Power BI Desktop

Power BI – Brief Information Power BI is a business analytics solution that lets you visualize your data and share insights across your organization, or embed them in your app or website. Connect to hundreds of data sources and bring your data to life with live dashboards and reports. interface is simple enough for end users to create their own reports and dashboards. Power BI provides cloud-based BI services, known as "Power BI Services", along with a desktop based interface, called "Power BI Desktop". It offers data warehouse capabilities including data preparation, data discovery and interactive dashboards

Power BI – Key Component Power BI Desktop :- The Windows-desktop-based application for PCs and desktops, primarily for designing and publishing reports to the Service. Power BI Service : online service (now referred to as PowerBI.com or simply Power BI). Power BI Mobile Apps : The Power BI Mobile apps for Android and iOS devices, as well as for Windows phones and tablets. Power BI Gateway :Gateways used to sync external data in and out of Power BI. In Enterprise mode, can also be used by Flows and PowerApps in Office 365. Power BI Embedded : Power BI REST API can be used to build dashboards and reports into the custom applications that serves Power BI users, as well as non-Power BI users. Power BI Report Server : An On-Premises Power BI Reporting solution for companies that won't or can't store data in the cloud-based Power BI Service. Power BI Visuals Marketplace :A marketplace of custom visuals and R-powered visuals.

Workflow of Power BI Desktop Query Editor Data View Report View Data preparation Data modelling Data visualization Relationship View

The Query Editor How we import and prepare our data

Power BI Desktop – Query Editor Data View Report View Relationship View Data preparation Data modelling Data visualization

The Star Schema FACT TABLE DIM TABLE VS

The Star Schema Products IdentifierProd ProductType PricePerUnit CostperUnit DIM TABLE Customers IdentifierCust FirstName SecondName Age Gender DIM TABLE Sales IdentifierProd IdentifierDate IdentifierCust IdentifierGeo UnitsSold TotalSales TotalCost FACT TABLE Time IdentifierDate Year Quarter Month Week Day SalesPoint IdentifierGeo Continent Country City

Our Project – Current structure Population-Combined Country-ID Country Year AgeGroup Gender Population

Out Project turned into a Star Schema Population Country-ID AgeGroup-ID Year Gender FACT TABLE Region Country-ID Country DIM TABLE Age AgeGroup-ID AgeGroup Category DIM TABLE

Query: Duplicate vs. Reference Source file Query Editor C Query 2 (Reference to Query 1) A B Query 1 (Created in Query Editor) Query 2 (Duplicate of Query 1)

Merge Queries - Join Kind Merged Queries LEFT ID Sales Region A 10 USA B 50 n/a C 20 Asia RIGHT ID Region Sales A USA 10 BB Europe n/a C Asia 20 FULL ID Sales Region A 10 USA B 50 n/a C 20 Asia BB Europe Separate Queries Outer Query 1 LEFT Query 2 RIGHT ID Sales A 10 B 50 C 20 ID Region A USA BB Europe C Asia Anti ID Sales Region B 50 n/a ID Region Sales BB Europe n/a Inner ID Sales Region A 10 USA C 20 Asia

Import data into the data model Query 1 Query 2 Default = Enable load is set for all queries Data preparation Query 1 & Query 2 are loaded into the data model Data model Query Editor Data View/Report View Source files Data preparation Enable load is only selected for Query 1 Query 1 is loaded into the data model Data model Import data Query 1 Query 2 Query Editor Data View/Report View

Data View & Relationships How we model our data

Power BI Desktop – Data Modelling Query Editor Data View Report View Relationship View Data preparation Data modelling Data visualization

Query Editor vs. Data Model Connect to source files Clean data Add relationships Add calculated columns Shape data Add measures Structure + prepare data Analyse data

Query Editor vs. Data Model Power BI Desktop Data preparation Data modelling Data visualization Relationship View Query Editor Data View Report View

Let‘s bring our Data Model to live Cardinality = „Type of relationship“

One to many (1:*) & Many to one (*:1) Customers Orders ID-Customer FirstName SecondName 1 Maximilian Schwarzmueller 2 John Meyer 3 Linda Belle 4 Manuel Lorenz ID-Order OrderDate ID-Customer A 01 Jan 2017 1 B 08 Jan 2017 2 C 15 Jan 2017 D 25 Jan 2017 E 05 Feb 2017 3 F 15 Feb 2017 4 Each customer is unique Each customer can have multiple orders

One to one (1:1) Passport Person ID-Passport Valid Issued FirstName SecondName Country 1 2025 2005 Maximilian Schwarzmueller Germany 2 2019 1999 John Meyer USA 3 2017 1997 Linda Belle Japan Passport Person ID-Passport Valid Issued 1 2025 2005 2 2019 1999 3 2017 1997 ID-Passport FirstName Second Name Country 1 Maximilian Schwarzmueller Germany 2 John Meyer USA 3 Linda Belle Japan

Power BI Desktop – Data Model Data preparation Data modelling Data visualization Query Editor Data View Relationship View Report View

Course interim conclusion This course M DAX OR

Calculated Columns vs. Measures Perform an operation that generates results for each row of your table Calculated Column Return a single result of a calculation or an aggregated value (e.g. Averages) Measure

Report View Let‘s create beautiful charts and tables

Power BI Desktop – Report View Data preparation Data modelling Data visualization Query Editor Data View Relationship View Report View