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Data Analytics is one of the most in-demand skills in today’s technology-driven world, especially in a thriving tech hub like Bangalore. This course is designed to equip students with the essential knowledge and hands-on experience needed to analyze, interpret, and transform data into actionable insights. The syllabus for the Data Analytics Course in Bangalore covers fundamental concepts of data handling, statistical analysis, data visualization, machine learning basics, and industry-relevant tools like Python, SQL, and Tableau. This comprehensive program is ideal for aspiring data analysts, business intelligence professionals, and anyone interested in a data-centric career, offering a step-by-step pathway from foundational skills to advanced analytical techniques.
Module 1: Introduction to Statistical Analysis
- Counting, Probability, and Probability Distributions
- Sampling Distributions
- Estimation and Hypothesis Testing
- Scatter Diagram
- Anova and Chisquare
- Imputation Techniques
- Data Cleaning
- Correlation and Regression
Module 2: Introduction to Data Analytics
- Data Analytics Overview
- Importance of Data Analytics
- Types of Data Analytics
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
- Benefits of Data Analytics
- Data Visualization for Decision Making
- Data Types, Measure Of central tendency, Measures of Dispersion
- Graphical Techniques, Skewness & Kurtosis, Box Plot
- Descriptive Stats
- Sampling Funnel, Sampling Variation, Central Limit Theorem, Confidence interval
Data Analytics Training Options
Module 3: Excel: Basics to Advanced
- Introduction to Backend Programming
- Java Backend Frameworks (e.g., Spring Boot)
- RESTful API Design and Implementation
- Data Storage and Databases (SQL and NoSQL)
- Server-side Validation and Security
Module 4: Changing the Chart Type
- Chart Types
- Changing the Way Data is Displayed
- Moving the Legend
- Formatting Charts
- Adding Chart Items
- Formatting All Text
- Formatting and Aligning Numbers
- Formatting the Plot Area
- Formatting Data Markers
- Pie Charts
- Creating a Pie Chart
- Moving the Pie Chart to its Own Sheet
- Adding Data Labels
- Exploding a Slice of a Pie Chart
- Data Analysis − Overview
- types of Data Analysis
- Data Analysis Process
- Working with Range Names
- Copying Name using Formula Autocomplete
- Range Name Syntax Rules
- Creating Range Names
- Creating Names for Constants
- Managing Names
- Scope of a Name
- Editing Names
- Applying Names
- Using Names in a Formula
- calculations
- Â
Module 5: Viewing Names in a Workbook
- Copying Formulas with Names
- Difference between Tables and Ranges
- Create Table
- Table Name
- Managing Names in a Table
- Table Headers replacing Column Letters
- Propagation of a Formula in a Table
Module 6:Resize Table
- Remove Duplicates
- Convert to Range
- Table Style Options
- Table Styles
- Cleaning Data with Text Functions
- Removing Unwanted Characters from Text
- Extracting Data Values from Text
- Formatting Data with Text Functions
- Date Formats
- Conditional Formatting
- Sorting
- Filtering
- Lookup Functions
- Pivoting
Module 7: SQL- Introduction to Oracle Database
- Retrieve Data using the SQL SELECT Statement
- Learn to Restrict and Sort Data
- Usage of Single-Row Functions to Customize Output
- Invoke Conversion Functions and Conditional Expressions
Module 8: Aggregate Data Using the Group Functions
- Display Data from Multiple Tables Using Joins
- Use Sub-Queries to Solve Queries
- The SET Operators
- Data Manipulation Statements
- Use of DDL Statements to Create and Manage Tables
- Other Schema Objects
- Control User Access
- Management of Schema Objects
- Manage Objects with Data Dictionary Views
Module 9:Â Manipulate Large Data Sets
- Identifying Performance Bottlenecks
- Caching Strategies
- Code Profiling and Optimization
- Content Delivery Networks (CDNs)
- Load Testing and Performance MonitoringÂ
Module 10: Tableau – Course Material
- Start Page
- Show Me
- Connecting to Excel Files
- Connecting to Text Files
- Connect to Microsoft SQL Server
- Connecting to Microsoft Analysis Services
- Creating and Removing Hierarchies
- Bins
- Joining Tables
- Data Blending
Module 11:Â Learn Tableau Basic Reports
- Parameters
- Grouping Example 1
- Edit Groups
- Set
- Combined Sets
- Creating a First Report
- Data Labels
- Create Folders
- Sorting Data
- Add Totals, Sub Totals and Grand Totals to Report
Module 12: Learn Tableau Charts
- Area Chart
- Bar Chart
- Box Plot
- Bubble Chart
- Bump Chart
- Bullet Graph
- Circle Views
- Dual Combination Chart
