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- Searching for the top provider of Data Analysis Training in Ahmedabad Look no further! Croma Campus delivers premier Data Analytics Training, meticulously crafted by our team of experts to enhance your skills and make you proficient, allowing you to confidently apply them in your workplace.
- Why Choose Our Data Analysis Course in Ahmedabad
- Regardless of your background, our Data Analysis Course in Ahmedabad offers a holistic training approach. Whether you come from an IT background or not, our program is designed to provide comprehensive training to all participants.
- Don't wait any longer. Enroll in the best Data Analysis Certification in Ahmedabad and become a certified professional. Start your journey with Croma Campus today and unlock your potential like never before!
Comprehensive Learning: Gain an immersive understanding of data analysis with our expertly designed curriculum.
High-Quality Learning Materials: Access top-tier learning materials and resources that will refine your necessary skills.
Career Advancement: Our Data Analysis Course is designed to help you kick-start an exceptional career journey.
Practical Experience: Learn through real-life case studies and hands-on practice to thoroughly grasp the concepts.
Decision-Making Skills: Discover how enterprises utilize data in their business processes to make informed decisions.
Data Analysis Course in Ahmedabad
- Our Data Analysis Training in Ahmedabad provides a robust foundation in data analysis concepts. Here are the key objectives:
Master Data Analysis Concepts and Principles: Our Data Analysis Course makes you an expert in data analysis concepts and principles.
Extract Meaningful Insights: Learn how to extract meaningful insights from data, such as hidden patterns, market trends, unknown correlations, and customer preferences.
Enhance Your Data Analysis Skills: Sharpen your data analysis skills and familiarize yourself with various data analytics terminologies.
Utilize Open-Source Data Analytics Tools: Familiarize yourself with open-source data analytics tools like R Studio and Spotfire.
Balanced Theoretical and Practical Knowledge: We offer an optimal distribution of theoretical and practical knowledge.
Advanced Concepts Mastery: Once you have mastered the fundamentals of the Data Analysis Course, youll learn more advanced concepts of R Studio, Tableau, Spotfire, and statistics.
- Data analysts are among the most in-demand and highly paid professionals globally. However, their salaries vary based on several factors, including work experience, location, organization size, and job role. Scroll down to learn about the salary structures offered after completing Data Analytics Training.
- In the USA, the average salary for a data analyst is over $65,000 per year. As you gain experience and knowledge, your salary will increase accordingly.
- Even at the entry level, data analysts can earn between $40,585 and $78,832 per year. Experienced data analysts can command salaries ranging from $45,280 to $99,542 annually. Data analytics remains one of the most sought-after and lucrative professions worldwide.
- Data analysis has become integral to every organization, leading to a high demand and significantly higher salaries for data analysts. Upon successfully completing the Data Analytics Certification, you can pursue job titles such as data engineer, data scientist, data architect, database administrator, and data analyst.
- You'll have the opportunity to work with leading IT giants in the marketplace, earning competitive salary packages. Our live sessions include access to class recordings, study materials, and project work.
- MNCs and corporate giants are actively hiring data analytics professionals worldwide. Popular job titles in this field include data engineer, data architect, data scientist, and database administrator.
- To benefit from a lucrative career in data analytics, enroll in one of the leading Data analysis course in Ahmedabad today!
- Data analysis course in Ahmedabad is highly in demand due to following reasons:
- These factors collectively contribute to the growing popularity of data analytics training in Ahmedabad, making it a sought-after destination for aspiring data professionals.
Thriving IT and Business Hub: Ahmedabad is rapidly growing as an IT and business hub, attracting numerous companies that rely on data analytics for decision-making and strategy development.
High Demand for Skilled Professionals: There is a high demand for skilled data analysts in Ahmedabad, driven by the increasing adoption of data-driven approaches by businesses across various industries.
Competitive Salaries: Data analytics professionals in Ahmedabad enjoy competitive salaries, making it an attractive career choice for many.
Quality Education and Training Institutes: The city hosts several reputable institutes offering comprehensive data analytics training, ensuring high-quality education and industry-relevant skills.
Career Growth Opportunities: Completing data analytics training opens up numerous career growth opportunities, from entry-level positions to senior roles in diverse sectors such as finance, healthcare, retail, and IT.
Access to Industry Experts: Training programs in Ahmedabad often feature industry experts and experienced professionals as instructors, providing valuable insights and real-world knowledge.
Networking and Collaboration: Ahmedabad offers a vibrant community of data professionals, providing ample networking and collaboration opportunities through events, seminars, and workshops.
Technological Advancements: The city's focus on technological advancements and innovation further boosts the importance of data analytics, as companies seek to leverage data for competitive advantage.
Practical Exposure: Many training programs emphasize hands-on learning and real-life projects, ensuring that participants gain practical experience and are job-ready.
Diverse Job Roles: Data analytics training in Ahmedabad prepares professionals for a variety of roles, including data engineer, data scientist, data architect, and business intelligence analyst, catering to the diverse needs of the job market.
- After completing your Data Analytics Training, here are some essential job roles and responsibilities you will need to perform:
Comprehensive Knowledge of Data Analytics: You should be proficient in all data analytics concepts and associated skills.
