Business Analytics: Principles and Practice with Microsoft Excel and Python | Pavankumar Gurazada & Seema Gupta  | Vikas Publishing | Edittion 2026

Business Analytics: Principles and Practice with Microsoft Excel and Python | Pavankumar Gurazada & Seema Gupta | Vikas Publishing | Edittion 2026

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Business Analytics: Principles and Practice with Microsoft Excel and Python | Pavankumar Gurazada & Seema Gupta  | Vikas Publishing | Edittion 2026

Business Analytics: Principles and Practice with Microsoft Excel and Python | Pavankumar Gurazada & Seema Gupta | Vikas Publishing | Edittion 2026

β‚Ή 580.00
Sale price  β‚Ή 580.00 Regular price  β‚Ή 725.00
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πŸ“˜ Business Analytics: Principles and Practice with Microsoft Excel and Python | Pavankumar Gurazada & Seema Gupta | Vikas Publishing | Edition 2026 Business Analytics: Principles and Practice with Microsoft Excel and Python by Pavankumar Gurazada & Seema Gupta, published by Vikas Publishing, is a practical and application-oriented textbook that introduces students to the fundamentals of Business Analytics, data analysis, statistical techniques, Microsoft Excel and Python. The book helps learners understand how data can be collected, processed, analysed and interpreted to support better business decisions. ⭐ Best Overall 🏒 Publisher: Vikas Publishing ✍️ Authors: Pavankumar Gurazada & Seema Gupta πŸ“š...
PRODUCT DESCRIPTION οΌ‹

πŸ“˜ Business Analytics: Principles and Practice with Microsoft Excel and Python | Pavankumar Gurazada & Seema Gupta | Vikas Publishing | Edition 2026

Business Analytics: Principles and Practice with Microsoft Excel and Python by Pavankumar Gurazada & Seema Gupta, published by Vikas Publishing, is a practical and application-oriented textbook that introduces students to the fundamentals of Business Analytics, data analysis, statistical techniques, Microsoft Excel and Python. The book helps learners understand how data can be collected, processed, analysed and interpreted to support better business decisions.


⭐ Best Overall

🏒 Publisher: Vikas Publishing

✍️ Authors: Pavankumar Gurazada & Seema Gupta

πŸ“š Edition: 2026

πŸ“– Category: Business Analytics | Data Analytics | Business Intelligence | Microsoft Excel | Python | Statistics | Data-Driven Decision Making

🎯 Suitable For: B.Com Students | BBA Students | MBA Students | Management Students | Commerce Students | Business Analytics Students | Data Analytics Beginners | Professional Courses


πŸš€ Why This Book is Important

πŸ‘‰ One fundamental principle:

πŸ“Œ "Business Analytics transforms raw business data into meaningful insights that help organisations make informed, efficient and data-driven decisions."

πŸ‘‰ This book helps readers understand:

βœ”οΈ Business Analytics Fundamentals

βœ”οΈ Data Analysis

βœ”οΈ Descriptive Statistics

βœ”οΈ Data Visualization

βœ”οΈ Microsoft Excel

βœ”οΈ Excel-Based Analytics

βœ”οΈ Python for Analytics

βœ”οΈ Data Interpretation

βœ”οΈ Statistical Analysis

βœ”οΈ Business Decision Making

βœ”οΈ Predictive Analytics Concepts

πŸ“Œ Data + Excel + Python + Analytics = Data-Driven Business Decisions


πŸ“–Β Β Description (Complete Guide to Business Analytics)

πŸ“Š 1. Introduction to Business Analytics

βœ”οΈ Covers:

  • Business Analytics

  • Importance of Data

  • Analytics in Business

  • Data-Driven Decision Making

  • Business Intelligence

  • Role of Analytics in Management

βœ”οΈ Provides a strong foundation for understanding how analytics can be applied to real-world business problems.


πŸ“ˆ 2. Types of Business Analytics

βœ”οΈ Introduces:

  • Descriptive Analytics

  • Diagnostic Analytics

  • Predictive Analytics

  • Prescriptive Analytics

βœ”οΈ Helps students understand how different forms of analytics answer different business questions.

πŸ“Œ What Happened? β†’ Why It Happened? β†’ What May Happen? β†’ What Should We Do?


πŸ—‚οΈ 3. Data & Business Decision Making

βœ”οΈ Covers concepts related to:

  • Business Data

  • Data Sources

  • Data Collection

  • Data Preparation

  • Data Quality

  • Data Interpretation

  • Decision Making

βœ”οΈ Explains how businesses can convert raw information into actionable insights.


