Microsoft Power BI Training Course | Power BI Certification

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Microsoft Power BI

Accredited Training Organization
Trained over 2000+ Professionals
Internationally Recognized Trainers
Design and build scalable data models
Cleaning and Transforming data
Learn advanced analytic capabilities
Preparation of an Power BI certification

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Microsoft Power BI is a power full Data Analysts application that enable businesses to maximize the value of their data assets. 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.

Prepare the Data (20-25%)

Model the Data

Develop a data model

Create measures by using DAX

Visualize the Data (20-25%)

Analyze the Data (10-15%)

Deploy and Maintain Deliverables (10-15%)

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 Microsoft Dataverse

• Use parameters

• Use or create a PBIDS file

• Use or create a data flow

• Connect to a dataset using the XMLA endpoint

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

• implement object-level security

• 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

• use Query Diagnostics

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 a paginated report

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

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

• personalize visuals

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

• apply AI Insights

Deploy and Maintain Deliverables (10-15%)

Manage datasets

• configure a dataset scheduled refresh

• configure row-level security group membership

• provide access to datasets

• configure incremental refresh settings

• promote or certify Power BI datasets

• identify downstream dataset dependencies

• configure large dataset format

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

• apply sensitivity labels to workspace content

• use deployment pipelines

• configure subscriptions

• promote or certify Power BI content

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