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Data Analytics Online Course

Data Analytics Online Course with 100% Placement Support

Our Data Analytics Course in India is designed for students, freshers, and working professionals who want to understand data and use it for business decisions. Data Analyst Online Course starts from the basics & slowly moves toward real-world data analysis work used.

Duration: 12 - 15 Week | Mode: Live + Recorded Sessions

Data Analytics Course Demo Videos

You can attend a demo session of our Data Analytics Course before enrolling. Demo helps you understand how live classes are conducted.

Our Recently Data Analyst Course Placed Students

Riya Malhotra

Placed at Cognizant

Amit Joshi

Placed at IBM

Neha

Placed at Deloitte

Kunal Patil

Placed at Capgemini

Pooja

Placed at Accenture

Rohit

Placed at Wipro

Sneha Kulkarni

Placed at Infosys

Aarav Mehta

Placed at TCS

Data Analytics Online Course Videos

About the Data Analyst Online Course

The Data Analyst Course explains how data is collected, cleaned, and studied to support business decisions. This Data Analyst Online Course focuses on real business problems and how data is used daily in companies.

Training Highlights
  • Live online classes by experienced trainers
  • Practical exercises with real data
  • Real business use cases
  • Job-oriented learning
  • Resume and interview preparation
  • Placement support

What You Get

  • Live instructor-led sessions
  • Class recordings for revision
  • Practical assignments
  • Interview and resume guidance

Course Design & Approved By

Nasscom & Wipro

What Will You Learn in Data Analyst Course?

This Data Analysis Online Course is taught in a simple and clear way. Every topic is explained with examples so you understand both concepts and real usage.

Core Modules Covered

  • Basics of data analysis
  • Working with data
  • Data cleaning and preparation
  • Data analysis techniques
  • Creating reports and insights

Advanced Topics & Projects

  • Data reporting
  • Data comparison and trends
  • Improving data accuracy
  • Real-time data analysis projects
  • Business-based case studies

Download Curriculum

Get a peek through the entire curriculum designed that ensures Placement Guidance

Course Design By

nasco wp

Course Offered By

Why Choose Our Data Analyst Course Material & Resources?

  • Easy training videos
  • Simple study notes
  • Real-world examples
  • Practice assignments
  • Interview questions

Benefits of Joining Our Data Analyst Online Course

  • Learn from experienced trainers
  • Work on real data analysis projects
  • Lifetime access to learning material
  • Recorded sessions for revision
  • Live doubt-clearing sessions
  • Certification guidance
  • Placement Assistance
Learners Reviews

“The resume and interview support after the course was very helpful.”

— Megha Shah – Junior Data Analyst

“Recorded sessions were useful for revising topics whenever I had time.”

— Deepak Verma – Operations Executive

“This course gave me the confidence to attend interviews and answer questions clearly.”

— Pallavi Joshi – Data Analyst

“Hands-on practice helped me connect theory with real work situations.”

— Vinay Nair – Working Professional

“The trainer explained each topic patiently. Even difficult parts were easy to understand.”

— Sneha – Data Analysis Student

“The training helped me see how data is actually used for everyday business decisions.”

— Rohit Malhotra – Data Analyst
Country-Wise Data Analytics Jobs & Salary Guide

Top Job Profiles:

  • Data analyst,
  • Junior Data Analyst
  • Business Analyst
  • Data Analytics Executive

Average Salary Range:

  • INR 4 LPA - INR 7 LPA for freshers
  • INR 8 LPA - INR 15 LPA with experience
  • INR 18 LPA - INR 20+ LPA for senior roles

Top Job Profiles:

  • Data Analyst
  • Senior Data Analyst
  • Business Analyst

Average Salary Range:

  • $70,000 - $90,000 per year for beginners
  • $95,000 - $125,000 per year with experience
  • $135,000 - $140,000+ per year for senior roles

Top Job Profiles:

  • Data Analyst
  • Business Analyst
  • Senior Data Analyst

Average Salary Range:

  • £40,000 - £55,000 per year for freshers
  • £60,000 - £80,000 per year with experience
  • £90,000 - £110,000+ per year for senior roles

Top Job Profiles:

  • Data Analyst
  • Business Analyst
  • Sr. Data Analyst

Average Salary Range:

  • EUR 65,000 - EUR 85,000 per year for beginners
  • EUR 75,000 - EUR 95,000 per year with experience
  • EUR 110,000 - EUR 140,000+ per year for senior roles

Enroll Today

Start your learning journey with our Data Analysis Online Training. Enroll now and build strong data analysis skills for your career.