πŸ“Š 4. Data Preparation & Analysis

βœ”οΈ Covers:

  • Data Cleaning

  • Data Organisation

  • Data Classification

  • Data Transformation

  • Missing Data

  • Data Validation

  • Data Preparation

βœ”οΈ Helps students understand why clean and structured data is essential for reliable analytics.


πŸ“‰ 5. Descriptive Statistics

βœ”οΈ Covers:

  • Mean

  • Median

  • Mode

  • Range

  • Variance

  • Standard Deviation

  • Measures of Central Tendency

  • Measures of Dispersion

βœ”οΈ Helps learners summarise and interpret business datasets using statistical measures.


πŸ“ 6. Statistical Analysis for Business

βœ”οΈ Covers concepts related to:

  • Probability

  • Statistical Distributions

  • Correlation

  • Regression

  • Sampling

  • Statistical Interpretation

βœ”οΈ Connects statistical methods with practical business applications.


πŸ’» 7. Microsoft Excel for Business Analytics

βœ”οΈ Covers practical applications of Microsoft Excel for:

  • Data Organisation

  • Data Analysis

  • Calculations

  • Statistical Analysis

  • Data Visualization

  • Business Reporting

βœ”οΈ Helps students use Excel as a powerful tool for analysing business data.

πŸ“Œ Excel + Business Data = Practical Analytics


πŸ“Š 8. Excel Functions & Analytical Tools

βœ”οΈ Introduces practical Excel-based techniques such as:

  • Formulas

  • Functions

  • Data Sorting

  • Data Filtering

  • Charts

  • Tables

  • Pivot Tables

  • Data Analysis

βœ”οΈ Helps students develop practical spreadsheet-based analytical skills.


πŸ“ˆ 9. Data Visualization

βœ”οΈ Covers:

  • Charts

  • Graphs

  • Tables

  • Visual Data Representation

  • Business Dashboards

  • Analytical Reporting

βœ”οΈ Explains how visualisation can make complex datasets easier to understand and communicate.

πŸ“Œ Good Visualization = Better Understanding of Data


🐍 10. Introduction to Python for Business Analytics

βœ”οΈ Introduces Python as a tool for:

  • Data Analysis

  • Data Processing

  • Statistical Analysis

  • Data Visualization

  • Business Analytics

βœ”οΈ Helps beginners understand how Python can complement spreadsheet-based analytics.


πŸ’» 11. Python Programming Fundamentals

βœ”οΈ Introduces fundamental programming concepts such as:

  • Variables

  • Data Types

  • Operators

  • Conditional Statements

  • Loops

  • Functions

  • Data Structures

βœ”οΈ Provides the programming foundation needed for performing data analysis with Python.


🐍 12. Python for Data Analysis

βœ”οΈ Covers practical concepts related to:

  • Data Handling

  • Data Manipulation

  • Data Analysis

  • Structured Data

  • Analytical Workflows

βœ”οΈ Helps learners understand how Python can be used to process and analyse business datasets.


πŸ“Š 13. Python-Based Data Visualization

βœ”οΈ Covers concepts related to:

  • Graphical Representation

  • Data Visualization

  • Analytical Charts

  • Business Data Presentation

βœ”οΈ Helps students communicate analytical findings through visual representations.


πŸ” 14. Business Data Interpretation

βœ”οΈ Covers:

  • Data Interpretation

  • Business Insights

  • Analytical Findings

  • Trend Identification

  • Pattern Recognition

  • Decision Support

βœ”οΈ Helps students move from numerical analysis to meaningful business conclusions.


πŸ“ˆ 15. Predictive Analytics

βœ”οΈ Introduces concepts related to:

  • Forecasting

  • Prediction

  • Regression

  • Trends

  • Business Forecasts

  • Predictive Decision Making

βœ”οΈ Explains how historical data can be used to identify patterns and support future business decisions.


🏒 16. Applications of Business Analytics

βœ”οΈ Business Analytics can be applied to areas such as:

  • Marketing

  • Finance

  • Human Resources

  • Sales

  • Operations

  • Supply Chain

  • Customer Analytics

  • Strategic Management

βœ”οΈ Helps students understand the practical relevance of analytics across different business functions.


🎯 17. Data-Driven Decision Making

βœ”οΈ Covers:

  • Business Problems

  • Data-Based Decisions

  • Analytical Thinking

  • Performance Measurement

  • Business Insights

  • Strategic Decisions

βœ”οΈ Connects analytical techniques with practical managerial decision-making.

