Become a Microsoft Power BI Data Analyst
Become a Microsoft Power BI Data Analyst, available at $49.99, has an average rating of 3.83, with 135 lectures, 10 quizzes, based on 6 reviews, and has 39 subscribers.
You will learn about Prepare the data Get data from different data sources Clean, transform, and load the data Model the data Design a data model Develop a data model Create model calculations by using DAX Optimize model performance Visualize and analyze the data Create reports Create dashboards Enhance reports for usability and storytelling Identify patterns and trends Deploy and maintain assets Manage files and datasets Manage workspaces This course is ideal for individuals who are Beginner Data Analyst or Beginner Power BI Data Analyst It is particularly useful for Beginner Data Analyst or Beginner Power BI Data Analyst.
Enroll now: Become a Microsoft Power BI Data Analyst
Summary
Title: Become a Microsoft Power BI Data Analyst
Price: $49.99
Average Rating: 3.83
Number of Lectures: 135
Number of Quizzes: 10
Number of Published Lectures: 134
Number of Published Quizzes: 10
Number of Curriculum Items: 145
Number of Published Curriculum Objects: 144
Original Price: $119.99
Quality Status: approved
Status: Live
What You Will Learn
- Prepare the data
- Get data from different data sources
- Clean, transform, and load the data
- Model the data
- Design a data model
- Develop a data model
- Create model calculations by using DAX
- Optimize model performance
- Visualize and analyze the data
- Create reports
- Create dashboards
- Enhance reports for usability and storytelling
- Identify patterns and trends
- Deploy and maintain assets
- Manage files and datasets
- Manage workspaces
Who Should Attend
- Beginner Data Analyst
- Beginner Power BI Data Analyst
Target Audiences
- Beginner Data Analyst
- Beginner Power BI Data Analyst
The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.
Prepare the data – ( Get data from different data sources)
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Identify and connect to a data source
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Change data source settings
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Select a shared dataset or create a local dataset
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Select a storage mode
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Use Microsoft Dataverse
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Change the value in a parameter
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Connect to a data flow
Clean, transform, and load the data
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Profile the data
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Resolve inconsistencies, unexpected or null values, and data quality issues
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Identify and create appropriate keys for joins
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Evaluate and transform column data types
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Shape and transform tables
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Combine queries
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Apply user-friendly naming conventions to columns and queries
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Configure data loading
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Resolve data import errors
Model the data – ( Design a data model )
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Define the tables
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Configure table and column properties
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Design and implement role-playing dimensions
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Define a relationship’s cardinality and cross-filter direction
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Design a data model that uses a star schema
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Create a common date table
Develop a data model
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Create calculated tables
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Create hierarchies
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Create calculated columns
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Implement row-level security roles
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Use the Q&A feature
Create model calculations by using DAX
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Create basic measures by using DAX
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Use CALCULATE to manipulate filters
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Implement Time Intelligence using DAX
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Replace implicit measures with explicit measures
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Use basic statistical functions
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Create semi-additive measures
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Use quick measures
Optimize model performance
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Remove unnecessary rows and columns
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Identify poorly performing measures, relationships, and visuals
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Reduce cardinality levels to improve performance
Visualize and analyze the data ( Create reports & Dashboards)
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Add visualization items to reports
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Choose an appropriate visualization type
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Format and configure visualizations
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Use a custom visual
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Apply and customize a theme
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Configure conditional formatting
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Apply slicing and filtering
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Configure the report page
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Use the Analyze in Excel feature
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Choose when to use a paginated report
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Manage tiles on a dashboard
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Configure mobile view
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Use the Q&A feature
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Add a Quick Insights result to a dashboard
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Apply a dashboard theme
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Pin a live report page to a dashboard