About the Trainer

Get coaching from an instructor with over 10 years of true industry experience as a Data Analysis Course in India and Data Analysis Online Training. Your instructor will provide you with actual industry experie

  • 10+ years of industry experience
  • Strong knowledge of data analysis
  • Conducted many online training batches
  • Practical, project-based teaching
  • Interview and career guidance
Frequently Asked Questions

Croma campus is one of the best institute for training of IT professional jobs. It is one of the most prestigious and certified organizations that has been associated with the top most MNCs. Croma campus is situated in Noida which is really famous for its innovative and technical teaching methods. So, if you want to get linked with Data Analytics then do a Collab with Croma Campus.

Data Analytics is a process of examining datasets to know about the information they contain. There are a lot of works and jobs under Data Analytics. The first thing you need to do is to always keep your profile updated on LinkedIn because they are directly associated with Data Analytics. So, if you get an Data Analytics certificate you can work as Data Analyst.

Data Analytics is nowadays becoming a very important certification that can lead you to get a good job. To get any Data Analyst job you need to get a certification in Data Analytics. There is a list of things after which you can get a certificate that contains in-depth training, many simultaneously exams, live demos, and other industrial projects that can make you a perfect Data Analyst. After all this training, you can get an Data Analytics certification.

Croma Campus India program sizes a powerful training tool that can be applied in classrooms as well as in manufacturing. We offer a wide range of agendas for Live Project Data Analytics Training in India under the leadership of the best industrial experts. We are always awarded for the past 10 years as the Best Data Analytics Online Training in India.

The ways to connect Croma Campus

  • Phone Number: - +91-120-4155255, +91-9711526942
  • Email: - info@cromacampus.com
  • Address: - G-21, Sector-03, Noida (201301)

You will be able to clean data properly, identify any errors, understand data patterns, and generate clear reports that will be helpful for company activities.

As part of this Data Analysis Online Course, you’ll actually work on real data files to correct problems, organize information, and better grasp what’s being shown in the data.

The Data Analytics Online Training also has practice problems and projects using actual business data, not just theory.

The Data Analyst Course informs learners of ways to find absent numbers and eliminate incorrect ones while ensuring that numbers are accurate before usage.

You will find out how to write simple reports to explain the results in simple terms in such a way that teams and management are able to understand.

CURRICULUM & PROJECTS

Data Analytics Training Program

    NA

    • Introduction
      • What is Data Analytic
      • Common Terms in Data Analytics
      • What is data
      • Classication of data
      • Relevance in industry and need of the hour
      • Types of problems and business objectives in various industries
      • How leading companies are harnessing the power of analytics
      • Critical success drivers.
      • Overview of Data Analytics tools & their popularity.
      • Data Analytics Methodology & problem-solving framework.
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    NA

    • Understanding Concepts of Excel
      • Creation of Excel Sheet Data
      • Range Name, Format Painter
      • Conditional Formatting, Wrap Text, Merge & Centre
      • Sort, Filter, Advance Filter
      • Different type of Chart Creations
      • Auditing, (Trace Precedents, Trace Dependents)Print Area
      • Data Validations, Consolidate, Subtotal
      • What if Analysis (Data Table, Goal Seek, Scenario)
      • Solver, Freeze Panes
      • Various Simple Functions in Excel(Sum, Average, Max, Min)
      • Real Life Assignment work
    • Ms Excel Advance
      • Advance Data Sorting
      • Multi-level sorting
      • Restoring data to original order after performing sorting
      • Sort by icons
      • Sort by colours
      • Lookup Functions
      • Subtotal, Multi-Level Subtotal
      • Grouping Features
      • Consolidation With Several Worksheets
      • Filter
      • Printing of Raw & Column Heading on Each Page
      • Workbook Protection and Worksheet Protection
      • Specified Range Protection in Worksheet
      • Excel Data Analysis
      • Data Table
      • Pivot Table
      • Generating MIS Report In Excel
      • Text Functions
      • Lookup & Reference Function
      • Logical Functions & Date and Time Functions
      • Database Functions
      • Statistical Functions
      • Financial Functions
      • Functions for Calculation Depreciation
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    NA

