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Data Analyst
- Earn a recognized Data Analyst Certification to boost your career
- Learn SQL, R, Python, data visualization, and predictive analytics skills
- Get hands-on experience with the latest tools and work on real-world projects
- Earn IBM certificates and benefit from Masterclasses by IBM experts
Next cohort Starts
7th Jan, 2025
Learning Format
Live, Online, Interactive
Program duration
11 months
Why Join this Program
Rdx Advantage
Access hackathons, masterclasses, and AMA sessions. Earn Rdx certificates for Rdx courses.
Rdx Advantage
Access hackathons, masterclasses, and AMA sessions. Earn Rdx certificates for Rdx courses.
Rdx Advantage
Access hackathons, masterclasses, and AMA sessions. Earn Rdx certificates for Rdx courses.
Rdx Advantage
Access hackathons, masterclasses, and AMA sessions. Earn Rdx certificates for Rdx courses.
Class Room Images Training Institute
Class room
We have Physical instructor led classes happening at Himayath Nagar , Ameerept & Hitech City Branches, Hyderabad.
E - Learning
We have recorded videos of the trainer . This videos were recorded while taking the class.
Class room
We have Physical instructor led classes happening at Himayath Nagar , Ameerept & Hitech City Branches, Hyderabad.
Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Masterclasses from IBM experts
- Capstone from 3 domains and 20+ projects
- Program crafted to initiate your journey as a Data Analyst
- Industry-recognized Data Analyst Master’s certificate from Simplilearn
- Industry-recognized IBM certifications for Rdx courses
- Capstone from 3 domains and 20+ projects
- Exclusive hackathons conducted by rdx
- Dedicated live sessions by faculty of industry experts
- Ask-Me-Anything (AMA) sessions with IBM leadership
- Lifetime access to self-paced learning content
Ready to accelerate your career?
Ready to accelerate your career? Rdx courses are designed to equip you with the skills that employers value. Whether you’re looking to upskill, change careers, or simply learn something new, we are here to help.
Data Analyst Certification Program Advantage
Get certified in data analysis with this IBM program. Access masterclasses by experts, and AMAs with leadership. Earn Data Analyst and IBM certificates plus complete capstone projects. Advance your career now!
Earn your Data Analyst Certificate
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Masterclasses from IBM experts
- Capstone from 3 domains and 20+ projects
- Program crafted to initiate your journey as a Data Analyst
About Online Data Analyst Course
Upon completing the Data Analyst certification course, you will have the data analysis skills necessary to get your dream job in the data analytics space. Apart from Data Analyst, other jobs titles include:
- Data Analytics Manager/Lead
- Business Analyst/Senior Business Analyst
- Business Intelligence Analyst
- Business Intelligence Engineer
- Various managerial roles
In this Data Analyst certification course, you will learn the latest analytics tools and techniques, how to work with SQL databases and basic sql queries, the programming language of R and Python, raw data manipulation, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment.
Upon completing the Data Analyst certification course, you will have the data analysis skills necessary to get your dream job in the data analytics space. Apart from Data Analyst, other jobs titles include:
- Data Analytics Manager/Lead
- Business Analyst/Senior Business Analyst
- Business Intelligence Analyst
- Business Intelligence Engineer
- Various managerial roles
- Data Analytics Manager/Lead
- Business Analyst/Senior Business Analyst
- Business Intelligence Analyst
- Business Intelligence Engineer
- Various managerial roles
Data Analyst Training Program Learning Path
Accelerate your career trajectory with our extensive data analyst course curriculum. Delve into foundational statistics, master data analysis with Python and R, navigate databases using SQL, and harness the power of visualization with Tableau and Power BI.
DATA ANALYSIS FOUNDATION – 6 MODULES
MODULE 1: DATA ANALYSIS FOUNDATION
• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain
MODULE 2: CLASSIFICATION OF ANALYTICS
• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics
MODULE 3: CRIP-DM Model
• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
• Modeling, Evaluation, Deploying,Monitoring
MODULE 4: UNIVARIATE DATA ANALYSIS
• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.
MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS
• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot
MODULE 6: BI-VARIATE DATA ANALYSIS
• Scatter Plots
• Regression Analysis
• Correlation Coefficients
PYTHON FOUNDATION – 4 MODULES
MODULE 1: PYTHON BASICS
• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
MODULE 2: PYTHON CONTROL STATEMENTS
• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements
MODULE 3: PYTHON DATA STRUCTURES
• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods
MODULE 4: PYTHON FUNCTIONS
• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions
STATISTICS ESSENTIALS – 4 MODULES
MODULE 1 : OVERVIEW OF STATISTICS
- Introduction to Statistics
- Descriptive And Inferential Statistics
- Basic Terms Of Statistics
- Types Of Data
MODULE 2 : HARNESSING DATA
- Random Sampling
- Sampling With Replacement And Without Replacement
- Cochran’s Minimum Sample Size
- Types of Sampling
- Simple Random Sampling
- Stratified Random Sampling
- Cluster Random Sampling
- Systematic Random Sampling
- Multi stage Sampling
- Sampling Error
- Methods Of Collecting Data
MODULE 3 : EXPLORATORY DATA ANALYSIS
- Exploratory Data Analysis Introduction
- Measures Of Central Tendencies: Mean, Median And Mode
- Measures Of Central Tendencies: Range, Variance And Standard Deviation
- Data Distribution Plot: Histogram
- Normal Distribution & Properties
- Z Value / Standard Value
- Empherical Rule and Outliers
- Central Limit Theorem
- Normality Testing
- Skewness & Kurtosis
- Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
- Covariance & Correlation
MODULE 4 : HYPOTHESIS TESTING
- Hypothesis Testing Introduction
- P- Value, Critical Region
- Types of Hypothesis Testing
- Hypothesis Testing Errors : Type I And Type Ii
- Two Sample Independent T-test
- Two Sample Relation T-test
- One Way Anova Test
- Application of Hypothesis testing
DATA ANALYSIS ASSOCIATE – 7 MODULES
MODULE 1: COMPARISION AND CORRELATION ANALYSIS
• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis
MODULE 2: VARIANCE AND FREQUENCY ANALYSIS
• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis
MODULE 3: RANKING ANALYSIS
• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis
MODULE 4: BREAK EVEN ANALYSIS
• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing
MODULE 5: PARETO (80/20 RULE) ANALSYSIS
• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis
MODULE 6: Time Series and Trend Analysis
• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis
MODULE 7: DATA ANALYSIS BUSINESS REPORTING
• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements
ADVANCED DATA ANALYTICS – 4 MODULES
MODULE 1: DATA ANALYTICS FOUNDATION
• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity
MODULE 2: OPTIMIZATION MODELS
• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity
MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION
• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel
MODULE 4: DECISION MODELING
• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling – Kickathlon Sports Retailer
PREDICTIVE ANALYTICS WITH ML – 8 MODULES
MODULE 1: DATA ANALYTICS FOUNDATION
• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity
MODULE 2: OPTIMIZATION MODELS
• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity
MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION
• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel
MODULE 4: DECISION MODELING
• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling – Kickathlon Sports Retailer
DATABASE: SQL AND MONGODB – 7 MODULES
MODULE 1: DATABASE INTRODUCTION
• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)
MODULE 2: SQL BASICS
• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation
MODULE 3: DATA TYPES AND CONSTRAINTS
• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment
MODULE 4: DATABASES AND TABLES (MySQL)
• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table
MODULE 5: SQL JOINS
• Inner join, Outer Join
• Left join, Right Join
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank
MODULE 6: SQL COMMANDS AND CLAUSES
• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries
MODULE 7: DOCUMENT DB/NO-SQL DB
• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
• MongoDB data management
BIG DATA FOUNDATION – 4 MODULES
MODULE 1: BIG DATA INTRODUCTION
• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction
MODULE 2: HDFS AND MAP REDUCE
• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort
MODULE 3: PYSPARK FOUNDATION
• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs
MODULE 4: SPARK SQL and HADOOP HIVE
• Introducing Spark SQL
• Spark SQL vs Hadoop Hive
BI ANALYST – 4 MODULES
MODULE 1: TABLEAU FUNDAMENTALS
• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies
MODULE 2: POWER-BI BASICS
• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION
MODULE 3: DATA TRANSFORMATION TECHNIQUES
• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values
MODULE 4: CONNECTING TO VARIOUS DATA SOURCES
• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model
8+ Skills Covered
- Data Analytics
- Data Visualization Tableau and Power BI
- Supervised Learning
- Data Analysis using Python and R
- Statistical Analysis using Excel
- Linear and logistic regression modules
- Unsupervised Learning
- Clustering using KMeans
Companies hiring Data Analyst
Our Clients
Join the fastest growing Rdx brand offering endless learning and growth opportunities and advance your career with us.
