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Learn how to extract data for analysis. Join now and learn under an expert data analyst.
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we train you to get hired.
- Looking for the best provider of Data Analytics Courses that can impart at the right price If so, your search ends here! Croma Campus offers the best Data Analytics Training that is industriously designed by our team of experts to help you improve your skills and make you proficient so that you can deploy them in your workplace, confidently.
- No matter if you are from an IT background or not, our Data Analytics Course offers a holistic approach to provide its training participants. So, what are you waiting for Simply enrol for the best Data Analytics Certification and become a certified professional like never before.
Get an immersive understanding of the relative domain.
Avail of suitable learning materials and knowledge that will enhance the necessary skills.
Our Data Analytics Course will help you to kick-start an incredible career journey.
Our Data Analytics Training will help you understand real-life case studies and hands-on practice to let you gain a proper understanding of the concepts.
Enterprises are using data in their business processes to make the right decisions.
Data Analytics Certification Training
- Our Data Analytics Training may help you with a robust foundation of data analysis concepts. Here are a few of the major objectives of the Data Analytics Course:
- Once you have mastered the fundamentals of the Data Analytics Course, youll learn more advanced concepts of R studio, Tableau, Spotfire, statistics, etc.
Our Data Analytics Course makes you an expert in Data Analytic concepts and, principles.
Know how to extract meaningful insights from the preferred data such as hidden patterns, market trends unknown correlations, and customer preferences.
Sharpen your data analysis skills and various data analytics terminologies.
Familiarize yourself with open-source data analytics tools i.e., R Studio or Spotfire, etc.
We offer an optimal distribution of theoretical and practical knowledge.
- Data Analytics are one of the most in-demand and highly-paid professionals across the world. However, the salary of a Data Analytics varies depending on various factors such as work experience, location, size of the organization, job role, etc.
- Scroll down a bit to know the salary structures offered post completing the Data Analytics Training.
The average salary of a Data Analytics is more than $ 65,000 per year in the USA.
The salary will grow as you gain experience, knowledge, and a job role.
It is one of the most in-demand and high-paid professionals across the globe.
Even a professional at the beginner level may earn $40,585 to $78,832.
An experienced data Analytics can earn up to $45,280 to $99,542.
- Data Analysis has become a part of every organization. However, the huge demand and therefore the salary of Data Analytics is significantly higher. Some of the job titles after successfully completing the Data Analytics Certification are data engineer, data scientist, data architect, database administrator, data Analytics, etc.
- If you want to avail the benefits of a lucrative career, you need to enrol in one of the leading Data Analytics Training.
You will work with leading IT giants in the marketplace and at a higher salary package.
Our Live session is empowered with delivering the recordings of the live class, study material, projects, etc.
MNCs and corporate giants are hiring data Analytics professionals across the globe.
Popular job titles include data engineer, data architect, data scientist, database administrator, etc.
- It wouldnt be wrong to say that data is increasingly popular, and so is the demand for a data Analytics professional. Well, Data Analytics Certification plays a crucial role in helping business operations by making effective business decisions.
Students will learn how to analyse and manage the data that could benefit the organization.
The demand for skilled professionals is likely to rise in the future.
Theres a shortage of skilled experts across the globe.
Professionals are likely to bag huge salary packages and even work abroad.
Most of the top MNCs are getting into data analytics.
- After the completion of your Data Analytics Training, here are some of the major job roles and responsibilities that you must need to perform at work.
- Our Data Analytics Course such as the projects, webinars, & assignments will make you industry-ready, allowing you to grab a high-paying job at a top-notch company.
A pro should know all Data Analytics concepts and related skills.
You must know about various data analytics terminologies like acquisition, manipulation, evaluation, experimentation, etc.
Implement basic R programming, and Tableau programming and familiarize yourself with open-source data analytics tools.
Apply for advanced-level training such as advanced analytics, R studio, Tableau, Spotfire, statistics, and much more.
- Upon Data Analytics Training completion, you will be bestowed with a training certificate that will assure your potential employers trust your skillset and knowledge. So, it will be a wise decision on your part to enrol in our Data Analytics Course and successfully complete the training.
Establish yourself as a certified data Analytics expert right away.
Major companies include Google, Intuit, Cisco Systems, Facebook, Apple, Capital, Maruti, etc.
Our Data Analytics Course provide an interview training session regarding job interviews
Get yourself ready to face any challenges that come your way.
- Our Data Analytics Certification includes comprehensive knowledge of all the related Data Analytics tools and techniques to cater to the specific needs of the learners.
Get noticed by potential recruiters, and get hired right away.
Our experts also support you by providing interview tips.
Increase your worth in todays competitive landscape.
As it is accepted worldwide, you can work abroad.
Get sufficient knowledge to clear any certification exam successfully.
- You May Also Read:
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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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