    • SQL Server Fundamentals
      • SQL Server 2019 Installation
      • Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
      • SQL Server Features & Purpose
      • Using Management Studio (SSMS)
      • Conguration Tools & SQLCMD
      • Conventions & Collation
    • SQL Server 2019 Database Design
      • SQL Database Architecture
      • Database Creation using GUI
      • Database Creation using T-SQL scripts
      • DB Design using Files and File Groups
      • File locations and Size parameters
      • Database Structure modications
    • SQL Tables in MS SQL Server
      • SQL Server Database Tables
      • Table creation using T-SQL Scripts
      • Naming Conventions for Columns
      • Single Row and Multi-Row Inserts
      • Table Aliases
      • Column Aliases & Usage
      • Table creation using Schemas
      • Basic INSERT
      • UPDATE
      • DELETE
      • SELECT queries and Schemas
      • Use of WHERE, IN and BETWEEN
      • Variants of SELECT statement
      • ORDER BY
      • GROUPING
      • HAVING
      • ROWCOUNT and CUBE Functions
    • Data Validation and Constraints
      • Table creation using Constraints
      • NULL and IDENTITY properties
      • UNIQUE KEY Constraint and NOT NULL
      • PRIMARY KEY Constraint & Usage
      • CHECK and DEFAULT Constraints
      • Naming Composite Primary Keys
      • Disabling Constraints & Other Options
    • Views and Row Data Security
      • Benets of Views in SQL Database
      • Views on Tables and Views
      • SCHEMA BINDING and ENCRYPTION
      • Issues with Views and ALTER TABLE
      • Common System Views and Metadata
      • Common Dynamic Management views
      • Working with JOINS inside views
    • Indexes and Query tuning
      • Need for Indexes & Usage
      • Indexing Table & View Columns
      • Index SCAN and SEEK
      • INCLUDED Indexes & Usage
      • Materializing Views (storage level)
      • Composite Indexed Columns & Keys
      • Indexes and Table Constraints
      • Primary Keys & Non-Clustered Indexes
    • Stored Procedures and Benets
      • Why to use Stored Procedures
      • Types of Stored Procedures
      • Use of Variables and parameters
      • SCHEMABINDING and ENCRYPTION
      • INPUT and OUTPUT parameters
      • System level Stored Procedures
      • Dynamic SQL and parameterization
    • System functions and Usage
      • Scalar Valued Functions
      • Types of Table Valued Functions
      • SCHEMABINDING and ENCRYPTION
      • System Functions and usage
      • Date Functions
      • Time Functions
      • String and Operational Functions
      • ROW_COUNT
      • GROUPING Functions
    • Triggers, cursors, memory limitations
      • Why to use Triggers
      • DML Triggers and Performance impact
      • INSERTED and DELETED memory tables
      • Data Audit operations & Sampling
      • Database Triggers and Server Triggers
      • Bulk Operations with Triggers
    • Cursors and Memory Limitations
      • Cursor declaration and Life cycle
      • STATIC
      • DYNAMIC
      • SCROLL Cursors
      • FORWARD_ONLY and LOCAL Cursors
      • KEYSET Cursors with Complex SPs
    • Transactions Management
      • ACID Properties and Scope
      • EXPLICIT Transaction types
      • IMPLICIT Transactions and options
      • AUTOCOMMIT Transaction and usage
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    NA

