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Master the art of data extraction for analysis. Enroll now and gain insights from an experienced data analyst.
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Corporate Served- Looking for the top provider of a Data Analysis Course in Kolkata that offers value for money Your search ends here! Croma Campus presents the premier Data Analytics Training in Kolkata, meticulously crafted by our expert team to elevate your skills and boost your proficiency, enabling you to apply them confidently in your workplace.
- Why Choose Croma Campus for Your Data Analytics Course in Kolkata
- Regardless of your background, our Data Analytics Course in Kolkata provides a holistic training approach. Whether you come from an IT background or not, our program is designed to offer comprehensive training to all participants.
- Don't delay. Sign up for the best Data Analytics Certification in Kolkata and become a certified professional. Start your journey with Croma Campus today and unlock your potential like never before!
In-Depth Learning: Achieve a comprehensive understanding of data analysis with our immersive curriculum.
Quality Educational Resources: Gain access to top-notch learning materials and knowledge resources that will enhance your essential skills.
Career Advancement: Our Data Analytics Course is designed to kick-start your exceptional career journey.
Practical Experience: Learn through real-life case studies and hands-on practice to fully grasp the concepts.
Decision-Making Skills: Discover how enterprises leverage data in their business processes to make informed decisions.
Data Analytics Course in Kolkata
- Our Data Analysis Training in Kolkata equips you with a comprehensive understanding of data analysis. Here are the primary objectives:
Gain Expertise in Data Analysis Concepts: Our Data Analysis Course in Kolkata ensures you become proficient in key data analysis concepts and methodologies.
Derive Valuable Insights: Learn to extract valuable insights from data, uncovering hidden patterns, market trends, unknown correlations, and customer preferences.
Improve Your Analytical Skills: Enhance your analytical skills and understand various data analytics terminologies.
Master Open-Source Tools: Get hands-on experience with open-source data analytics tools like R Studio and Spotfire.
Blend of Theory and Practice: Benefit from a balanced mix of theoretical knowledge and practical applications.
Advanced Learning Opportunities: After mastering the basics, delve into advanced concepts of R Studio, Tableau, Spotfire, and statistical analysis.
- Upon completing the Data Analyst Course in Kolkata, you can anticipate competitive salary packages in the field of data analysis. Here are the typical salary expectations:
- Factors Influencing Salary:
- Investing in a Data Analyst Course in Kolkata is a valuable step towards a rewarding and lucrative career in data analysis.
Entry-Level Data Analyst: Fresh graduates or professionals transitioning into data analysis can expect an average salary ranging from 3,00,000 to 5,00,000 per annum.
Mid-Level Data Analyst: With a few years of experience, data analysts can earn between 5,00,000 to 8,00,000 per annum.
Senior Data Analyst: Experienced professionals with significant expertise in data analysis can command salaries ranging from 8,00,000 to 12,00,000 or more per annum.
Specialized Roles: Data analysts specializing in advanced areas such as machine learning, big data, or specific industry sectors can expect higher salary packages, often exceeding 12,00,000 per annum.
Industry: Salaries can vary based on the industry, with finance, healthcare, and technology sectors often offering higher compensation.
Location: While Kolkata offers competitive salaries, data analysts in metropolitan cities like Mumbai, Bangalore, and Delhi may earn higher due to the cost of living and demand.
Skills and Certifications: Additional certifications and specialized skills can significantly boost your salary prospects.
- Completing a Data Analyst Course in Kolkata can significantly boost your career prospects. Heres a compact overview of potential career growth:
- Entry-Level Positions:
- Mid-Level Positions:
- Senior-Level Positions:
- Specialized Roles:
- Leadership Positions:
- Enhancing Your Career:
- Investing in a Data Analyst Course in Kolkata opens up diverse opportunities for career growth and advancement.
Junior Data Analyst: Handle data collection, basic analysis, and report generation.
Business Intelligence Analyst: Analyse data to support business decisions using BI tools.
Data Analyst: Work on complex data analysis and predictive models.
Data Scientist: Apply advanced statistical and machine learning techniques.
Data Engineer: Build and maintain data pipelines and ensure data quality.
Senior Data Analyst: Lead projects and mentor junior analysts.
Analytics Manager: Manage teams and align data projects with business goals.
Data Architect: Design and manage data system architecture.
Machine Learning Engineer: Develop and deploy machine learning models.
Big Data Analyst: Analyse large datasets using big data technologies.
Chief Data Officer (CDO): Oversee data strategy and governance.
Director of Analytics: Lead the analytics division and drive data initiatives.
Certifications: Obtain additional certifications for career advancement.
Networking: Engage with professional networks and communities.
Continuous Education: Stay updated with the latest trends and technologies.
- Data analytics course in Kolkata is popular due to the following reasons.
Growing IT and Business Sector: Kolkatas expanding IT and business sectors drive demand for data analytics professionals.
High Demand for Skilled Analysts: Increasing adoption of data analytics by businesses boosts the need for skilled analysts.
Competitive Salaries: Data analytics professionals in Kolkata enjoy attractive salary packages.
Reputable Training Institutes: The city hosts esteemed institutes offering quality data analytics training.
Career Advancement: Training opens up numerous opportunities for career growth in various industries.
Expert Instructors: Programs feature experienced industry professionals providing practical insights.
Networking Opportunities: Kolkata has a vibrant data professional community, fostering networking and collaboration.
- Upon completing your Data Analytics Training, you will be equipped to perform several key job roles and responsibilities:
Master Data Analytics Concepts: A professional should be well-versed in all data analytics concepts and related skills.
Understand Data Analytics Terminologies: You must be familiar with various data analytics terminologies such as acquisition, manipulation, evaluation, and experimentation.
Implement Programming Skills: Implement basic R programming and Tableau programming, and familiarize yourself with open-source data analytics tools.
Pursue Advanced Training: Apply for advanced-level training in areas like advanced analytics, R Studio, Tableau, Spotfire, and statistics.
Industry-Ready Skills: Our Data Analytics Course, which includes projects, webinars, and assignments, will make you industry-ready, enabling you to secure a high-paying job at a top-notch company.
- Upon completing the Data Analytics Training in Kolkata, you will receive a certification that assures potential employers of your skills and expertise. Enrolling in our Data Analytics Course and successfully finishing the training is a smart move.
Become a certified data analytics expert today.
Top companies such as Google, Intuit, Cisco Systems, Facebook, Apple, Capital, Maruti, and more are seeking professionals like you.
Our Data Analytics Course includes specialized interview training sessions to prepare you for job interviews.
Equip yourself to tackle any challenges that come your way.
- Our Data Analytics Certification course in Kolkata provides in-depth knowledge of all relevant data analytics tools and techniques tailored to meet learners' specific needs.
Stand out to potential recruiters and get hired immediately.
Our experts also offer support with valuable interview tips.
Enhance your value in today's competitive job market.
Recognized globally, this certification opens up opportunities to work abroad.
Gain the necessary knowledge to successfully pass any certification exam.
- You May Also Read:
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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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Course Duration
80 Hrs.
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