- Embark on an exciting journey in the data analytics industry with our comprehensive Data Analytics Course in Bangalore at Croma Campus. Unlock a world of opportunities in a dynamic and data-driven field. With a high demand for data analytics specialists worldwide, it's a promising career for dedicated learners.
- Whether you choose self-study or a paid program, consider the Data Analytics Certification Course in Bangalore. As the leading Data Analytics training institute in Bangalore, we work hard to help you become a successful Data Analyst, with the potential for substantial earnings in top industries.
- Our Data Analytics courses at Croma Campus are designed to provide a comprehensive education, encompassing fundamental concepts and advanced data analytics. The primary objectives of our Data Analytics Course in Bangalore include:
Data Proficiency: Equip students to work proficiently with both structured and unstructured data across diverse business settings.
Informed Decision-Making: Empower students to utilize data effectively for making informed, strategic decisions that impact organizational success.
Complete Skill Set: Provide students with a complete package of data analytics skills, including mastery of tools, algorithms, complex data modeling, identifying business needs, and conducting in-depth data analysis.
Diverse Learning: Cover a wide range of topics, such as statistics, computer science, data analytics, data visualization, and programming languages like R and Python.
Advanced Topics: Introduce advanced concepts like big data technologies, machine learning, artificial intelligence, and deep learning.
- Let's delve into the salary expectations for fresh graduates pursuing a data analytics career:
High Demand: The data analytics field is witnessing increasing demand for skilled professionals.
Salary Projections: Salary expectations vary, with opportunities for competitive compensation.
- Course Data analyst in Bangalore at Croma Campus caters to a diverse audience:
Aspiring Data Analysts: Enthusiastic learners looking to kickstart a rewarding career in the field of data analytics.
IT Professionals: Experienced IT experts looking to upgrade their skills and seize data analytics opportunities.
Business Professionals: Executives and decision-makers eager to enhance their data analysis capabilities.
Academics and Researchers: Scholars and researchers aiming to explore data analytics as an academic or research specialization.
Professionals Seeking a Career Change: Individuals from various backgrounds contemplating a transition into data analytics for a fresh career trajectory.
- With intensive training that covers a broad spectrum of data analytics topics, individuals can anticipate remarkable career growth upon completing our data analyst classes in Bangalore. Students are empowered to:
1. Apply Practical Knowledge: Implement acquired concepts in real-world scenarios, effectively addressing complex challenges.
2. Elevate Earning Potential: Attain certifications that enhance employability and earning potential.
3. Unlock Job Opportunities: Access job openings across diverse industries and organizations.
4. Drive Industry Transformation: Play a pivotal role in the transformation of various sectors through data-driven insights and decision-making.
5. Pursue Leadership Positions: Develop the competence to advance into leadership roles, such as Data Analytics Manager, or other technical positions like Machine Learning Engineer or Data Analyst.
- The future of data analytics is exceedingly promising, with data professionals set to play a pivotal role in harnessing the power of data across various industries. Key trends shaping the future scope of data analytics include:
Growing Demand: The increasing reliance on data in organizations will continue to drive demand for data professionals.
Emerging Technologies: The convergence of data analytics with emerging technologies promises diverse job roles and opportunities.
Varied Job Roles: Data analytics professionals will have the option to explore diverse job profiles and industries.
Evolving Data Landscape: As organizations increasingly rely on data, the field of data analytics will adapt to changing data landscapes.
- Embarking on a data analytics career opens doors to a plethora of exciting job profiles in the data-driven industry, each offering unique challenges and opportunities. Let's explore some of the prominent job roles and their corresponding salary expectations in the world of data analytics:
Data Analyst: Data analysts work with datasets to uncover valuable insights. Their average salary varies, depending on factors such as experience and location.
Business Intelligence Analyst: Business intelligence analysts focus on data interpretation to support decision-making. Their salary is competitive, and they play a crucial role in business success.
Data Scientist: Data scientists specialize in complex data analysis, deriving actionable insights from data. Their salary varies based on experience and expertise.
Data Engineer: Data engineers design and maintain data infrastructure. Their salary is competitive, and their role is pivotal in ensuring data availability.
Statistician: Statisticians analyze data to generate valuable statistics. Their skills are in high demand, with competitive salaries.