    • Introduction to Power BI
      • Overview of BI concepts
      • Why we need BI
      • Introduction to SSBI
      • SSBI Tools
      • Why Power BI
      • What is Power BI
      • Building Blocks of Power BI
      • Getting started with Power BI Desktop
      • Get Power BI Tools
      • Introduction to Tools and Terminology
      • Dashboard in Minutes
      • Interacting with your Dashboards
      • Sharing Dashboards and Reports
    • Power BI Desktop
      • Power BI Desktop
      • Extracting data from various sources
      • Workspaces in Power BI
    • Power BI Data Transformation
      • Data Transformation
      • Query Editor
      • Connecting Power BI Desktop to our Data Sources
      • Editing Rows
      • Understanding Append Queries
      • Editing Columns
      • Replacing Values
      • Formatting Data
      • Pivoting and Unpivoting Columns
      • Splitting Columns
      • Creating a New Group for our Queries
      • Introducing the Star Schema
      • Duplicating and Referencing Queries
      • Creating the Dimension Tables
      • Entering Data Manually
      • Merging Queries
      • Finishing the Dimension Table
      • Introducing the another DimensionTable
      • Creating an Index Column
      • Duplicating Columns and Extracting Information
      • Creating Conditional Columns
      • Creating the FACT Table
      • Performing Basic Mathematical Operations
      • Improving Performance and Loading Data into the Data Model
    • Modelling with Power BI
      • Introduction to Modelling
      • Modelling Data
      • Manage Data Relationship
      • Optimize Data Models
      • Cardinality and Cross Filtering
      • Default Summarization & Sort by
      • Creating Calculated Columns
      • Creating Measures & Quick Measures
    • Data Analysis Expressions (DAX)
      • What is DAX
      • Data Types in DAX
      • Calculation Types
      • Syntax, Functions, Context Options
      • DAX Functions
      • Measures in DAX
      • Measures and Calculated Columns
      • ROW Context and Filter Context in DAX
      • Operators in DAX - Real-time Usage
      • Quick Measures in DAX - Auto validations
      • In-Memory Processing DAX Performance
    • Power BI Desktop Visualisations
      • How to use Visual in Power BI
      • What Are Custom Visuals
      • Creating Visualisations and Colour Formatting
      • Setting Sort Order
      • Scatter & Bubble Charts & Play Axis
      • Tooltips and Slicers, Timeline Slicers & Sync Slicers
      • Cross Filtering and Highlighting
      • Visual, Page and Report Level Filters
      • Drill Down/Up
      • Hierarchies and Reference/Constant Lines
      • Tables, Matrices & Conditional Formatting
      • KPI's, Cards & Gauges
      • Map Visualizations
      • Custom Visuals
      • Managing and Arranging
      • Drill through and Custom Report Themes
      • Grouping and Binning and Selection Pane, Bookmarks & Buttons
      • Data Binding and Power BI Report Server
    • Introduction to Power BI Dashboard and Data Insights
      • Why Dashboard and Dashboard vs Reports
      • Creating Dashboards
      • Conguring a Dashboard Dashboard Tiles, Pinning Tiles
      • Power BI Q&A
      • Quick Insights in Power BI
    • Direct Connectivity
      • Custom Data Gateways
      • Exploring live connections to data with Power BI
      • Connecting directly to SQL Server
      • Connectivity with CSV & Text Files
      • Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel
      • Content packs
      • Update content packs
    • Publishing and Sharing
      • Introduction and Sharing Options Overview
      • Publish from Power BI Desktop and Publish to Web
      • Share Dashboard with Power BI Service
      • Workspaces (Power BI Pro) and Content Packs (Power BI Pro)
      • Print or Save as PDF and Row Level Security (Power BI Pro)
      • Export Data from a Visualization
      • Export to PowerPoint and Sharing Options Summary
    • Refreshing Datasets
      • Understanding Data Refresh
      • Personal Gateway (Power BI Pro and 64-bit Windows)
      • Replacing a Dataset and Troubleshooting Refreshing
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    NA

