POWER BI COURSE IN AGARTALA

• What is PowerBI?
• Download and Install Power BI Desktop
• Quick Interface Tour
• Mini Project: Transform Data
• Mini Project: Visualize Data
• Mini Project: Creating a Data Model

• Exploring Query Editor
• Connecting to our DataSource
• Editing Rows
• Changing DataTypes
• Replacing values
• Close and Apply
• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Merging Queries
• Pivoting and Unpivoting
• Appending Queries
• Practice and Solution:Population Table
• The Fact-Dimension-Model
• Practice:Load the Dimension Table
• Organizing Our Querires in Groups
• Entering Data Manually
• Creating an Index Column
• Workflow and More Transformation
• Module Summary
• Practice Assignment 1

• Advanced Editor-Best Practices
• Performance: References Versus Duplicating
• Performance: Enable/Disable Load and Report Refresh
• Group By
• Mathematical Operations
• Run Python Script
• Using Parameters to Dynamically Transform Data
• M Formula Language:Basics
• M Formula Language:Values, Lists, and Tables
• M Formula Language: Functions

• Why a Data Model?
• Create and Edit Relationships
• One-to-Many and One-to_One Relationship
• Many-to-Many(m:n) Relationship
• Cross-Filter Direction
• Activate and Deactivate Relationships
• Practice Assignment 2

• Our First Visual
• The Format Tab
• Understanding Tables
• Conditional Formatting
• The Pie Chart
• All about the filter Visual
• The Filter Pane for Developers
• Cross Filtering and Edit Interactions
• Practice Assignment 3
• Synching Slicers across Pages
• Creating Drilldowns
• Creating Drill-Throughs
• The Treemap Visual
• The Decomposition Tree
• Understanding the Matrix Visual
• Editing Pages
• Buttons and Actions
• Bookmarks to Customize Your Report
• Analytics and Forecasts with Line Charts
• Working with Custom Visuals
• Get Data Using Python Script

• Python in Power BI
• Setting Up Python for Power BI
• Transforming Data Using Python
• Creating Visualizations Using Python
• Violin Plots, Pair Plots and Ridge Plots Using Python
• Machine Learning (BayesTextAnalyzer) Using Python

• Introduction
• The Project Data
• Measures Versus Calculated Columns
• Automatically Creating a Data Table in DAX
• Calender
• Creating a Complete Data Table with Features
• Creating a Key Measure Table
• Aggregation Functions
• The Different Versions of COUNT
• SUMX- Row-Based Calculations

• CALCULATE- The Basics
• Changing the Context with FILTER
• ALL
• ALLSELECT
• ALLEXCEPT

• Introduction - Best Practices
• Show Emphaty and Identify the Requirements
• Find the Most Suitable KPIs
• Choose and Effective Visual
• Make Use of Natural Reading Patters
• Tell a Story Using Visual Cues
• Avoid Chaos and Group Information

• JSON and REST API
• Setting UP a Local MYSQL Database
• Connecting to a MYSQL Databased in Power BI
• Connecting to a SQL Database (PostgreSQL)

Power BI is a robust data visualization platform primarily utilised for business intelligence purposes. It empowers users to create interactive and visually appealing dashboards that can display and report data using various formats, including maps, graphs, charts, and scatter plots.

• Proficient Data Visualization

• Data Analysis Abilities

• Effective Communication

• Problem-Solving Skills

• Data Science Knowledge

• Project Management Competence

Various tools are available for data visualisation, including:

• Tableau

• Grafana

• Chart.js

• FusionCharts

• Infogram

• Google Data Studio

Power BI serves several purposes in the business world, including:

• Creating interactive dashboards to present data sets in diverse visual formats.

• Connecting and transforming data from sources like Excel sheets, data warehouses, and cloud-based storage into actionable business insights.

• Generating various data visuals, such as Pie charts, Gauge charts, KPIs, Combo charts, Column charts, and Decomposition trees.

The essential components of Power BI include:

• Power Query

• Power Pivot

• Power View

• Power Map

• Power Q&A

• Power BI Desktop

• Power BI Mobile Apps

• Power BI Website

Agartala offers a range of job roles in the Power BI domain, including:

• Business Intelligence Manager

• Business Intelligence Analyst

• Data Analyst

• Business Analyst

• Power BI Developer

• Power BI Analyst

• Business Intelligence Developer

The salary of a Power BI developer in Agartala ranges from INR 1,500,000 per year according to a Talent.com report.

Power BI is extensively employed by data analysts and business intelligence professionals who design data models and distribute reports across organizations. It is utilized by both departmental and managerial roles to monitor employee progress and track goal attainment.

Power BI can be relatively accessible for individuals with prior experience in data analysis and visualization tools. However, like any software, there is a learning curve to master Power BI's functionalities. It provides an intuitive interface with drag-and-drop capabilities, along with a variety of pre-built templates and visuals for creating polished reports and dashboards.

The key characteristics of Power BI encompass rapid insights, support for a common data model, artificial intelligence capabilities, hybrid deployment support, integration with Cortana, and extensive customization options.