Powering Up with Power BI Brian Larson & Lily Vergara Superior Consulting Services, LLC Powering Up with Power BI

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Brian Larson 15 years experience with Microsoft Data Visualization Tools Contributed to the initial codebase of SQL Server Reporting Service Regional and National Speaker Author on Business Intelligence and Data Visualization topics for McGraw-Hill Professional

Lily Vergara Certified Microsoft Data Scientist and Business Intelligence Consultant Experience working in manufacturing, retail, restaurant, agriculture, health insurance, and higher education I enjoy long walks with datamarts on the beach, DAX by candlelit dinner, and curling up with a duvet coding some R

Course Outline Power BI Architecture Power BI Desktop Direct Connect with Power BI Desktop Basic Visualizations Data Import and Transformations Tabular Data Model Building Measures and DAX Expressions Advanced Visualizations Power BI Report Server Power BI Desktop Report Viewer Power BI Service Navigation Features Workspaces Content Packs and Apps Subscriptions Refreshing Data with Gateway Administration Power BI Mobile App

Power BI Architecture Brian

Power BI Architecture Power BI is… a set of tools from Microsoft designed to provide business users with self-service business intelligence capabilities. Brian

Power BI Architecture Power BI Desktop (pbix file) Tabular Data Storage Visualizations Model Structure Source Data Query Editor Brian

Power BI Architecture Power BI Desktop (pbix file) Tabular Data Storage Model Structure Visualizations Query Editor Source Data Brian

Power BI Architecture Power BI Service Power BI Report Server Deploy Brian Power BI Service Power BI Report Server

Power BI Connection Types Components Stored in… Works with… Data Source Power BI Visualizations Model Structure Data SQL Server Analysis Services DAX/MDX Queries Live Connection Live Connection Visualizations Data Model Structure SQL Server Relational DB, Azure SQL Database, Azure SQL Data Warehouse, SAP HANA T-SQL Queries Direct Query Direct Query Data Visualizations Model Structure All supported Power BI data sources including those listed above. Import Import

Power BI Desktop Brian

Direct Connect with Power BI Desktop Brian Demonstration

Basic Visualizations Brian Demonstration

Data Import and Transformations Brian Demonstration

Tabular Data Model Building User Friendly Models – star schema Relationships –establish and maintain Hierarchies – how to build, start with highest level Demonstration

Measures and DAX Expressions Brian

Default Context in a Measure Default Context is the table Brian

Measures Respond to Filters and Slicers Only Andy Only 2015 Only Guiding Lights Brian Measures respond to the context created by filters and slicers

Measures Respond to Filters and Slicers Sales Tax:=SUM('Orders'[StoreSales]) * 0.07775 2015 Guiding Lights Orders for Andy 2015 Guiding Lights Orders By Product Type By Sales Person Sales Tax $50,652.48 Only 2015 . . . . . . . . . All Orders 2015 Orders 2015 Woodland Creatures Orders for Zeb Brian 2015 Woodland Creatures Orders Filter Sales Tax $490,457.43 Slice Slice Calculate Measure

Aggregate in a Calculate Column Does not react to User Filters Brian Calculated Column becomes an Attribute

Filter Condition in a Measure Large Order Sales:=CALCULATE([Sales in Dollars], Orders[StoreSales]>150) 2015 Guiding Lights Orders for Andy 2015 Guiding Lights Orders > $150 Large Order Sales {None} By Product Type By Sales Person Only 2015 . . . . . . . . . . . . All Orders 2015 Orders 2015 Woodland Creatures Orders for Zeb > $150 Brian 2015 Woodland Creatures Orders Large Order Sales $4,766,105.40 User Filter Measure Filter User Slice User Slice Calculate Measure

Same Attribute in Slicer & Measure Filter Guiding Lights Sales:= CALCULATE([Sales in Dollars], 'Products'[Product Type]="Guiding Lights") 2015 Guiding Lights Orders for Andy 2015 Guiding Lights Orders Guiding Lights 2015 Guiding Lights Sales for Andy $651,478.80 X By Product Type By Sales Person Only 2015 . . . . . . . . . . . . All Orders 2015 Orders 2015 Guiding Lights Sales for Zeb $2,120,164.20 Guiding Lights 2015 Woodland Creatures Orders for Zeb Brian 2015 Woodland Creatures Orders X User Filter Measure Filter User Slice User Slice Calculate Measure