πŸ“Œ Analyse β†’ Interpret β†’ Decide β†’ Improve


πŸŽ“ Academic & Professional Relevance

βœ”οΈ Useful for:

  • B.Com Students

  • BBA Students

  • MBA Students

  • Management Students

  • Commerce Students

  • Business Analytics Students

  • Data Analytics Beginners

  • Business Intelligence Learners

  • Professional Courses

βœ”οΈ Particularly useful for learners who want to develop practical skills in Excel, Python, statistics and business data analysis.


🧠 Examination & Practical Learning

βœ”οΈ Business Analytics concepts

βœ”οΈ Types of Analytics

βœ”οΈ Descriptive Statistics

βœ”οΈ Data Preparation

βœ”οΈ Excel Functions

βœ”οΈ Pivot Tables

βœ”οΈ Data Visualization

βœ”οΈ Python Fundamentals

βœ”οΈ Data Analysis

βœ”οΈ Correlation & Regression

βœ”οΈ Predictive Analytics

βœ”οΈ Business Decision Making

πŸ“Œ Concepts + Excel Practice + Python Practice + Data Interpretation = Strong Business Analytics Preparation


⭐ Why This Book is Highly Recommended

βœ”οΈ Comprehensive introduction to Business Analytics

βœ”οΈ Edition 2026

βœ”οΈ Published by Vikas Publishing

βœ”οΈ Written by Pavankumar Gurazada & Seema Gupta

βœ”οΈ Combines conceptual understanding with practical analytics

βœ”οΈ Covers Microsoft Excel

βœ”οΈ Introduces Python

βœ”οΈ Covers statistical analysis

βœ”οΈ Explains data preparation and interpretation

βœ”οΈ Includes data visualization concepts

βœ”οΈ Introduces predictive analytics

βœ”οΈ Connects analytics with business decision-making

βœ”οΈ Useful for Commerce and Management students

βœ”οΈ Suitable for beginners learning business analytics

πŸ‘‰ This book is an excellent choice for students who want to understand Business Analytics while developing practical skills using Microsoft Excel and Python.


🧠 Smart Learning Strategy

βœ”οΈ Start with the fundamentals of Business Analytics

βœ”οΈ Understand the four major types of analytics

βœ”οΈ Learn data preparation before analysis

βœ”οΈ Master basic statistical concepts

βœ”οΈ Practise Excel formulas and analytical tools

βœ”οΈ Learn to create meaningful charts and visualisations

βœ”οΈ Build Python fundamentals gradually

βœ”οΈ Practise data analysis using Python

βœ”οΈ Connect analytical results with real business problems

βœ”οΈ Focus on interpretation rather than calculations alone

πŸ‘‰ Golden Rule:

πŸ“Œ "Learn the concept, practise it with Excel, apply it with Python and finally interpret the results from a business perspective."


🎯 Final Verdict

βœ”οΈ Comprehensive Business Analytics textbook

βœ”οΈ Edition 2026 | Vikas Publishing

βœ”οΈ Written by Pavankumar Gurazada & Seema Gupta

βœ”οΈ Covers Business Analytics fundamentals

βœ”οΈ Explains descriptive, diagnostic, predictive and prescriptive analytics

βœ”οΈ Covers data preparation and analysis

βœ”οΈ Includes statistical techniques

βœ”οΈ Provides practical Microsoft Excel applications

βœ”οΈ Covers Excel-based data analysis and visualization

βœ”οΈ Introduces Python for Business Analytics

βœ”οΈ Covers Python fundamentals and data analysis

βœ”οΈ Explains data visualization

βœ”οΈ Introduces predictive analytics

βœ”οΈ Covers data-driven business decision-making

βœ”οΈ Connects analytics with Marketing, Finance, HR, Sales and Operations

πŸ‘‰ A complete guide to Business Analytics covering data analysis, descriptive statistics, data preparation, Microsoft Excel, Excel functions, Pivot Tables, data visualization, Python, statistical analysis, correlation, regression, predictive analytics and data-driven decision making for B.Com, BBA, MBA, Management, Commerce and Business Analytics students.


BuyΒ Business Analytics: Principles and Practice with Microsoft Excel and Python by Pavankumar Gurazada & Seema Gupta, published by Vikas Publishing, Edition 2026. A practical Business Analytics textbook covering data analysis, statistics, Microsoft Excel, data visualization, Python, predictive analytics and data-driven decision making, ideal for B.Com, BBA, MBA and Management students.


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Business Analytics: Principles and Practice with Microsoft Excel and Python featuring business analytics, descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, data preparation, statistics, Excel functions, Pivot Tables, data visualization, Python programming, data analysis, correlation, regression, forecasting and data-driven decision making for B.Com, BBA, MBA, Commerce, Management and Business Analytics students.

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