Today's large volumes of data can provide insights that are visible only when data is transformed, summarized, and visualized correctly. Important decisions can then be made from relevant and compact information.
Target Audience: IT technicians and business analysts who need to analyze data utilizing Power BI
This collection contains of the following three courses:
Data Analytics using Power BI: Concepts
Business intelligence boils down to knowing how to manage data to draw conclusions from otherwise meaningless information.
Objectives:
- Introduction to Business Intelligence
- describe the purpose of business intelligence
- determine what data is telling you
- describe how data visualizations can convey meaningful messages
- use self-provisioning to work with Power BI
- define Excel functionality related to Power BI
- Getting Started with Microsoft Power BI
- recognize Power BI capabilities
- explain what the Power BI cloud service is used for
- create a personal Power BI service account
- explain what Power BI desktop is used for
- install Power BI Desktop
- use mobile device apps to interact with Power BI dashboards and reports
- install the Power BI app on Windows 10
- determine which region your Power BI tenancy exists in
- recognize when to use Power BI groups
- Practice: Understand Power BI Concepts
- describe Power BI concepts and establish data sources
Data Analytics Using Power BI: Data Sourcing and Preparation
Power BI can draw data from numerous files, databases and web sources. Data must sometimes be transformed for use in analytic software such as Power BI.
Objectives:
- Getting Data into Power BI
- describe where Power BI data comes from
- recognize how Power BI can use data from files
- recognize how Power BI can use data from databases
- recognize how Power BI can use data from online sources
- use Quick Insights in the Power BI Service to quickly generate interactive data visualizations
- import a file data source into Power BI
- import a database data source into Power BI
- import a web URL data source into Power BI
- recognize the purpose of the Power BI Gateway
- configure the Power BI on-premises Gateway
- Data Preparation
- describe why data in its raw form is sometimes not suitable for use with Power BI
- determine when the use of queries is appropriate
- recognize when data should be combined
- explain how row values can be grouped together and how rows can be filtered out to remove unnecessary data
- create an append query
- create a merge query
- filter out rows that are unnecessary
- create a calculated column
- Practice: Prepare Data for Visualization
- ensure data is in a form usable by Power BI for querying and visualization
Data Analytics Using Power BI: Data Modeling and Visualization
Data must sometimes be modeled for use in analytic software such as Power BI. This can reveal patterns and relationships that can be conveyed in a quick and compact form using visualizations.
Objectives:
- Data Modeling
- recognize when to use Data View in Power BI Desktop
- recognize when to use Relationship View in Power BI Desktop
- navigate through Desktop View in Power BI Desktop
- navigate through Relationship View in Power BI Desktop
- explain the purpose of DAX, including syntax
- create a DAX measure formula
- Data Visualization
- define how visualization can quickly convey messages from large datasets
- explain how KPIs are used to measure progress
- explain how to work with and create reports
- create a report in Power BI
- explain how dashboards can be used to monitor data at a glance
- create a custom Power BI dashboard
- share a Power BI dashboard with other users
- filter visualizations using slicers
- Practice: Prepare Data for Visualizations
- ensure data is in a form usable by Power BI for querying and visualization