Manish Beniwal
Advisor Reporting - Global Mobility at Rio Tinto
I am a Data Analyst with 7 years of experience, but I hadn’t worked with Statistics much. So, I enrolled in this Data Analyst Certification course. It’s a good course, even for beginners. Overall, the training is very good. Thank you, Simplilearn.
Manish Beniwal
Advisor Reporting - Global Mobility at Rio Tinto
I am a Data Analyst with 7 years of experience, but I hadn’t worked with Statistics much. So, I enrolled in this Data Analyst Certification course. It’s a good course, even for beginners. Overall, the training is very good. Thank you, Simplilearn.
Manish Beniwal
Advisor Reporting - Global Mobility at Rio Tinto
I am a Data Analyst with 7 years of experience, but I hadn’t worked with Statistics much. So, I enrolled in this Data Analyst Certification course. It’s a good course, even for beginners. Overall, the training is very good. Thank you, Simplilearn.
Manish Beniwal
Advisor Reporting - Global Mobility at Rio Tinto
I am a Data Analyst with 7 years of experience, but I hadn’t worked with Statistics much. So, I enrolled in this Data Analyst Certification course. It’s a good course, even for beginners. Overall, the training is very good. Thank you, Simplilearn.
Our Popular Courses
Data Analyst Course FAQs
What is Data Analytics?
Data Analytics is a process of inspecting, cleaning, transforming and modeling data to discover useful information that help businesses in accurate decision-making. Data analysis is done by various methods like qualitative and quantitative methods using analytical or statistical tools. They help in extracting useful information from data, translating them into insights. Simplilearn’s Data Analyst Course covers all these aspects offering you a comprehensive understanding of the field, including its practical applications.
What is Data Analytics?
Data analysts play a unique role among the top data-centric jobs available today. A Data Analyst commonly works on data mining, collecting and interpreting data, analyzing data outcome, and using statistical tools to come up with insights that are vital to informed business decision-making. The key responsibilities of a certified Data Analyst include data cleaning and organizing, performing complex computations and ensuring data integrity at all times. They analyze data and translate it into tangible insights that can be applied to various business use cases, including improving operational efficiency, business performance, and much more.
What is Data Analytics?
Data Analytics is a process of inspecting, cleaning, transforming and modeling data to discover useful information that help businesses in accurate decision-making. Data analysis is done by various methods like qualitative and quantitative methods using analytical or statistical tools. They help in extracting useful information from data, translating them into insights. Simplilearn’s Data Analyst Course covers all these aspects offering you a comprehensive understanding of the field, including its practical applications.
What is Data Analytics?
Data Analytics is a process of inspecting, cleaning, transforming and modeling data to discover useful information that help businesses in accurate decision-making. Data analysis is done by various methods like qualitative and quantitative methods using analytical or statistical tools. They help in extracting useful information from data, translating them into insights. Simplilearn’s Data Analyst Course covers all these aspects offering you a comprehensive understanding of the field, including its practical applications.