Multiple Attributes Filtered in Measure Guiding Lights 2014 Sales:= CALCULATE([Sales in Dollars], 'Products'[Product Type]="Guiding Lights", 'Time'[Year]=2014) X 2015 Guiding Lights Orders for Andy 2014 Guiding Lights Sales for Andy $703,915.80 Guiding Lights 2015 Guiding Lights Orders X By Product Type By Sales Person Only 2015 . . . . . . . . . . . . All Orders 2015 Orders X 2014 Guiding Lights Sales for Zeb $2,115,498.00 Guiding Lights 2015 Woodland Creatures Orders for Zeb Brian 2015 Woodland Creatures Orders X User Filter Measure Filter User Slice User Slice Calculate Measure

Overriding a User Filter/Slicer with ALL() Guiding Lights All Years Sales:= CALCULATE([Sales in Dollars], 'Products'[Product Type]="Guiding Lights", ALL('Time'[Year])) X Guiding Lights Sales for Andy $2,069,970.00 2015 Guiding Lights Orders for Andy Guiding Lights 2015 Guiding Lights Orders X By Product Type By Sales Person Only 2015 . . . . . . . . . . . . All Orders 2015 Orders X Guiding Lights Sales for Zeb $6,323,343.60 Guiding Lights 2015 Woodland Creatures Orders for Zeb Brian 2015 Woodland Creatures Orders X User Filter Measure Filter User Slice User Slice Calculate Measure

Overriding Filter/Slicer with ALLEXCEPT() All Sales Selected Year:= CALCULATE([Sales in Dollars], ALLEXCEPT('Orders', 'Time'[Year])) 2015 Guiding Lights Orders for Andy Guiding Lights 2015 Sales $161,815,808.92 2015 Guiding Lights Orders X By Product Type By Sales Person Only 2015 X . . . . . . . . . . . . All Orders 2015 Orders Guiding Lights 2015 Sales $161,815,808.92 2015 Woodland Creatures Orders for Zeb Brian 2015 Woodland Creatures Orders X User Filter X Measure Filter User Slice User Slice Calculate Measure

RELATED() Function Orders Product =RELATED(Products[Retail Price]) 2 Unit Price 2 $22.05 5 $15.75 6 $14.70 4 $25.20 Product Code Product Retail Price 2 Boston, MS Harbor Lighthouse $22.05 3 Cape Hatteras, NC Lighthouse $18.90 4 Portland, ME Lighthouse $25.20 5 Split Rock, MN Lighthouse $15.75 6 Manitowoc, WI Lighthouse $14.70 Brian

LOOKUPVALUE() Function =LOOKUPVALUE(Products[Retail Price], [Product Code], [Product]) Orders Product X Product Unit Price 2 $22.05 5 $15.75 6 $14.70 4 $25.20 Product Code Product Retail Price 2 Boston, MS Harbor Lighthouse $22.05 3 Cape Hatteras, NC Lighthouse $18.90 4 Portland, ME Lighthouse $25.20 5 Split Rock, MN Lighthouse $15.75 6 Manitowoc, WI Lighthouse $14.70 Brian Relationship created on the fly

SUMX() Iterative Function Calcd Total Sales:=SUMX('Orders', 'Orders'[Unit Price] * 'Orders'[UnitSales]) 30.80 * 4 = 123.20 Brian 123.20

SUMX() Iterative Function Calcd Total Sales:=SUMX('Orders', 'Orders'[Unit Price] * 'Orders'[UnitSales]) 30.80 * 4 = 123.20 Brian 246.40

SUMX() Iterative Function Calcd Total Sales:=SUMX('Orders', 'Orders'[Unit Price] * 'Orders'[UnitSales]) 30.80 * 4 = 123.20 Brian 369.60

SUMX() Iterative Function Calcd Total Sales:=SUMX('Orders', 'Orders'[Unit Price] * 'Orders'[UnitSales]) 29.40 * 4 = 117.60 Brian 487.20