Familiarity with Key Terminologies: Understand key data analytics terminologies such as acquisition, manipulation, evaluation, and experimentation.
Programming Proficiency: Implement basic R programming and Tableau programming, and get acquainted with open-source data analytics tools.
Advanced Training Opportunities: Engage in advanced training in fields like advanced analytics, R Studio, Tableau, Spotfire, and statistics.
Industry Preparedness: Our Data Analytics Course, through projects, webinars, and assignments, will prepare you for the industry, helping you secure a lucrative position at a leading company.
- After finishing the Data Analytics Training in Ahmedabad, you will be awarded a certification that validates your skills and knowledge to potential employers. Its a wise choice to enroll in our Data Analytics Course and complete the training successfully.
Establish yourself as a certified data analytics specialist now.
Leading companies, including Google, Intuit, Cisco Systems, Facebook, Apple, Capital, Maruti, and others, are on the lookout for talent like yours.
Our Data Analytics Course offers dedicated interview preparation sessions to help you succeed in job interviews.
Prepare yourself to overcome any obstacles in your professional journey.
- Our Data Analytics Certification course in Ahmedabad equips you with comprehensive knowledge of essential data analytics tools and techniques designed to meet your learning requirements.
Get noticed by recruiters and secure a job quickly.
Our experts provide crucial interview tips to support your job search.
Boost your value in the competitive job landscape.
Globally accepted, this certification allows you to pursue opportunities abroad.
Acquire the expertise needed to pass any certification exam with confidence.
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CURRICULUM & PROJECTS
Data Analytics Training Program
- 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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- 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
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- Categorical Data
- Numerical Data
- Mean
- Median
- Mode
- Outliers
- Range
- Interquartile range
- Correlation
- Standard Deviation
- Variance
- Box plot
- Descriptive Statistics
- Sample vs Population Statistics
- Random variables
- Probability distribution functions
- Expected value
- Normal distribution
- Gaussian distribution
- Z-score
- Spread and Dispersion
- Correlation and Co-variance
- Data Preparation
- Feature Engineering
- Feature Scaling
- Datasets
- Dimensionality Reduction
- Anomaly Detection
- Parameter Estimation
- Data and Knowledge
- Selected Applications in Data Mining
- Need for structured exploratory data
- EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)
- Identify missing data
- Identify outliers data
- Imbalanced Data Techniques
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- Statistics
- Pandas
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- 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
- AI Tools:
- Copilot in Azure Data Studio or GitHub for SQL suggestions
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- 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
- 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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- 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
- 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
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- Data Visualization
- Business Intelligence tools
- Introduction to Tableau
- Tableau Architecture
- Tableau Server Architecture
- VizQL Fundamentals
- Introduction to Tableau Prep
- Tableau Prep Builder User Interface
- Data Preparation techniques using Tableau Prep Builder tool
- Features of Tableau Desktop
- Connect to data from File and Database
- Types of Connections
- Joins and Unions
- Data Blending
- Tableau Desktop User Interface
- Visual Analytics
- Basic Charts Bar Chart, Line Chart, and Pie Chart
- Hierarchies
- Data Granularity
- Highlighting
- Sorting
- Filtering
- Grouping
- Sets
- Types of Calculations
- Built-in Functions (Number, String, Date, Logical and Aggregate)
- Operators and Syntax Conventions
- Table Calculations
- Level of Detail (LOD) Calculations
- Using R within Tableau for Calculations
- Parameters
- Tool tips
- Trend lines
- Reference lines
- Forecasting
- Clustering
- Count Customer by Order
- Profit per Business Day
- Comparative Sales
- Profit Vs Target
- Finding the second order date
- Cohort Analysis
- Introduction to Geographic Visualizations
- Manually assigning Geographical Locations
- Types of Maps
- Spatial Files
- Custom Geocoding
- Polygon Maps
- Web Map Services
- Background Images
- Box and Whiskers Plot
- Bullet Chart
- Bar in Bar Chart
- Gantt Chart
- Waterfall Chart
- Pareto Chart
- Control Chart
- Funnel Chart
- Bump Chart
- Step and Jump Lines
- Word Cloud
- Donut Chart
- Introduction to Dashboards
- The Dashboard Interface
- Dashboard Objects
- Building a Dashboard
- Dashboard Layouts and Formatting
- Interactive Dashboards with actions
- Designing Dashboards for devices
- Story Points
- Tableau Tips and Tricks
- Choosing the right type of Chart
- Format Style
- Data Visualization best practices
- Publishing Workbooks to Tableau Online
- Interacting with Content on Tableau Online
- Data Management through Tableau Catalog
- AI-Powered features in Tableau Online (Ask Data and Explain Data)
- Understand Scheduling
- Managing Permissions on Tableau Online
- Data Security with Filters in Tableau Online
- Ask Data: Natural Language Data Exploration
- Explain Data: Automatic statistical insights
- Tableau GPT (Einstein Copilot - Salesforce)
- AI forecasting in visualizations
- Integration with Python (TabPy) and R
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