Data Analytics Course Centre in Pune | Best Data Analytics Institute in Pune
Data Analytics Course
Jivantu Tech is the best Data Analytics training institute in Pune Maharashtra, where quality is the passion and objective is knowledge to make students skillful for their better future.
Data Analytics : Data Analytics is the process of examining, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making. It is used across industries like finance, healthcare, e-commerce, IT, and manufacturing.
Data Analytics combines skills from statistics, computer science, and business domain knowledge. With the explosion of data in today's digital world, companies are heavily investing in data-driven decision making, making Data Analytics one of the most in-demand career paths globally.
Tools like SQL, Python, Power BI, and Tableau are industry standards. A Data Analyst translates raw data into actionable business insights that drive growth, optimize operations, and improve customer experiences.
Why Data Analytics is the Future Data is the new oil. Every organization - from startups to Fortune 500 companies - is collecting massive amounts of data. The ability to analyze this data and extract meaningful insights is what separates successful businesses from the rest. Data Analysts are the bridge between raw data and strategic decisions, making this one of the most secure and rewarding career paths in the 21st century.
Types of Data Analytics
Descriptive Analytics: "What happened?" – Summarizes historical data using dashboards, reports, and visualizations.
Diagnostic Analytics: "Why did it happen?" – Digs deeper to find root causes using drill-downs and correlation analysis.
Predictive Analytics: "What will happen?" – Uses historical data and machine learning to forecast future trends.
Prescriptive Analytics: "What should we do?" – Recommends actions based on predictive insights using optimization algorithms.
Where Data Analytics Is Used ?
E-commerce & Retail: Customer segmentation, sales forecasting, inventory optimization, recommendation engines.
Finance & Banking: Fraud detection, risk assessment, credit scoring, investment analysis, portfolio management.
Healthcare: Patient outcome prediction, drug discovery, hospital resource optimization, disease trend analysis.
Marketing: Campaign performance tracking, customer lifetime value (LTV) analysis, sentiment analysis, A/B testing.
Manufacturing: Supply chain optimization, quality control, predictive maintenance, production efficiency analysis.
IT & Technology: User behavior analysis, system performance monitoring, cybersecurity threat detection.
Why Learn Data Analytics ?
High Demand: Every industry needs Data Analysts. It's one of the fastest-growing job roles globally.
Great Salary Packages: Entry-level analysts earn competitive salaries with rapid growth potential.
Career Versatility: Skills are transferable across domains – finance, healthcare, retail, IT, and more.
Future-Proof Career: With AI and automation, data-driven decision-making will only become more critical.
Work with Cutting-Edge Tools: Get hands-on with SQL, Python, Power BI, Tableau, and cloud platforms.
Impact Business Decisions: Your insights will directly influence strategy, growth, and profitability.
Tools & Technologies Covered in Data Analytics Course
Module 1: Data Analytics Introduction
Data Analytics kya hai?
Types of Analytics – Descriptive, Diagnostic, Predictive, Prescriptive
Data Analytics Life Cycle
Business Problems ko Data se Solve karna
Data-driven Decision Making
Module 2: Microsoft Excel
Excel Basics – Formulas & Functions
IF, SUMIF, COUNTIF
VLOOKUP, HLOOKUP, XLOOKUP
INDEX + MATCH
Conditional Formatting
Data Validation
Pivot Tables & Pivot Charts
Dashboards in Excel
Advanced Excel Tricks
Module 3: Statistics
Mean, Median, Mode
Variance & Standard Deviation
Percentiles
Probability Basics
Normal Distribution
Correlation
Regression Basics
Sampling
Hypothesis Testing
Confidence Interval
Module 4: SQL (Database)
Introduction to Databases
SELECT, WHERE, ORDER BY
GROUP BY, HAVING, LIMIT
Aggregate Functions (SUM, AVG, COUNT, MAX, MIN)
JOINs – INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
Subqueries
CTE (Common Table Expressions)
Window Functions (RANK, ROW_NUMBER, LAG, LEAD)
Views & Stored Procedures (Basic)
Module 5: Python for Data Analytics
Python Basics – Variables, Data Types, Loops
Functions & File Handling
Exception Handling
Object-Oriented Programming (Basic)
Libraries – NumPy, Pandas, Matplotlib, Seaborn
Pandas – DataFrame, Series, Data Cleaning
Pandas – Merge, GroupBy, Pivot
Pandas – Filtering, Sorting
Module 6: Data Cleaning
Handling Missing Values
Duplicate Data Removal
Outlier Detection & Treatment
Data Transformation
Feature Engineering (Basic)
Encoding & Scaling
Module 7: Data Visualization
Bar Chart, Pie Chart, Histogram
Scatter Plot, Box Plot, Heatmap
Interactive Dashboards
Module 8: Power BI
Power BI Introduction & Data Import
Power Query – Data Cleaning
Data Modeling & Relationships
DAX Basics – Calculated Columns & Measures
KPIs, Slicers, Dashboard Design
Publishing Reports
Module 9: Tableau (Optional but Valuable)
Tableau Basics
Charts, Filters, Parameters
Dashboards & Storytelling
Module 10: Business Intelligence
KPIs & Business Metrics
Dashboard Design & Report Building
Business Case Studies
Module 11: Machine Learning Basics
Supervised Learning vs Unsupervised Learning
Linear Regression
Logistic Regression
Decision Trees
Clustering (K-Means)
Model Evaluation (RMSE, Accuracy, Precision, Recall)
Module 12: Real-World Projects
Sales Dashboard
HR Analytics – Employee Attrition Analysis
Customer Churn Analysis
E-commerce Analytics
Banking Dashboard – Loan & Risk Analysis
Hospital Analytics – Patient Data Analysis
Financial Dashboard – Profit & Loss Analysis
Marketing Analytics – Campaign Performance
Module 13: Interview Preparation
SQL Interview Questions
Excel Interview Questions
Python Interview Questions
Power BI Interview Questions
Statistics Questions for Data Analyst
Case Studies & Problem Solving
Resume Building & Portfolio Creation
Mock Interviews
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