Using the FILTER() Function Total Sales for Medium Priced Items:=SUMX(FILTER('Orders',Orders[Unit Price] >= 20.00 && Orders[Unit Price] <= 30.00), 'Orders'[Unit Price] * 'Orders'[UnitSales]) 2015 Guiding Lights Orders for Andy Medium Priced Items Total Sales for Medium Priced Items $236,048.40 2015 Guiding Lights Orders By Product Type By Sales Person Only 2015 . . . . . . . . . . . . All Orders 2015 Orders Medium Priced Items Total Sales for Medium Priced Items $657,643.20 2015 Woodland Creatures Orders for Zeb Brian 2015 Woodland Creatures Orders User Filter User Slice User Slice Measure Filter Calculate Measure

Using the FILTER() Function Total Sales for Medium Priced Items:=SUMX(FILTER('Orders',Orders[Unit Price] >= 20.00 && Orders[Unit Price] <= 30.00), 'Orders'[Unit Price] * 'Orders'[UnitSales]) 2015 Guiding Lights Medium Priced Item Orders for Andy 2015 Guiding Lights Orders for Andy SUMX(…) Iterates through the virtual table calculating the sum of the [Unit Price] * [UnitSales] FILTER(…) Filtered Rows Virtual Table New Virtual Table Brian

Using the DATESYTD() Function YTD Sales:=CALCULATE([Sales in Dollars], DATESYTD('Time'[Date])) 2015 Guiding Lights Orders for January Set of Dates YTD Guiding Lights January 2015 YTD Sales $1,212,750.00 2015 Guiding Lights Orders By Product Type By Month of Year Only 2015 . . . . . . . . . . . . All Orders 2015 Orders Set of Dates YTD Woodland Creatures December 2015 YTD Sales $41,577,790.20 2015 Woodland Creatures Orders for December Brian 2015 Woodland Creatures Orders User Filter User Slice User Slice Measure Filter Calculate Measure

Using the DATESYTD() Function YTD Sales:=CALCULATE([Sales in Dollars], DATESYTD('Time'[Date])) 2015 Guiding Lights Orders for January 2015 Guiding Lights Orders for January SUM(…) Sum all Sales in the Virtual Table DATESYTD(…) Filtered Rows Virtual Table New Virtual Table Brian

Using the DATESYTD() Function YTD Sales:=CALCULATE([Sales in Dollars], DATESYTD('Time'[Date])) 2015 Guiding Lights Orders for January - February 2015 Guiding Lights Orders for February SUM(…) Sum all Sales in the Virtual Table DATESYTD(…) Filtered Rows Virtual Table New Virtual Table Brian

Using the DATESYTD() Function YTD Sales:=CALCULATE([Sales in Dollars], DATESYTD('Time'[Date])) 2015 Guiding Lights Orders for January - March 2015 Guiding Lights Orders for March SUM(…) Sum all Sales in the Virtual Table DATESYTD(…) Filtered Rows Virtual Table New Virtual Table Brian

Using the PARALLELPERIOD() Function Prev Qtr Sales:=CALCULATE([Sales in Dollars], PARALLELPERIOD('Time'[Date],-1, QUARTER)) 2015 Guiding Lights Orders for Quarter 1 Set of Dates Prev Quarter Guiding Lights Quarter 1 2015 Prev Qtr Sales $3,534,379.80 2015 Guiding Lights Orders By Product Type By Month of Year Only 2015 . . . . . . . . . . . . All Orders 2015 Orders Dates Prev Quarter Set of Woodland Creatures Quarter 4 2015 Prev Qtr Sales $10,572,865.72 2015 Woodland Creatures Orders for Quarter 4 Brian 2015 Woodland Creatures Orders User Filter User Slice User Slice Measure Filter Calculate Measure

Using the PARALLELPERIOD() Function Prev Qtr Sales:=CALCULATE([Sales in Dollars], PARALLELPERIOD('Time'[Date],-1, QUARTER)) 2014 Guiding Lights Orders for Quarter 4 2015 Guiding Lights Orders for Quarter 1 SUM(…) Sum all Sales in the Virtual Table PARALLELPERIOD(…) Filtered Rows Virtual Table New Virtual Table Brian

