Analyzing Data with Microsoft Power BI
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.
About this Course
The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.
Outline
Prepare the Data (20-25%)
Get data from different data sources
· identify 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
· identify query performance issues
· use the Common Data Service (CDS)
· use parameters
Profile the data
· identify 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
· identify 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
Model the Data (25-30%) 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 numeric columns with measures
· use basic statistical functions to enhance data
· create semi-additive measures
Optimize model performance
· remove unnecessary rows and columns
· identify poorly performing measures, relationships, and visuals
· improve cardinality levels by changing data types
· improve cardinality levels through summarization
· create and manage aggregations
Visualize the Data (20-25%) 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
· configure automatic page refresh
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 drill through and cross filter
· drilldown into data using interactive visuals
· export report data
· design reports for mobile devices
Analyze the Data (10-15%)
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
· identify outliers
· conduct Time Series analysis
· use groupings and binnings
· use the Key Influencers to explore dimensional variances
· use the decomposition tree visual to break down a measure
Deploy Maintain Deliverables (10-15%) Manage datasets
· configure a dataset scheduled refresh
· configure row-level security group membership
· providing access to datasets
· configure incremental refresh settings
· promote or certify 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
Prerequisites
To get the most out of this training, it would be best to know the following:
- Basic computer skills (PC/Windows)
- Familiarity with various mouse controls (Left click, Right-click, Drag & Drop…)
- Exposure to structured data (Microsoft Excel spreadsheet, CSV, Text Table…)
- Understand the difference between a “Flat file” and a Database
- Awareness of data types (Boolean, Integer, Date, String…)
- Awareness of basic chart types (Bar chart, Time Series, Scatterplot…)
- Dual Monitors are required for this class
Exam Details
Exam PL-300: Microsoft Power BI Data Analyst
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