business Projects
  2. Project Planning and Requirement Gathering
  3. Problem Identification and Business Understanding
  4. Data Collection and Data Preparation
  5. Data Cleaning and Validation Techniques
  6. Exploratory Data Analysis (EDA)
  7. Business Metrics and KPI Identification
  8. Dashboard Design and Development
  9. Data Visualization Best Practices
  10. Generating Business Insights and Recommendations
  11. Report Creation and Documentation
  12. Project Testing and Validation
  13. Project Presentation and Stakeholder Communication
  14. Portfolio Building and Project Deployment
  15. Capstone Project and Final Evaluation

Real-World Student Projects


Explore the outstanding student projects and practical work, showcasing their skills and creativity in real-world scenarios. Discover how our students apply their knowledge through innovative and hands-on experiences.

Personalized_Data_Analytics_Course_Guidance

One-To-One Data Analytics Course Guidance

Our 1-to-1 guidance for the Data Analytics course offers a highly personalized learning experience with a 100% placement guarantee. Tailored to your individual needs, this course provides expert instruction on data cleaning, visualization, and statistical analysis. Benefit from hands-on projects that apply real-world data to solve practical problems. Our mentors offer targeted feedback and support, while our dedicated placement team helps you navigate job applications, optimize your resume, and prepare for interviews. With this comprehensive approach, you’ll develop the skills and confidence needed to excel in data analytics and secure a position in the competitive job market.

Customized Curriculum: Learning plan designed to align with your experience level and career goals. Direct access to seasoned data analysts for personalized guidance.

  • Personalized Curriculum
  • Expert Mentorship
  • Practical Projects
  • Skill Development
  • Portfolio Creation
  • Placement Support
Sandip_Gadekar_Founder_and_Director

Sandip Gadekar

Founder and Director

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