Data Analytics Training in India

Credo Systemz is the No:1 Software training institute in India which offers the best Data Analytics training for transforming aspirants into data analytics professionals.

The data analytics course focuses on applying analytics to real-world business problems through projects and case studies.
Interactive data analytics training covers statistics, SQL, Excel, data visualization and Power BI.
Live hands-on weekdays & weekends Classroom/online Training with placement support.

Flexible Mode of Training

Online Training
Corporate Training
Class Room Training
1V1 / Personal Training

Data
Analytics

Case Studies and Projects15+
Hours of Practical Training80+
Placement Assurance100%
Expert Support24/7
Support & AccessLifetime
CertificationYes

Click here to view detailed Syllabus

Data Analytics Training

Download Syllabus

What is Data Analytics?
Types of Data Analytics
The Data Analytics Process
Importance of Data Analytics in Business
Tools and Technologies in Data Analytics
Real-World Examples
Career scope and job roles in Data Analytics

Introduction to Excel
Understanding Cell Referencing
Basic Arithmetic and Logical Operations
Data Cleaning and Formatting
Data Validation & Drop-downs
Flash Fill and AutoFill
Functions and Formulas
Array Formulas & Dynamic Arrays (FILTER, SORT, UNIQUE)
Pivot Tables and Charts
Slicers and Timelines for Interactive Filtering
Conditional Formatting
Dynamic Formatting Based on Cell Value or Date
Dashboard Creation
Combining Charts, KPIs, and Sparklines
Linking Pivot Tables with Slicers
Introduction to Macros and VBA
Workbook Protection and Data Security

Hands-on Practical Exercises

Clean and Analyze Raw Sales Data
Create Interactive Employee Dashboard
Monthly Report Automation using Formulas and Pivot Tables
KPI Dashboard for Marketing Metrics

Introduction to Oracle Database
Introduction to RDBMS (MySQL, PostgreSQL, SQL Server)
Understanding Tables, Rows, Columns
SQL Syntax, Case Sensitivity, Comments
SQL Commands
Using Aliases
Filtering and Logic
Aggregations & Grouping
Difference between WHERE vs HAVING
Joins – Inner, Left, Right, Full Outer, Self, Cross Join
Subqueries & Nested Queries
Window (Analytic) Functions
DML – Data Manipulation Language
DDL – Data Definition Language
Time Series Analysis
Revenue Analysis with Filters and Joins
Customer Segmentation using SQL

Hands-on Practical Exercises

Create & Query a Sales Database
Build a Regional Revenue Report
Customer Insights
Employee Performance Ranking

Importance of Statistics in Data Analytics
Descriptive Statistics: Mean, Median, Mode, Range, Variance, Std. Deviation
Data Summarization
Data Visualization
Using Visualizations for Outlier Detection
Probability Concepts
Types of Events
Addition & Multiplication Rules
Conditional Probability
Probability Distributions
Central Limit Theorem
Inferential Statistics
Hypothesis Testing
Correlation and Regression
Exploratory Data Analysis with Statistics

Hands-on Practical Exercises

Customer Satisfaction Analysis
Ad Spend vs Sales
Product Quality Check
Delivery Time Comparison

Introduction to Power BI
Installing Power BI Desktop
Power BI Interface
Data Loading & Importing from Various Sources
Understanding Power BI File Types
Power Query – Data Transformation
Cleaning and Shaping Data
Filtering and Sorting Data
Unpivoting and Pivoting Data
Data Modeling
Creating Date Table & Time Intelligence
DAX Basics: SUM, COUNT, DISTINCT, AVERAGE
Logical, Aggregation and Filter Functions
Data Visualization: Bar, Column, Line, Pie, Donut
Advanced Charts: TreeMap, Funnel, Waterfall, Gauge, KPI
Slicers and Filters
Dashboard and Report Design
Power BI Service
Row-Level Security

Hands-on Practical Exercises

Customer Segmentation Report
E-commerce Product Performance
Marketing Campaign Analysis
Sales Dashboard

Introduction to Python
Why Python for Data Analytics?
Python Syntax and Code Structure
Arithmetic & Logical Operators
Conditional Statements
Loops & Functions
Error Handling
Data Structures in Python
NumPy – Numerical Python
NumPy Arrays vs Lists
Statistical Functions: mean(), std(), sum()
Pandas – Data Handling Library
Visual EDA with Pandas
Indexing, Filtering, and Slicing
GroupBy and Aggregations
Sorting, Renaming Columns
Data Cleaning and Preparation
Data Visualization with Python
Statistical Analysis with Python

Hands-on Practical Exercises

Analyze sales data to find top-performing products
Clean messy customer data and find duplicates
Segment customers by spending habits using Pandas
Automate data reports using Python scripting

Handling Missing Data: Imputation, Deletion
Data Normalization and Standardization
Detecting and Handling Outliers
Feature Engineering
EDA: Distribution Analysis, Correlation, Feature Selection

Hands-on Practical Exercises

Clean and prepare a messy dataset for analysis.
Perform a thorough EDA, identifying key trends and insights.

AI for Data Analytics: Automated Insights, Predictive Analytics
Using AI tools like ChatGPT for Data Analysis
AI-Powered Data Wrangling
Predictive Models: Introduction to Basic Machine Learning Algorithms

Hands-on Practical Exercises

Use AI tools to automate data cleaning or feature engineering on a dataset.
Build a simple predictive model using an AI tool.

Flexible Mode of Training and Payment

Data Analytics Course FAQs

Data Analytics is about turning data into meaningful information to find trends, patterns, and insights that can help in making better decisions.

Technical Skills:

Excel/Google Sheets: Pivot tables, formulas, charts
SQL: Query databases to extract data
Python/R: Data cleaning, analysis, and visualization
Data Visualization: Power BI, Tableau, or Matplotlib/Seaborn
Statistics: Mean, median, mode, standard deviation, probability

Credo Systemz offers data analytics training to gain essential skills through 60+ hours of live expert-led sessions.

Yes, you can become a Data Analyst without a technical background by learning key skills like Excel, SQL, and data visualization. The course is designed for learners from all backgrounds.

Data Analytics focuses on interpreting existing data to find patterns, trends, and insights, while Data Science also involves building predictive models and machine learning solutions.

In India, the average salary of a Data Analyst ranges from ₹2.0 Lakhs to ₹14.0 Lakhs per year. Experienced professionals can earn up to ₹18.5–₹26.0 Lakhs per year, depending on skills and company.

Career Opportunities:

Data Analyst
BI Analyst
Reporting Specialist
Business Analyst
Data Visualization Specialist

Industries such as IT, finance, healthcare, and retail hire data analysts for reporting, dashboard creation, and business insights.

To start your Data Analytics career, learn Excel, SQL, Python/R basics, and data visualization tools. Practice on sample datasets and join Credo Systemz Data Analytics Training to gain real-time experience.

Credo Systemz offers affordable Data Analytics courses suitable for students, professionals, and non-IT learners. Exclusive offers and discounts are provided regularly for all aspirants.

Data Analytics has a growing demand in every industry as companies depend on data-driven decisions for success. Emerging technologies like AI, IoT, and Cloud Computing further increase the demand for skilled analysts.