Power BI online training in Hyderabad India
Power BI is a powerful business analytics tool developed by Microsoft that allows users to visualize and analyze data from various sources in interactive dashboards and reports. It enables organizations to gain insights into their data, identify trends, and make data-driven decisions to drive business success. Power BI offers a wide range of features and capabilities, including data visualization tools, data modeling capabilities, interactive dashboards, natural language queries, and integration with other Microsoft products such as Excel, SharePoint, and Azure.
SNS Tech Academy offers comprehensive Power BI online training in Hyderabad, India, catering to individuals aiming to master the art of data visualization and business intelligence. The training program covers a wide range of Power BI concepts, including data modeling, report building, dashboard design, DAX expressions, data integration, and advanced analytics. Participants engage in hands-on projects, real-world case studies, and personalized mentoring sessions, gaining practical experience in harnessing the full potential of Power BI to derive actionable insights from data. Whether aspiring data analysts, business intelligence professionals, or decision-makers, learners receive expert guidance and certification preparation to excel in today's data-driven business landscape. SNS Tech Academy's Power BI online training equips individuals with the skills and expertise needed to leverage data as a strategic asset, drive informed decision-making, and unlock business value.
Power BI Online Training course content :-
Module 1 : Overview
- Introduction of Power BI
- Introduction to Power BI Suite - Tools & Products
- Install Power BI Desktop tool
- Power BI Desktop walk through
- Power BI Forums & User Community
- Report, Table & Model Views
- Introduce Power BI Terminology
- Demo : Connecting Data using Power BI Desktop
- Power BI : Data source universe
- Direct Query vs Import Data
- Discussing Data Refresh
- Load Data from TXT file (Sales Data As Example)
- Design Table Reports – Basic Level
- Take steps to Improve “Look & Feel” Reporting
- Load Data from Excel file (Finance Data as Example)
- Design Dashboard – Basic Level - II
- Introduction to Power BI Visual Gallery
- Load Data from SQL Database (E-Commerce Data as example)
- Design Dashboard – Intermediate level
- Introduction to Slicing & Dicing in Power BI
Module 2 : Power Query (ETL Tool for Power BI)
Case Study 4 :- Load CSV file (Real time Collisions data as Example)
- Introduce ETL in Power BI – Power Query
- Checking Data Quality - Profiling
- Resolve data quality issues
- Data Cleaning
- Replace null/empty values
- Changing data types
- Dates & Date parts
- Remove columns & Filter rows
- Design Dashboard – Intermediate Level - II
- Think & Act like “Data Analyst”
- Rename Queries/Tables
- Remove Columns (unnecessary)
- Filter Rows (unwanted data)
- Renaming columns
- Fixing Data types
- Replacing values
- Split Columns & Add new columns
- Duplicating/Referencing table/query
- Appending Operations
- Pivot & Unpivot Tables
- Understanding & Performing Merges
- Power Query – M Language
- Working with Folders and Files
Module 3 : Data Modeling
Case Study 5 :- Load Data from Various Sources
- CSV Files (Comma Separated Values)
- TSV Files (Tab Separated Values)
- Web/HTML Files
- Clean Data from source files using Power Query - ETL
- Transform/shape data by following business rules
- Implement Data Modeling :
- Introduce Dimension & Facts
- Introduce Star Schema
- Design Star Schema for Case study
- Introduce DAX
- Design Dashboard – Advanced Level
- Finding facts from Data
- Understand the role of the Data Model in Power BI
- Understand table relationships
- Setup and Manage Relationships
- Understand Cardinality and Cross Filtering
- Discuss Star and Snowflake schema
- Create a Date Dimension
- Build a Data Model from multiple Data sources
- Introduce Adventure Works Data warehouse
- Microsoft recommended DW Example
- Set up Adventure Works for Practice
- Explain Data & Business rules
- Facilitate Documentation
Module 4 : Data Visualization (Power BI Viz)
Case Study 6 :- Load Data from Adventure Works
- Walkthrough Prototype & Requirements
- Brainstorm about data before reporting
- Power Query – For ETL on Data
- Design Dashboard :
- Choosing right visuals
- Formatting visual for Look & feel
- Advantage of Filters – Slicing/Dicing
- Implement Drilldown & Hierarchies
- Design Dashboard – Advanced Level – II
- End to End Power BI workflow
- Scatter & Bubble Charts & Play Axis
- Slicers & Tooltips
- Cross Filtering and Highlighting
- Visual, Page and Report Level Filters
- Hierarchies, Drill Down/Up & Drill through
- Constant Lines & Custom Visuals
- Tables, Matrices & Table Conditional Formatting
- KPI's, Cards & Gauges
- Map Visualizations & Custom Report Themes
- Custom Visualization
Module 5 : DAX (Data Analysis Expression)
- DAX Purpose - Why we need DAX?