Using the PARALLELPERIOD() Function Prev Qtr Sales:=CALCULATE([Sales in Dollars], PARALLELPERIOD('Time'[Date],-1, QUARTER)) 2015 Guiding Lights Orders for Quarter 1 2015 Guiding Lights Orders for Quarter 2 SUM(…) Sum all Sales in the Virtual Table PARALLELPERIOD(…) Filtered Rows Virtual Table New Virtual Table Brian

Using the DATESBETWEEN() Function Curr Qtr Sales:=CALCULATE([Sales in Dollars], DATESBETWEEN('Time'[Date], STARTOFQUARTER('Time'[Date]), ENDOFQUARTER('Time'[Date]))) 2015 Guiding Lights Orders for Quarter 1 2015 Guiding Lights Orders for January SUM(…) Sum all Sales in the Virtual Table DATESBETWEEN(…) Filtered Rows Virtual Table New Virtual Table Brian

Using Variables in a Measure Qtr Over Qtr Sales Growth:= VAR QtrOverQtrDiff = [Curr Qtr Sales] - [Prev Qtr Sales] return IF([Prev Qtr Sales] <> 0, DIVIDE(QtrOverQtrDiff, [Prev Qtr Sales])) Brian

Advanced Visualizations Out of The Box Features, Custom Visuals, and R Scripting Lily •Power BI service supports viewing and interacting with visuals created with R scripts. Visuals created with R scripts, commonly called R visuals, can present advanced data shaping and analytics such as forecasting, using the rich analytics and visualization power of R. •Demonstrate this feature by having R installed on the presentation laptop or server where data is sourced, install common package ggplot, create 2 visualization showing capability Demonstration

Custom Visualizations Office Store Community-sourced R Powered Custom Visuals R Script Showcase R scripted visualizations Data visualizations allow you to interact with your data to find business insights. Power BI lets you choose from a list of available visualizations, add a custom visualization that you create yourself, or select from our expanding list of available visualizations in the community gallery. Custom Visualizations: The Office store contains custom visualizations created by members of the community and by Microsoft. These visualizations can be downloaded and added to Power BI Service reports and Power BI Desktop reports. All of these custom visuals have been approved by Microsoft and they behave just similar to the native visualizations included with Power BI; they can be filtered, highlighted, edited, shared, etc. You can use R-powered custom visuals without any knowledge of R, and without any R scripting. This enables you to harness the analytic and visual power of R visuals, and R scripts, without learning R or doing any programming yourself. https://store.office.com/search.aspx?productgroup=PowerBI&ui=en-US&rs=en-US&ad=US&catfltr=1&clickedfilter=AppCategoryFilter%3AAdvanced%20Analytics&category=Advanced%2BAnalytics

Open Source Software Environment Introduction to R Open Source Software Environment Extracting Data Transforming Data Loading Data Analyzing Organizing Summarizing Programming Language Statistics Graphing Cross Platform Linux Windows MacOS FreeBSD Used By Statisticians Data Scientists Developers Programmers IT Professionals Analysts R is a free, open source software environment and programming language for statistical computing and graphics. R provides a wide variety of statistical techniques, including linear and non-linear modeling, classical statistical tests, time-series analysis, classification, clustering, machine learning, among many more. Also used for ETL. R is for analyzing, organizing, summarizing data Cross platform: It compiles and runs on a wide variety of UNIX platforms, FreeBSD, Linux, Windows, and MacOS. R is used by statisticians, data scientists, developers, programmers, IT professionals, analyst, etc. R operates on built-in functions and self developed packages that target different technique and graphical aspects of data analysis. Packages as a group of functions, datasets, compiled codes, or documentation. Contents of package are downloaded from Comprehensive R Archive Network (CRAN) and stored on local machine. The current R is the result of a collaborative effort with contributions from all over the world. R was initially written by Robert Gentleman and Ross Ihaka—also known as “R & R” of the Statistics Department of the University of Auckland.