Machine Learning Engineer: Machine learning engineers develop AI models and algorithms. Their role is critical in AI development and commands a competitive salary.
- Leading industries in data analytics include prominent companies in Bangalore and beyond. Opportunities abound in:
IT Sector: Leading tech companies seek skilled data analytics professionals.
Healthcare and Medical Sector: The healthcare industry relies on data for decision-making, creating a high demand for data professionals.
Banking & Finance: Financial institutions leverage data analytics for risk assessment, fraud detection, and customer insights.
Transportation: Data analytics is essential for optimizing routes, managing logistics, and improving transportation services.
Travel Industry: The travel sector employs data analytics for recommendations, personalization, and enhancing the customer experience.
eCommerce: Companies employ data analysts to enhance user experiences and boost sales.
Media & Entertainment: Data analysis plays a pivotal role in content recommendation, user engagement, and personalization.
Non-Profit Industries: Non-profit organizations utilize data analytics to drive social impact and optimize operations.
Insurance Sector: Data analytics helps insurers analyze risks, set premiums, and predict claims effectively.
- Upon course completion at the Data Analytics Training Institute in Bangalore, you'll receive a training certificate. This certificate is earned by completing projects and skill assessments at various points during the course.
- Having a well-thought-out career plan is always a smart choice, no matter where you are in your IT career. So, don't hesitate to explore our comprehensive Data Analytics training in Bangalore.
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Course Duration
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CURRICULUM & PROJECTS
Data Analytics Certification Training
- 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
- Advance Data Sorting
- Multi-level sorting
- Restoring data to original order after performing sorting
- Sort by icons
- Sort by colours
- Lookup Functions
- Lookup
- VLookup
- HLookup
- Subtotal, Multi-Level Subtotal
- Grouping Features
- Column Wise
- Row Wise
- Consolidation With Several Worksheets
- Filter
- Auto Filter
- Advance Filter
- Printing of Raw & Column Heading on Each Page
- Workbook Protection and Worksheet Protection
- Specified Range Protection in Worksheet
- Excel Data Analysis
- Goal Seek
- Scenario Manager
- Data Table
- Advance use of Data Tables in Excel
- Reporting and Information Representation
- Pivot Table
- Pivot Chat
- Slicer with Pivot Table & Chart
- Generating MIS Report In Excel
- Advance Functions of Excel
- Math & Trig Functions
- Text Functions
- Lookup & Reference Function
- Logical Functions & Date and Time Functions
- Database Functions
- Statistical Functions
- Financial Functions
- Functions for Calculation Depreciation
- 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 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 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
- 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
- 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
- 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
- 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
- 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
- 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
- Cursor declaration and Life cycle
- STATIC
- DYNAMIC
- SCROLL Cursors
- FORWARD_ONLY and LOCAL Cursors
- KEYSET Cursors with Complex SPs
- ACID Properties and Scope
- EXPLICIT Transaction types
- IMPLICIT Transactions and options
- AUTOCOMMIT Transaction and usage
- 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
- Extracting data from various sources
- Workspaces in Power BI
- 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
- 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
- What is DAX
- Data Types in DAX
- Calculation Types
- Syntax, Functions, Context Options
- DAX Functions
- Date and Time
- Time Intelligence
- Information
- Logical
- Mathematical
- Statistical
- Text and Aggregate
- 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
- Installation and Working with Python
- Understanding Python variables
- Python basic Operators
- Understanding the Python blocks.
- Python Comments, Multiline Comments.
- Python Indentation
- Understating the concepts of Operators
- Arithmetic
- Relational
- Logical
- Assignment
- Membership
- Identity
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FAQ's
Croma Campus offers comprehensive Data Analytics training with expert guidance and hands-on experience, ensuring you are job-ready.
Upon course completion, you'll have proficiency in data handling, analysis, and advanced data analytics concepts, setting you up for a successful career.
No, there are no specific prerequisites for joining our Data Analytics classes. We welcome learners from various backgrounds.
Your earning potential is significant, dependent on your skill level and location.
Yes, we provide placement support to help you secure a job and kick-start your data analytics career.

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Real-life Case Studies
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Assignment
Adding the scope of improvement and fostering the analytical abilities and skills through the perfect piece of academic work.
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