Power BI

Data Science with Python training Ernakulam Kerala
AXL Power BI certification course will help you gain expertise in Business Analytics. You will master the concepts such as Power BI Desktop, Architecture, DAX, Service, Mobile Apps, Reports, and Q&A, to name a few, with industry use cases.
  • Programmers, Developers, Technical Leads, Architects
  • Developers aspiring to be a ‘Machine Learning Engineer'
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Machine
  • Learning (ML) Techniques
  • Information Architects who want to gain expertise in
  • Predictive Analytics
  • Professionals who want to design automatic predictive models
  • Programmatically download and analyze data
  • Learn techniques to deal with different types of data – ordinal, categorical, encoding
  • Learn data visualization
  • Using I python notebooks, master the art of presenting step by step data analysis
  • Gain insight into the 'Roles' played by a Machine Learning Engineer
  • Describe Machine Learning
  • Work with real-time data
  • Learn tools and techniques for predictive modeling
  • Discuss Machine Learning algorithms and their implementation
  • Validate Machine Learning algorithms
  • Perform Text Mining and Sentimental analysis
  • Explain Time Series and its related concepts
  • Gain expertise to handle business in future, living the present

1. Introduction to Power BI

Learning Objective:This module will introduce you to its building blocks and the various fundamental concepts of Power BI.

  • Business Intelligence
  • Self Service Business Intelligence
  • SSBI Tools
  • Power BI vs Tableau vs QlikView
  • What is Power BI
  • Why Power BI?
  • Key Benefits of Power BI
  • Flow of Power BI
  • Components of Power BI
  • Architecture of Power BI
  • Building Blocks of Power BI
  • Question Bank

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2. Power BI Desktop and Data Transformation

Learning Objective:This module will introduce you to Power BI Desktop. You will know how to extract data from various sources and establish connections with Power BI Desktop, perform transformation operations on data and the Role of Query Editor in Power BI.

  • Overview of Power BI Desktop
  • Data Sources in Power BI Desktop
  • Connecting to a data Sources
  • Query Editor in Power BI
  • Query Ribbon
  • Clean and Transform your data with Query Editor
  • Combining Data – Merging and Appending
  • Cleaning irregularly formatted data
  • Views in Power BI Desktop
  • Modelling Data
  • Manage Data Relationship
  • Automatic Relationship Updates
  • Template Apps
  • Cross Filter Direction
  • Create calculated tables and measures
  • Optimizing Data Models 
  • PBIDS Files
  • Question Bank

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3. Data Analysis Expressions (DAX)

Learning Objective:This module will help you learn the basics of DAX in Power BI Desktop.

  • Essential concepts in DAX
  • Why is DAX important?
  • DAX Syntax
  • Data Types in DAX
  • Ranking and rank over groups
  • Filter and evaluation context
  • Context interactions
  • Calculation Types
  • DAX Functions 
  • Measures in DAX
  • DAX Operators
  • DAX tables and filtering
  • DAX queries
  • Create simple and compound measures
  • Schema relations
  • Star schema design
  • DAX Parameter Naming

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4. Data Visualization Learning Objective: This Power BI online course module will help you understand the benefits and best practices of Data Visualization. It will also help you in creating charts using Custom Visuals.

Learning Objective:This Module helps you get familiar with basics of statistics, different types of measures and probability distributions, and the supporting libraries in Python that assist in these operations. Also, you will learn in detail about data visualization.

  • Introduction to visuals in Power BI
  • Charts in Power BI 
  • Matrixes and tables
  • Slicers
  • Map Visualizations
  • Gauges and Single Number Cards 
  • Create scatter, waterfall, and funnel charts
  • Modifying colors in charts and visuals
  • Shapes, text boxes, and images
  • What Are Custom Visuals?
  • Page layout and formatting  
  • KPI Visuals
  • Z-Order
  • Explore time-based data
  •  AppSource
  • Question Bank

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5. Introduction to Power BI Service,

Learning Objective:This module will help you in creating Dashboards and publishing it on Power BI services. You will also be taught to monitor Real-time Data with REST API.

  • Introduction to Power BI Service
  • Introduction to using workspaces
  • Dashboard vs. Reports
  • Quick Insights in Power BI
  • Creating Dashboards
  • Configuring a Dashboard
  • Power BI Q&A
  • Ask questions of your data with natural language
  • Power BI embedded
  • Create custom Q&A suggestions
  • Edit tile details and add widgets
  • Build apps
  • Integrate OneDrive for Business with Power BI
  • Question Bank 
  • Case Study

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6. Connectivity Modes

Learning Objective:This Power BI course module will help you learn, how to connect data sources directly to Azure, HD Spark, My SQL, and create interactive dashboards.

  • Introduction to using Excel data in Power BI
  • Exploring live connections to data with Power BI 
  • Connecting directly to SQL Azure, HD Spark, SQL Server Analysis Services/ My SQL
  • Introduction to Power BI Development API 
  • Import Power View and Power Pivot to Power BI
  • Data caching and refresh
  • Introducing Power BI Mobile
  • Question Bank

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7. Power BI Report Servers

Learning Objective:This Power BI online course module will help you understand about Power BI Report Servers and data gateways. Also you will learn about the web portal in which you display and manage reports and KPI’s.

  • Report Server Basics
  • Web Portal
  • Paginated Reports
  • Row level Security
  • Data Gateways
  • Scheduled Refresh
  • Configure scheduled refresh
  • Create a publish-to-web embed code
  • Customize the sample Power BI file

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8. Using Python in Power BI

Learning Objective:This module will help you create R and Python visuals in Power BI Desktop as well as in Power BI Service.

  • R Integration in Power BI Desktop
  • R visuals in Power BI
  • R Powered Custom Visuals
  • Creating R visuals in Power BI
  • R Visuals in Power BI Service
  • R Scripts Security
  • Creating visual using Python

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9. Advanced Analytics In Power BI

Learning Objective:This module will help you perform advanced analysis using Anomaly Detection and Smart Narrative visualisation in Power BI.

  • Using Parameters
  • Create a data flow
  • Introduction to Anomaly Detection
  • Introduction to Smart Narrative
  • Introduction to Sensitivity labels in Power BI
  • Deployment Pipeline

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