Description

This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Finally, this course will show how to build paginated reports within the Power BI service and publish them to a workspace for inclusion within Power BI.

Data Analysts enable businesses to maximize the value of their data assets by using Microsoft Power BI. As a subject matter expert, Data Analysts are responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations. Data Analysts also collaborate with key stakeholders across verticals to deliver relevant insights based on identified business requirements.

The Data Analyst should have a fundamental understanding of data repositories and data processing both on-premises and in the cloud.

Note: This exam will retire on March 31, 2022. A replacement exam, Exam PL-300: Microsoft Power BI Data Analyst, is available.

Course Fee: £1,799+VAT

Objectives

After completing this course, you will be able to:

• Ingest, clean, and transform data
• Model data for performance and scalability
• Design and create reports for data analysis
• Apply and perform advanced report analytics
• Manage and share report assets
• Create paginated reports in Power BI

Who Should Attend

• Data Analyst

Prerequisites

• Basic knowledge of Cloud platform: Azure
• IT industry work experience or those pursuing a degree in the IT field
• Strong learning acumen

Course Outline

Module 1: Prepare the Data

• Get Data from different Data Sources
  • Indentify and Connect to a Data Source
  • change Data Source Settings
  • Select a Shared Dataset or Create a Local Dataset
  • Select a Storage Mode
  • Choose an Appropriate Query Type
  • Indentify Query Performance Issues
  • Use the Common Data Service (CDS)
  • Use Parameters
• Profile the Data
  • Indentify Data Anomalies
  • Examine Data Structures
  • Interrogate Column Properties
  • Interrogate Data Statistics
• Clean, Transform, and Load the Data
  • Resolve Inconsistencies, Unexpected or Null Values, and Data Quality Issues
  • Apply User-friendly Value Replacements
  • Indentify and Create Appropriate Keys for Joins
  • Evaluate and Transform Column Data Types
  • Apply Data Shape Transformations to Table Structures
  • Combine Queries
  • Apply User-friendly Naming Conventions to Columns and Queries
  • leverage Advanced Editor to Modify Power Query M code
  • Configure Data Loading
  • Resolve Data Import Errors

Module 2: Model the Data

• Design a Data Model
  • Define the Tables
  • Configure Table and Column Properties
  • Define Quick Measures
  • Flatten out a Parent-child Hierarchy
  • Define Role-playing Dimensions
  • Define a Relationship’s Cardinality and Cross-filter Direction
  • Design the Data Model to Meet Performance Requirements
  • Resolve Many-to-many Relationships
  • Create a Common Date Table
  • Define the Appropriate Level of Data Granularity
• Develop a Data Model
  • Apply Cross-Filter Direction and Security Filtering
  • Create Calculated Tables
  • Create Hierarchies
  • Create Calculated Columns
  • Implement Row-level Security Roles
  • Set up the Q&A Feature
• Create Measures by using DAX
  • Use DAX to Build Complex Measures
  • Use CALCULATE to Manipulate Filters
  • Implement Time Intelligence using DAX
  • Replace Nmeric Columns with Measures
  • Use Basic Statistical Functions to Enhance Data
  • Create Semi-Additive Measures
• Optimize Model Performance
  • Remove Unnecessary Rows and Columns
  • Indentify Poorly Performing Measures, Relationships, and Visuals
  • Improve Cardinality Levels by Changing Data Types
  • Improve Cardinality Levels Through Summarization
  • Create and Manage Aggregations

Module 3: Visualize the Data

• Create Reports
  • Add Visualization Items to Reports
  • Choose an Appropriate Visualization Type
  • Format and Configure Visualizations
  • Import a Custom Visual
  • Configure Conditional Formatting
  • Apply Slicing and Filtering
  • Add an R or Python Visual
  • Configure the Report Page
  • Design and Configure for Accessibility
• Create Dashboards
  • Set Mobile View
  • manage tiles on a Dashboard
  • Configure Data Alerts
  • Use the Q&A Feature
  • Add a Dashboard Theme
  • Pin a Live Report Page to a Dashboard
  • Configure Data Classification
• Enrich Reports for Usability
  • Configure Bookmarks
  • Create Custom Tooltips
  • Edit and Configure Interactions Between Visuals
  • Configure Navigation for a Report
  • Apply Sorting
  • Configure Sync Slicers
  • Use the Selection Pane
  • Use Drillthrough and Cross Filter
  • Drilldown into Data using Interactive Visuals
  • Export Report Data

Module 4: Analyze the Data

• Enhance Reports to Expose Insights
  • Apply Conditional Formatting
  • Apply Slicers and Filters
  • Perform top N Analysis
  • Explore Statistical Summary
  • Use the Q&A Visual
  • Add a Quick Insights Result to a Report
  • Create Reference Lines by using Analytics Pane
  • Use the Play Axis Feature of a Visualization
• Perform Advanced Analysis
  • Indentify Outliers
  • Conduct Time Series Analysis
  • Use Goupings and Binnings
  • Use the Key Influencers to Explore Dimensional Variances
  • Use the Decomposition Tree Visual to Break Down a Measure
  • Apply AI Insights

Module 5: Deploy and Maintain Deliverables

• Manage Datasets
  • Configure a Dataset Scheduled Refresh
  • Configure Row-level Security Group Membership
  • Providing Access to Datasets
  • Configure Incremental Refresh Settings
  • Endorse a Dataset
• Create and Manage Workspaces
  • Create and Configure a Workspace
  • Recommend a Development Lifecycle Strategy
  • Assign Workspace Roles
  • Configure and Update a Workspace App
  • Publish, Import, or Update Assets in a Workspace

About the Trainer

Certified Microsoft Azure Trainer

Course Fee

£1,799+VAT