    • Introduction To Python
      • Installation and Working with Python
      • Understanding Python variables
      • Python basic Operators
      • Understanding the Python blocks.
    • Python Keyword and Identiers
      • Python Comments, Multiline Comments.
      • Python Indentation
      • Understating the concepts of Operators
    • Introduction To Variables
      • Variables, expression condition and function
      • Global and Local Variables in Python
      • Packing and Unpacking Arguments
      • Type Casting in Python
      • Byte objects vs. string in Python
      • Variable Scope
    • Python Data Type
      • Declaring and using Numeric data types
      • Using string data type and string operations
      • Understanding Non-numeric data types
      • Understanding the concept of Casting and Boolean.
      • Strings
      • List
      • Tuples
      • Dictionary
      • Sets
    • Control Structure & Flow
      • Statements if, else, elif
      • How to use nested IF and Else in Python
      • Loops
      • Loops and Control Statements.
      • Jumping Statements Break, Continue, pass
      • Looping techniques in Python
      • How to use Range function in Loop
      • Programs for printing Patterns in Python
      • How to use if and else with Loop
      • Use of Switch Function in Loop
      • Elegant way of Python Iteration
      • Generator in Python
      • How to use nested Loop in Python
      • Use If and Else in for and While Loop
      • Examples of Looping with Break and Continue Statement
      • How to use IN or NOT IN keyword in Python Loop.
    • Python Function, Modules and Packages
      • Python Syntax
      • Function Call
      • Return Statement
      • Arguments in a function Required, Default, Positional, Variable-length
      • Write an Empty Function in Python pass statement.
      • Lamda/ Anonymous Function
      • *args and **kwargs
      • Help function in Python
      • Scope and Life Time of Variable in Python Function
      • Nested Loop in Python Function
      • Recursive Function and Its Advantage and Disadvantage
      • Organizing python codes using functions
      • Organizing python projects into modules
      • Importing own module as well as external modules
      • Understanding Packages
      • Random functions in python
      • Programming using functions, modules & external packages
      • Map, Filter and Reduce function with Lambda Function
      • More example of Python Function
    • List
      • What is List.
      • List Creation
      • List Length
      • List Append
      • List Insert
      • List Remove
      • List Append & Extend using + and Keyword
      • List Delete
      • List related Keyword in Python
      • List Revers
      • List Sorting
      • List having Multiple Reference
      • String Split to create a List
      • List Indexing
      • List Slicing
      • List count and Looping
      • List Comprehension and Nested Comprehension
    • Tuple
      • What is Tuple
      • Tuple Creation
      • Accessing Elements in Tuple
      • Changing a Tuple
      • Tuple Deletion
      • Tuple Count
      • Tuple Index
      • Tuple Membership
      • TupleBuilt in Function (Length, Sort)
    • Dictionary
      • Dict Creation
      • Dict Access (Accessing Dict Values)
      • Dict Get Method
      • Dict Add or Modify Elements
      • Dict Copy
      • Dict From Keys.
      • Dict Items
      • Dict Keys (Updating, Removing and Iterating)
      • Dict Values
      • Dict Comprehension
      • Default Dictionaries
      • Ordered Dictionaries
      • Looping Dictionaries
      • Dict useful methods (Pop, Pop Item, Str , Update etc.)
    • Sets
      • What is Set
      • Set Creation
      • Add element to a Set
      • Remove elements from a Set
      • PythonSet Operations
      • Frozen Sets
    • Strings
      • What is Set
      • Set Creation
      • Add element to a Set
      • Remove elements from a Set
      • PythonSet Operations
    • Python Exception Handling
      • Python Errors and Built-in-Exceptions
      • Exception handing Try, Except and Finally
      • Catching Exceptions in Python
      • Catching Specic Exception in Python
      • Raising Exception
      • Try and Finally
    • Python File Handling
      • Opening a File
      • Python File Modes
      • Closing File
      • Writing to a File
      • Reading from a File
      • Renaming and Deleting Files in Python
      • Python Directory and File Management
      • List Directories and Files
      • Making New Directory
      • Changing Directory
    • Python Database Interaction
      • SQL Database connection using
      • Creating and searching tables
      • Reading and Storing cong information on database
      • Programming using database connections
    • Reading an excel
      • Working With Excel
      • Reading an excel le using Python
      • Writing to an excel sheet using Python
      • Python| Reading an excel le
      • Python | Writing an excel le
      • Adjusting Rows and Column using Python
      • ArithmeticOperation in Excel le.
      • Play with Workbook, Sheets and Cells in Excel using Python
      • Creating and Removing Sheets
      • Formatting the Excel File Data
      • More example of Python Function
    • Complete Understanding of OS Module of Python
      • Check Dirs. (exist or not)
      • How to split path and extension
      • How to get user prole detail
      • Get the path of Desktop, Documents, Downloads etc.
      • Handle the File System Organization using OS
      • How to get any les and folders details using OS
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    NA

    • Data Analysis and Visualization using Pandas.
      • Statistics
      • Pandas
    • Data Analysis and Visualization using NumPy and MatPlotLib
      • NumPy
      • MatPlotLib
    • Introduction to Data Visualization with Seaborn
      • Introduction to Seaborn
      • Visualizing Two Quantitative Variables
      • Visualizing a Categorical and a Quantitative Variable
      • Customizing Seaborn Plots
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    NA

