Introduction to Power BI for Data Analysis and Visualization

MagnaDataSolutions.com
Introduction to Power BI for
Data Analysis & Visualization
Cecilia Brusatori
Magna Data Inc

Cecilia Brusatori
ready
Founder and CEO of Magna Data inc
Data Analytics Solutions and Corporate Training
University Graduate Degree in Computer Science
& Engineering
Tech Community Leader & Organizer in South
Florida US
Proudly Nerd- Always Learning - Naturist –
Love Books & Outdoors Adventures
Entrepreneur- Consultant, Trainer, Speaker
Miami/Fort Lauderdale Area

Agenda
 Microsoft Tech for Analytics & BI Tour
 Intro to Power BI
 Demo: Content Creation Life Cycle
 Sharing
 Licensing
!!! Introductory Session for Beginners – New Users

Please leave me a Review here:
Presentation:
www.MagnaDataSolutions.com/Data-Modeling-101
News & Events: www.MagnaDataSolutions.com
YouTube Channel: www.youtube.com/c/MagnaDataInc
LinkedIn: www.linkedIn.com/company/magnadatainc
Meetup: www.meetup.com/Power-BI-Community-Times
community.fabric.microsoft.com “Miami Power BI Cafe”
Cecilia@MagnaDataSolutions.com
LinkedIn.com/CeBrusa

Microsoft Technology for BI &
Analytics

Analytics on Azure Cloud
Managed Databases
Data Lakes

On-Prem options
 SQL Server
 BI Stack: SSIS, SSAS, SSRS
 Power BI Report Server (PBIRS)
 Power BI Desktop
 Ms Excel

Microsoft Analytics Cloud Platform
ANALYZE & AUTHOR VISUALIZE
Web
Mobile
Power BI Service
Excel
Power BI
Desktop
Power BI Report Builder –
Visual Studio – API - SDK
Synapse Analytics
Data
Warehouses Data Lakes
Data Factory
(ETL/ELT)
Machine Learning
Semantic Models –
Analysis Services
More
M , DAX, SQL
Power BI supported
Languages
*
More
Microsoft Fabric

Microsoft Fabric does it all—in a unified solution
An end-to-end analytics platform that brings together all the data and analytics tools that
organizations need to go from the data lake to the business user
Data Integration
Data Factory
Data Engineering
Synapse
Data Warehouse
Synapse
Data Science
Synapse
Real Time Analytics
Synapse
Business Intelligence
Power BI
UNIFIED
SaaS product experience
Unified data foundation
OneLake
Observability
Data Activator
Security and governance Compute and storage Business model
Source: microsoft

Microsoft Fabric
Data
Factory
Synapse Data
Engineering
Synapse Data
Science
Synapse
Data
Warehousing
Synapse Real
Time
Analytics
Power
BI
Data
Activator
Spark T-SQL
Serverless
Compute
KQL
Analysis
Services
Customers
360
Delta – Parquet
Format
Finance
Delta – Parquet
Format
OneLake
Service
Telemetry
Delta – Parquet
Format
Business
KPIs
Delta – Parquet
Format
Universal security
Shortcuts

Intro to Power BI

Power BI
 Scalable platform for Self Service and
Enterprise Business Intelligence (BI).
 Connect, model, analyze and visualize data.
 Reporting.
 Discover and share insights for Better
decision making
 Integrates beautifully with Excel.
Which makes it the dream platform for any
business
 Public Cloud, Private Cloud (Government)
and On-Premise Platform

Solution Example
Data
Warehouses
Data Lakes
Datasets
Data
Visualizatio
ns / Reports
/
Dashboards
Power BI Service
Cloud data
On-premises
data
Web
Mobile
Machine Learning

Creating content
 From PBI Desktop, Excel, Power BI Report Builder, Visual Studio, SDK,
API, Power BI Service, Tabular Editor, Fabric
 Profiles:
 Data Engineers, Analyst, Business Users
 all levels (tech and non tech)
 Languages:
 ETL: M, SQL, Python, R
 Analysis: DAX, Python, R
 TMDL (Preview): Tabular Model Definition Language

Typical life cycle for reporting
Cloud data
On-premises
data
Power BI
Service
Get Data Build Reports Share Content
Power BI
Desktop
Prepare Data Create Data Model
Data Visualization &
Analysis

DEMO
Creating content with Power BI Desktop. Data Source: Local Excel Workbook File.

Sharing
 Pbix File
 Direct Link to Report
 Workspaces
 Apps
 Embedding
 Website (Public/Secure)
 Custom applications/software
 Intranet (Sharepoint)
 Power Point
 Teams

Sharing- Workspaces
 Environments where content is uploaded and/or created.
 Main purpose: collaboration within a team
 UX Interface is more complex and not intended for consumers.
 Can be assigned to a shared capacity or premium capacity
 Different roles can be assigned to members

Sharing- APPs
 Content type that combines related dashboards and reports, all in one
place.
 UX Interface is simplified for easier navigation.
 Apps are created by Power BI designers who distribute and share
them with consumers(generally a big audience).
 Optimal option for sharing and distributing content

Sharing- Embedding
 Allows developers to embed fully interactive reports and dashboards
into your organization’s own branded applications.
 SDKs, Rest APIs
 Consumption price model

Sharing – Power Point Embedding

Most relevant licenses for Power BI Cloud Services:
 Power BI Desktop is always free
 Power BI Free License: access to “My Workspace” and to Premium content shared with the user
 Power BI Pro: Can Create, Consume and Distribute content. Price: $10/user or 365 E5
 Power BI Premium Per User (PPU): All of Pro features plus some of the important features offered by Premium
Capacities (Example: advanced AI, more Self-Service features, more storage, more refreshes). Price $20/user or as an
add-on $10/user
 Power BI Premium: it is not a license assigned to a specific user, it is a dedicated resource that enables advanced
features. Price starts at $4,995*
 Power BI Embedded: it is a dedicated resource on Azure for application developers, price is variable, starts ~$1/hour.
Link.
 Enter Fabric Capacity: replaced Power BI Premium from SKU F64 up, charged per usage. Required for Fabric Objects.
Cheapest F2 starts at ~$0.215/hour, F64 starts at ~$6.853/hour. Link
*Power BI Premium is not currently available for new purchases and those existents will be transitioned to Fabric Capacities on 2025.

Licensing

Some Performance Tips
Do not bring columns that you won’t be using.
Choose the right data types
Avoid creating unnecessary calculated columns
Design Star Schema for your Data Model
Use Explicit Measures
Disable AutoDateTime. Use Calendar Tables
Try to use the smaller number of items per
page.

THANK YOU!
@magnadatainc MagnaDataSolutions.com
Cecilia@MagnaDataSolutions.com
@CeBrusa

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