Microsoft Power BI Analytics Features With A Brief History of R Integration 1970’s-1980’s John Chambers, Bell Labs S Language Publicly Made Available 1993 R Founded Ross Ihaka and Robert Gentleman 1995-1997 R Released under GNU Public License (GPL) R Mailing Lists Comprehensive R Archive Network Established 2000 R 1.0.0 Released Stable for Production Use 2007 Revolution Analytics Founded Purpose of R Development, Support, Services, and Consulting 2015 Microsoft Acquires Revolution Analytics R Consortium Organized (Microsoft, Rstudio, Alteryx, Google, Hewlett Packard, Ketchum Trading, Mango Solutions, Oracle) Custom Visuals R Integration (R Scripted Visuals) 2016 Grouping and Binning Include/Exclude Data Points Forecasting TopN Filter R Powered Custom Visual Use your own R IDE Analytics Pane Dynamic Reference Lines 2017 Explain the Increase/Decrease Insights What-If Parameters Symmetry Shading and Ratio Lines in Scatterplot Quick Measures Show Values as Clustering 1970s-1980s: Before there was R, there was S. 1993: The current R is the result of a collaborative effort with contributions from all over the world. R was initially written by Robert Gentleman and Ross Ihaka—also known as “R & R” of the Statistics Department of the University of Auckland. 2015: Revolution Analytics Purchased by Microsoft: Revolution Analytics focuses on big data, large scale multiprocessor (or "high performance") computing, and multi-core functionality. 2015: Enhanced distribution of R: MRAN-Time stamped Version of CRAN, Multithreaded Performance-Math Kernel libraries, and Reproducible R Toolkit

R is among the most popular and widely used analytics tools Used across a variety of industries: automotive, social media, retail, technology, government, travel, real estate, etc. In RedMonk’s 2017 Q1 study on programming languages rank from GitHub projects and stack overflow tags, R was ranked among the top 15 in programming languages Ranked number 1 analytics tool used by analytics professionals according to Rexer Analytics 2015 Data Science Survey Ranked number 2 in self-service BI, next to Excel Show the audience the website to download R-from MRAN: https://mran.microsoft.com/documents/getting-started/

Power BI Report Server

Power BI Report Server A Suite of Products Paginated reports Mobile reports Power BI Report Server is a solution that customers deploy on their own premises for creating, publishing, and managing reports, then delivering them to the right users in different ways, whether that’s viewing them in web browser, on their mobile device, or as an email in their in-box. A modern web portal you can view in any modern browser. In the web portal, you can organize and display reports and KPIs. You can also store Excel workbooks on the portal. View PBI Desktop reports, paginated reports, and mobile reports within the web portal in your own environment.

Power BI Report Server Demonstration

Power BI Service Lily From the open .pbix, publish to service, select workspace, publish from power bi desktop OR Navigate to PowerBI.com Supported browsers: Microsoft Edge Internet Explorer 11 Chrome desktop latest version Safari Mac latest version Firefox desktop latest version

Power BI Service Features Demonstration

Power BI and Excel Integration Demonstration

Workspaces Demonstration

Sharing and Receiving Reports and Dashboards Share Dashboard, Create and View Content Packs and Apps Email Subscriptions Demonstration

Data Gateway

Gateway Personal Data Gateway On-premises Data Gateway Personal, prototype use Impersonates you Available with Power BI Pro Computer must be on Computer must have internet connection You have to be logged in or run services as an admin (run as an autonomous service running in the back ground) On-premises Data Gateway For production enterprise use Installed on server, available 24/7 Always on and not asleep Direct internet connection, not wireless Runs as local services The on-premises data gateway acts as a bridge, providing quick and secure data transfer between on-premises data (data that is not in the cloud) and the Power BI, Microsoft Flow, Logic Apps, and PowerApps services.

Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises Service Bus: piece of middleware that allows applications to communicate indirectly Key to enabling hybrid solutions Everything done via outbound requests Different ways to download gateway Power BI.com When logged in, download arrow on navigation bar Dataset ellipses>Datasets>manage gateways>learn more Can only have one gateway on server Requirements .Net 4.5 64 bit windows Windows 7 or higher Windows Server 2008 R2 or higher Recommendations 8 core 8 GB RAM Windows Server 2012 R2 or higher Network Requirements Internet connectivity No inbound ports Outbound ports 443 login/general 5671, 5672 messaging protocol 9350-9354 service bus listeners Install and Configure Identify the account to use with the gateway, service account (O365 login) Gateway name Recovery key: used for disaster or migration Application Gateway Data Source

Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Q/DS/C A model refresh or Direct Query queues up a request with Query/Data Source/Credentials (encrypted) Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises Application Gateway Data Source

The request is analyzed by the Gateway Cloud Service Data Gateway Q/DS/C Power BI Model Gateway Queue Gateway Cloud Service The request is analyzed by the Gateway Cloud Service Azure Service Bus PowerBI.com On-premises Application Gateway Data Source

The Gateway Cloud Service sends the request to the Azure Service Bus Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Q/DS/C The Gateway Cloud Service sends the request to the Azure Service Bus Azure Service Bus PowerBI.com On-premises Application Gateway Data Source

Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus Q/DS/C PowerBI.com On-premises The Application Gateway makes a secure, outbound connection to the Azure Service Bus Application Gateway Data Source

The Application Gateway receives any pending requests Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus Q/DS/C PowerBI.com On-premises The Application Gateway receives any pending requests Application Gateway Data Source

The Application Gateway uses the Data Source to initiate a connection Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The Application Gateway uses the Data Source to initiate a connection Q/DS/C Application Gateway Data Source

Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The Application Gateway decrypts the credentials and uses them to complete the connection Q/DS/C Application Gateway Data Source

The query is sent to the data source and executed Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The query is sent to the data source and executed Q/DS/C Application Gateway Data Source

The result set is returned Data Gateway Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The result set is returned to the model Results Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises Application Gateway Data Source

Data Gateway with Live Connect Q/DS/C/UPN A Live Query queues up a request with Query/Data Source/Credentials (encrypted)/ User Principal Name Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises Application Gateway Data Source

Data Gateway with Live Connect Q/DS/C/UPN Power BI Model Gateway Queue Gateway Cloud Service The request is analyzed by the Gateway Cloud Service Azure Service Bus PowerBI.com On-premises Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Q/DS/C/UPN The Gateway Cloud Service sends the request to the Azure Service Bus Azure Service Bus PowerBI.com On-premises Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus Q/DS/C/UPN PowerBI.com On-premises The Application Gateway makes a secure, outbound connection to the Azure Service Bus Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus Q/DS/C/UPN PowerBI.com On-premises The Application Gateway receives any pending requests Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The Application Gateway uses the Data Source to initiate a connection Q/DS/C/UPN Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The Application Gateway decrypts the credentials and uses them to complete the connection Q/DS/C/UPN Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The User Principal Name is sent as the EffectiveUserName in the connection string Q/DS/C/UPN Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The query is sent to the data source and executed in the security context of the user associated with the UPN Q/DS/C/UPN Application Gateway Data Source

Data Gateway with Live Connect Power BI Model Gateway Queue Gateway Cloud Service Azure Service Bus PowerBI.com On-premises The result set is returned to the model Results Application Gateway Data Source

Data Refresh with On-Premises Data Gateway Demonstration

Power BI Administration Office 365 Admin Center Manage users Manage licenses Power BI Admin Portal Usage settings User with most dashboards Dashboard shared the most Most consumed data sources Delivery mode most used Tenant settings Disable publish to web, export data, publish content packs to entire organization, shared outside organization Usage metrics for dashboards and reports Admins can enable/disable for organization; specific groups Admin Power BI Admin role in O365 Audit logs globally available Granular Admin Controls Share content to external users Export reports as PowerPoint presentations Export Data Print dashboards and reports Publish content packs to the entire organization Create template organizational content packs Use Analyze in Excel with on-premises datasets

Power BI Mobile

Supported Devices and Power BI App iOS (iPad, iPhone, iPod Touch, or Apple Watch) Android phone or tablet Windows 10 device Supported Devices Download the Power BI App Google Play Store Apple Store Windows Store Sign into your Power BI account Power BI App Note: Power BI App supports Power BI and SQL Server Reporting Services (2016)

Power BI Mobile Demonstration

Questions

Thank you Brian Larson Lily Vergara blarson@teamscs.com lvergara@teamscs.com