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Uncover the methods to extract data for analytical purposes. Join us now and study under a skilled data analyst.
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- In today's world, being able to analyse data is essential for making smart business decisions. Our data analysis course in Mumbai is designed to give you the skills and knowledge you need to succeed in this field.
- This course covers a wide range of topics, from basic data handling to advanced analysis techniques, ensuring you are prepared to handle real-world data challenges. The course content is balanced with both theory and hands-on practice. You'll learn how to collect, clean, and prepare data, as well as dive into advanced topics like statistical analysis, data visualization, and predictive modelling.
- By the end of the course, you'll be skilled in using popular tools like Excel, SQL, Python, and R to analyse data and create useful insights.
- Prerequisites for Data Analyst Course in Mumbai
- Who Should Enroll for Data Analytics Classes in Mumbai
Open to Everyone: No specific background needed.
Basic Understanding: Some knowledge of statistics, math, and programming is helpful.
Familiarity with Tools: Experience with Excel, SQL, Python, or R is a plus but not required.
Interest in Learning: A strong desire to learn about data and analytics is important.
Beginners: Anyone new to data analysis.
Career Changers: People looking to switch to a career in data analysis.
Current Data Professionals: Data analysts, data scientists, and business analysts wanting to improve their skills.
IT Professionals: IT experts looking to add data analysis to their skillset.
Business Managers: Managers who want to use data analytics for better decision-making.
Students and Graduates: Recent graduates or students wanting to gain practical data analysis skills.
Data Analytics Course in Mumbai
- Our data analytics training in Mumbai aims to provide the essential skills for effective data analysis. The goals include:
Comprehensive Knowledge: Understand the basics and advanced concepts of data analysis.
Hands-On Experience: Work on real-world projects to apply what you learn.
Tool Mastery: Get proficient with tools like Excel, SQL, Python, and R.
Statistical Analysis: Learn how to perform statistical analysis to find trends and patterns in data.
Data Visualization: Learn to create visual representations of data to communicate findings effectively.
Predictive Modeling: Understand how to use data to predict future trends.
Problem-Solving: Use data to identify and solve business problems.
Communication Skills: Improve your ability to present data findings clearly to stakeholders.
- Completing a data analyst course in Mumbai can boost your earning potential. Here's what you can expect based on experience:
Entry-Level Data Analysts: Around Rs 4,00,000 to Rs 6,00,000 annually.
Mid-Level Data Analysts: Rs 7,00,000 to Rs 12,00,000 annually with a few years of experience.
Senior Data Analysts: Rs 13,00,000 to Rs 20,00,000 annually for experienced professionals.
Global Opportunities: Higher salaries in global markets like the US or UK, often exceeding $70,000 to $100,000 per year.
- Completing a data analysis course with the best data analytics institute in Mumbai opens up many career opportunities, including:
Diverse Roles: Move into roles like data scientist, business analyst, or data engineer.
High Demand: Industries like IT, finance, healthcare, and retail need data analysts.
Professional Development: Further certifications and training can lead to higher positions.
Leadership Roles: Experienced data analysts can advance to management positions.
Entrepreneurial Opportunities: Some data analysts start their own consulting businesses.
- The popularity of data analytics courses in Mumbai is due to several reasons:
Industry Demand: Businesses need skilled data analysts to make informed decisions.
Career Opportunities: Many job openings in various industries like IT, finance, healthcare, and retail.
Technological Advancements: New tools and technologies make data analysis easier.
Global Recognition: Certifications from Mumbai are recognized worldwide.
Professional Community: Access to a network of professionals and experts in the field.
- Our Data analytics classes in Mumbai helps you to become an established data analyst and Data analysts play a key role in organizations by:
Collecting Data: Gathering data from various sources.
Cleaning Data: Ensuring data is accurate and consistent.
Analysing Data: Using statistical methods to find trends and patterns.
Visualizing Data: Creating charts and graphs to present findings.