Enhance reports for usability and storytelling
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Configure bookmarks
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Create custom tooltips
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Edit and configure interactions between visuals
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Configure navigation for a report
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Apply sorting
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Configure Sync Slicers
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Group and layer visuals by using the selection pane
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Drilldown into data using interactive visuals
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Export report data
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Design reports for mobile devices
Identify patterns and trends
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Use the Analyze feature in Power BI
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Identify outliers
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Choose between continuous and categorical axes
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Use groupings, binnings, and clustering
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Use AI visuals
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Use the Forecast feature
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Create reference lines by using the Analytics pane
Deploy and maintain assets (Manage files, datasets and Manage workspaces)
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Identify when a gateway is required
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Configure a dataset scheduled refresh
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Configure row-level security group membership
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Provide access to datasets
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Manage global options for files
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Create and configure a workspace
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Assign workspace roles
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Configure and update a workspace app
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Publish, import, or update assets in a workspace
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Apply sensitivity labels to workspace content
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Configure subscriptions and data alerts
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Promote or certify Power BI content
Course Curriculum
Chapter 1: Introduction to Microsoft Data Analytics
Lecture 1: Introduction
Lecture 2: Microsoft Data Analytics
Lecture 3: Overview of Data Analysis
Lecture 4: Roles in Data Analysis
Lecture 5: Tasks of a Data Analyst
Chapter 2: Power BI Setup
Lecture 1: What is Power BI
Lecture 2: What is Power BI Desktop
Lecture 3: Install Power BI Desktop
Lecture 4: Exploring Power BI Desktop Interface
Lecture 5: Microsoft 365 Setup
Lecture 6: Getting started with Microsoft 365
Lecture 7: Creating a new user account in Microsoft 365
Chapter 3: Power BI Data Sources
Lecture 1: Getting data into Power BI Desktop
Lecture 2: Connect to data in a file
Lecture 3: Connect to data in a database
Lecture 4: Connect to data in Power Platform
Lecture 5: Connect to Azure SQL Database
Lecture 6: Data Source Settings
Lecture 7: Storage Modes
Chapter 4: Power BI Overview
Lecture 1: Introduction
Lecture 2: Power BI Overview : Part 1
Lecture 3: Power BI Overview : Part 2
Lecture 4: Power BI Overview : Part 3
Lecture 5: Parts of Power BI
Lecture 6: Power BI Building blocks
Lecture 7: Exploring Power BI Service
Chapter 5: Building with Power BI
Lecture 1: Building blocks of Power BI
Lecture 2: The flow of work in Power BI
Lecture 3: Tour and use of Power BI Service
Lecture 4: Update data in Power BI Service
Lecture 5: Summary
Chapter 6: Connect & Transform Online Data
Lecture 1: Connect to Web Data
Lecture 2: Clean & transform data : Part 1
Lecture 3: Clean & transform data : Part 2
Lecture 4: Combine data sources
Lecture 5: Creating Data Visuals : Part 1
Lecture 6: Creating Data Visuals : Part 2
Lecture 7: Publish report to Power BI Service
Chapter 7: SQL Server Setup
Lecture 1: What is SQL Server
Lecture 2: SQL Server Editions
Lecture 3: SQL Server Installation Requirements
Lecture 4: Download SQL Server
Lecture 5: SQL Server Installation
Lecture 6: SQL Server Configuration Manager
Lecture 7: Installing SQL Server Management Studio
Lecture 8: Connect to SQL Server with SSMS
Lecture 9: Restore AdventureWorksDW2020 Database
Chapter 8: Prepare data ( Get data from different data sources )
Lecture 1: Introduction
Lecture 2: Get data from online services
Lecture 3: Get data from a NoSQL database
Lecture 4: Create and save a new Power BI Desktop file
Lecture 5: Set Power BI Desktop options
Lecture 6: Get data from relational data sources
Lecture 7: Preview SQL Server queries
Lecture 8: Get data from files
Lecture 9: Get data from a CSV file
Lecture 10: Get additional data from a CSV file
Lecture 11: Change the source file
Lecture 12: Selecting a storage mode
Lecture 13: Get data from Azure Analysis Services
Lecture 14: Resolve data import errors
Lecture 15: Summary
Chapter 9: Clean, transform, and load data in Power BI
Lecture 1: Introduction
Lecture 2: Fix performance issues
Lecture 3: Shape the initial data
Lecture 4: Configure the Salesperson query
Lecture 5: Configure the SalespersonRegion query
Lecture 6: Configure the Product query
Lecture 7: Configure the Reseller query
Lecture 8: Configure the Region query
Lecture 9: Configure the Sales query
Lecture 10: Configure the Targets query
Lecture 11: Configure the ColorFormats query
Lecture 12: Update the Product query
Lecture 13: Update the ColorFormats query
Chapter 10: Model Data In Power BI Desktop
Lecture 1: Introduction
Lecture 2: Create Model Relationships
Lecture 3: Configure the Product table
Lecture 4: Configure the Region table
Lecture 5: Configure the Reseller table
Lecture 6: Configure the Sales table
Lecture 7: Bulk update properties
Lecture 8: Review the model interface
Lecture 9: Create quick measures
Lecture 10: Create a many-to-many relationship
Lecture 11: Relate the Targets Table
Instructors
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Bluelime Learning Solutions
Making Learning Simple
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 1 votes
- 3 stars: 0 votes
- 4 stars: 1 votes
- 5 stars: 3 votes
Frequently Asked Questions
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Can I take my courses with me wherever I go?
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