- DAX Scope - Usage in Power BI
- Context, Entities, Data Types and Functions
- DAX - Calculations vs Measures
- DAX Operators & Symbols
- Time Intelligence Functions with DAX
- IF..ELSEIF.. Conditions with DAX
- Slicing and Dicing Options with Columns, Measures
- DAX for Query Extraction, Data Mashup Operations
- Advanced DAX Functions & Scenarios
- Row Context & Filter Context
Module 6 : Power BI Online
- Power BI Service vs Power BI Server
- Power BI Service Components
- Publishing a Project to Power BI Service (Web)
- Sharing Reports , Dashboards and Alerts
- Exporting to PowerPoint, PDF and from Viz
- Exploring Power BI Mobile
Module 7 : Power BI – AI Integration
- AI – Powered features in Power BI
- Azure Machine Learning Integration
- Working with Microsoft Fabric
- Working with Power Platform
- Scope of AI in Power BI
Power BI is a business analytics tool developed by Microsoft that allows users to visualize and analyze data from various sources in interactive dashboards and reports. It is used in business intelligence to gain insights into data, identify trends, and make data-driven decisions to drive business success.
The main components of Power BI include Power BI Desktop (for report authoring), Power BI Service (for sharing and collaboration), Power BI Mobile (for accessing reports on mobile devices), and Power BI Gateway (for connecting on-premises data sources).
Power BI Desktop is a desktop application used for creating and designing reports and dashboards, while Power BI Service is a cloud-based platform used for sharing, publishing, and collaborating on reports and dashboards with other users.
A dataset in Power BI is a collection of data that is imported or connected to Power BI for analysis and visualization. Datasets can be created by importing data from files (such as Excel or CSV), connecting to databases or online services, or entering data manually in Power BI Desktop.
Relationships between tables in Power BI are created by defining common fields (keys) between the tables. This can be done in Power BI Desktop by selecting the fields that represent the relationships and creating a one-to-many or many-to-many relationship between them.
DAX (Data Analysis Expressions) is a formula language used in Power BI for creating calculated columns, measures, and calculated tables. DAX formulas are used to perform calculations, manipulate data, and create custom metrics and aggregations in Power BI reports and visualizations.
Slicers in Power BI are visual filters that allow users to interactively filter data in reports and dashboards. Users can select values from slicers to filter data displayed in visuals, enabling dynamic exploration and analysis of data.
Power Query is a data connectivity and preparation tool in Power BI that allows users to connect to and transform data from various sources before loading it into Power BI. Power Query provides a graphical interface for data manipulation, such as cleaning, transforming, and shaping data for analysis.
Reports in Power BI can be published and shared with others using the Power BI Service. Users can publish reports from Power BI Desktop to the Power BI Service, where they can be accessed by other users with appropriate permissions. Reports can also be shared via email, embedded in websites or applications, or exported to various formats such as PDF or PowerPoint.
Some best practices for creating effective Power BI reports include organizing data model and relationships, using meaningful and descriptive field names, creating intuitive and user-friendly visualizations, applying consistent formatting and styling, optimizing performance by limiting data loading and reducing complexity, and regularly updating and refreshing reports with new data.