Reporting: Preparing reports and presentations for stakeholders.
Using Tools: Working with tools like Excel, SQL, Python, and R.
Collaborating: Working with different teams to meet their data needs.
Solving Problems: Using data to address business issues.
- Data analysts are in demand in various industries, including:
IT: Analyzing large volumes of data to improve decision-making.
Finance and Banking: Optimizing processes, managing risks, and ensuring compliance.
Healthcare: Improving patient care and managing healthcare data.
Retail and E-commerce: Enhancing customer experience and optimizing inventory.
Consulting: Providing data-driven solutions to clients.
- After completing the data analysis course in Mumbai, you'll receive a certificate that proves your skills and knowledge. This certification can enhance your credibility and career prospects
- By enrolling in our data analysis training in Mumbai, you'll acquire the skills needed to excel in this dynamic field, opening up many career opportunities and advancing your professional journey.
In-Depth Knowledge: Gain a strong understanding of data analysis principles.
Practical Experience: Work on real-world projects.
Career Advancement: Essential for securing data analyst roles and advancing your career.
Attractive Salaries: Access to high-paying job opportunities.
Updated Skills: Stay current with industry trends and best practices.
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CURRICULUM & PROJECTS
Data Analytics Training Program
- 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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- 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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- 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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- 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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- 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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- 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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- Capstone Project
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WHAT OUR ALUMNI SAYS ABOUT US
Tinish Sharma
R programming
I was enrolled for the R programming under the guidance of Mr. Anantha Rao sir. He has a very unique way of teaching and daily presentations by the students were the main highlight of the class. Whatever he taught is actually really helping me during my internship period. I really liked his way of t Read more...
Ishani
Data Analytics
Best training institute for learning Tableau. Anurag Mishra sir is the best trainer for learning Tableau. Read more...
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Data Analytics
Hi. I have done this course Croma campus. The trainer give the sessions very nicely nd in-depth knowledge. My experience is good throughout the learning program. Management is good. The course helped me in increasing my knowledge and capable in entering the desiring field. Read more...
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Data Analytics
If you are looking to get a reputed job after SAS certification then you should go for the top which is Croma Campus. I have recently completed my SAS certification and got a placement in a reputed MNC. Moreover, the training offered out by the specialists are of world-class and prepares out the stu Read more...
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Data Analytics
Hi, my name is Anup Singh and I have recently completed my SAS certification from Croma Campus. I am fully satisfied after getting a world-class experience at affordable costs. Besides offering out the training they also guided me regarding the preparation for getting some world-renowned certificati Read more...
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Data Analytics
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Data Analytics
Croma Campus is a very nice training center. I have taken SPSS training in Croma Campus. They are very experienced and the way of teaching is very good. I got the job based on training; it was my great experience at Croma Campus. All the tutors were very knowledgeable and supportive, the staff was v Read more...
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Hi, my name is Neelam. I currently work as a Microsoft Excel at HCL. My interview in this company was scheduled by Croma Campus as I have done 2 months of Microsoft Advance Excel Certification Training course from it. I managed to crack this interview and the whole credit of my success goes to my Mi Read more...
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FAQ's
The course typically lasts for 3 to 6 months, depending on the level of depth and the schedule (part-time or full-time).
Yes, we offer job placement assistance, including resume building, interview preparation, and connecting with industry recruiters.
The course is available both online and in-person, providing flexibility to learners based on their preferences.
Yes, the course includes assessments and certification exams to validate your knowledge and skills.
Graduates can pursue careers as data analysts, business analysts, data scientists, or data engineers in various industries.
Our course stands out due to its comprehensive curriculum, experienced instructors, hands-on projects, and strong industry connections.
You will work on real-world projects involving data cleaning, analysis, visualization, and predictive modeling using industry-standard tools.
Yes, we provide opportunities to network with industry experts through workshops, guest lectures, and networking events.
You will receive continuous support from instructors and mentors, including regular feedback on your progress and assistance with any challenges you encounter.
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