    • Capstone Project
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+ More Lessons

Course Design By

naswipro

Nasscom & Wipro

Course Offered By

croma-orange

Croma Campus

Our Students' Projects
1769511109.webp
IBM - Dashboard Optimization Project

Scenario: Keeping dashboards updated

Live Work:
  • Updated data regularly
  • Checked values
  • Fixed small issues
  • Kept reports current

Outcome: Dashboards always showed correct data

1769510899.webp
HCL Tech - Sales Performance Report Project

Scenario: Making easy sales reports

Live Work:
  • Collected sales data
  • Created simple reports
  • Checked totals
  • Explained results clearly

Outcome: Managers could understand the reports

1769510806.webp
Wipro - Risk Data Management Project

Scenario: Finding risky cases in data

Live Work:
  • Checked past records
  • Found risk signs
  • Updated results
  • Verified numbers

Outcome: Risks were easier to spot

1769510588.webp
Deloitte - Data Quality Improvement Project

Scenario: Fixing messy data

Live Work:
  • Removed duplicate entries
  • Fixed missing data
  • Arranged the data properly
  • Prepared it for use

Outcome: The data was clean and ready

1769252113.webp
Capgemini – Product Data Analysis Project

Scenario: Understanding product data.

Live Work:
  • Studied product records
  • Compared product numbers
  • Made simple notes
  • Shared findings

Outcome: Product performance became clear.

1769252020.webp
Accenture – Data Validation & Checking Project

Scenario: Finding mistakes in data

Live Work:
  • Checked data for errors
  • Removed wrong entries
  • Filled missing values
  • Reviewed final data

Outcome: The data became reliable.

1769251882.webp
TCS – Customer Data Insights & Reporting

Scenario: Learning about customers from data.

Live Work:
  • Looked at customer details
  • Sorted customers into groups
  • Compared customer data
  • Fixed small data issues

Outcome: The company understood customers more clearly.

1769251661.webp
Infosys – Sales Data Analysis & Reporting

Scenario: Understanding sales using past data.

Live Work:
  • Collected old sales records
  • Cleaned the data
  • Checked sales numbers
  • Made simple summaries

Outcome: The team could understand sales better.

Recent Data Analytics Job Requirements
Junior Data Analyst

Company: Capgemini

Location: Hyderabad

Experience: 0–2 Years

Required Skills: Managing data, SQL basics, data visualization & reports

Business Data Analyst

Company: Infosys

Location: Pune

Experience: 0–2 Years

Required Skills: Analyzing data, Excel, Power BI or Tableau, making reports

Data Analyst

Company: TCS

Location: Bangalore

Experience: 0–2 Years

Required Skills: Cleaning and organizing data, using Excel, basic SQL.

Who Can Join Data Analytics Course?
  • Why : Good for anyone starting a career in data analytics with no prior experience.
  • Best Topics: Basics of data analytics, working with data, reports
  • Job Benefit: Can apply for junior data analyst positions
  • Why : Helpful to those who want to move to roles related to data
  • Best Topics: Data handling, analysis work, real project practice
  • Job Benefit: Ability to move into a Data Analytics job
  • Why : Suitable for individuals from non-technical fields and those willing to work with data
  • Best Topics: Basic data work, Basic analysis work, Easy practice material, Easy analysis situations
  • Job Benefit: Entry-level jobs in data team
  • Why : Helps understand the use of data in real systems.
  • Best Topics: Full data process, working with real data
  • Job Benefit: Can work better on data projects
  • Why : This helps in the understanding of the data in business decisions
  • Best Topics: Simple reports, reading of data results, trends.
  • Job Benefit: Ability to make better choices, communicate direction to teams
Data Analytics Related Courses

Explore related courses that help enhance your data analytics skills.

Power BI Course

Get hands-on with the Power BI tool to create dashboards, visualize the data, and make appropriate decisions.

Advanced Excel Online Course

Get knowledge of advanced Excel tools and formulas to analyze and present reports in a professional format.

SQL Online Training

Master SQL to manage, query, and effectively analyze your data with ease in the real world.

Business Analyst Online Course

Analyze data in businesses, generate reports, make appropriate decisions, and much more with this online course.

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