- Dual Lines Chart
- Funnel Chart
- Traditional Funnel Charts
- Gantt Chart
- Grouped Bar or Side by Side Bars Chart
- Heatmap
- Highlight Table
- Histogram
- Cumulative Histogram
- Line Chart
- Lollipop Chart
Module 13: Pareto Chart
- Scatter Plot
- Stacked Bar Chart
- Text Label
- Tree Map
- Word Cloud
- Waterfall Chart
Module 14:Â Learn Tableau Advanced Reports
- Dual Axis Reports
- Blended Axis
- Individual Axis
- Add Reference Line
Module 15 :Â Reference Bands
- Reference Distributions
- Basic Maps
- Symbol Map
- Use Google Maps
- Mapbox Maps as a Background Map
- WMS Server Map as a Background Map
Module 16 : Learn Tableau Calculations & Filters
- Calculated Fields
- Basic Approach to Calculate Rank
- Advanced Approach to Calculate Ra
- Calculating Running Total
- Filters Introduction
- Quick Filters
- Filters on Dimensions
- Conditional Filters
Module 17 : Top and Buttom Filters
- Filters on Measures
- Context Filters
- Slicing Fliters
- Data Source Filters
- Extract Filters
Module 18:Â Learn Tableau Dashboards
- Create a Dashboard
- Format Dashboard Layou
- Create a Device Preview of a Dashboard
- Create Filters on Dashboard
- Dashboard Objects
- Create a Story
Module 19: Learn Tableau Dashboards
- Overview of Tableau Server.
- Publishing Tableau objects and scheduling/subscription
Module 20:Â Power BI – Introduction to Power BIÂ
- Get Started with Power BI
- Overview: Power BI concepts
- Sign up for Power BI
- Overview: Power BI data sources
- Connect to a SaaS solution
- Upload a local CSV file
- Connect to Excel data that can be refreshed
- Connect to a sample
- Create a Report with Visualizations
- Explore the Power BI portal
Module 21:Â Viz and Titles
- Overview: Visualizations
- Using visualizations
- Create a new report
- Create and arrange visualizations
- Format a visualization
- Create chart visualizations
- Use text, map, and gauge visualizations and save a report
- Use a slicer to filter visualizations
- Sort, copy, and paste visualizations
- Download and use a custom visual from the gallery
Module 22 : Reports And Dashboards
- Modify and Print a Report
- Rename and delete report pages
- Add a filter to a page or report
Module 23 : Set Visualization and InteractionsÂ
- Print a report page
- Send a report to PowerPoint
- Create a Dashboard
- Create and manage dashboards
- Pin a report tile to a dashboard
- Pin a live report page to a dashboard
- Pin a tile from another dashboard
- Pin an Excel element to a dashboard
- Manage pinned elements in Excel
- Add a tile to a dashboard
- Build a dashboard with Quick Insights
- Set a Featured (default) dashboard
- Ask Questions about Your Data
- Ask a question with Power BI Q&A
- Tweak your dataset for Q&A
- Enable Cortana for Power BI
Module 24 : Publishing Workbooks and Workspaces
- Share Data with Colleagues and Others
- Publish a report to the web
- Manage published reports
- Share a dashboard
- Create an app workspace and add users
- Use an app workspace
- Publish an app
- Create a QR code to share a tile
- Embed a report in SharePoint Online
Module 25 : Other Power BI Components and Table Relations
- Use Power BI Mobile Apps
- Get Power BI for mobile
- View reports and dashboards in the iPad app
Module 26 : Use Workspaces in Mobile App
- Sharing from Power BI Mobile
- Use Power BI Desktop
- Install and launch Power BI Desktop
- Get data
- Reduce data
- Transform data
- Relate tables
- Get Power BI Desktop data with the Power BI service
- Export a report from Power BI service to Desktop
Module 27 : DAX Functions
- New Dax functions
- Date and time functions
- Time intelligence functions
- Filter functions
- Information functions
- Logical functions
- Math & trig functions
- Parent and child functions
- Text functions
Module 28 : Python Basics
- Comments
- Python Data Structures & Data Types
- String Operations in Python
- Simple Input & Output
- Simple Output Formatting
- Deep copy
- Shallow copy
- Operators in python
Conclusion
By the end of this Data Analytics course, you will have gained the essential skills needed to analyze, visualize, and interpret complex data sets effectively. You’ll be well-versed in using industry-standard tools, applying statistical models, and deriving meaningful insights from data. The comprehensive understanding you’ve developed will empower you to make data-driven decisions and contribute value to any organization. Whether you aim to pursue a career in data analytics, improve your existing skill set, or simply learn how to harness the power of data, this course provides a solid foundation for success in the dynamic field of data analytics.