Power BI Overview
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This document provides an overview of Power BI, including: - A history of Power BI and its tools over time from 2009 to present day. - An overview of the different Power BI tools for preparing, building, exploring and reporting on data. - How Power BI fits into the broader business intelligence ecosystem for preparing, modeling, visualizing and sharing data and reports. - The capabilities Power BI provides for analysts, IT professionals and business users.
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Power BI Overview
- 1. Power BI Overview Gal Vekselman January 1st, 2018
- 2. Gartner Magic Quadrant 2014 2015 2016 2017 Tableau Power BI Qlik *Gartner “Magic Quadrant for Business Intelligence and Analytics Platforms,” by Rita L. Sallam, Cindi Howson, Carlie J. Idoine, Thomas W. Oestreich, James Laurence Richardson, and Joao Tapadinhas February 16, 2017 This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Microsoft. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
- 3. First, some History Project “Gemini” 2009 2009 Power Pivot Power Pivot began to gain traction 2010 2012 Power View Data Explorer 2012 2012 Power Query 2015 Microsoft announced a new Power BI service Microsoft announced Power BI Desktop
- 4. Power BI Tools • Use Query functionality to connect to data from a variety of sources • Transform data to fit your needs using intuitive UI • Build semantic layer: Ability to automatically find related tables when connecting to database sources • Easily create measures using DAX language • Add calculated columns to tables • Define hierarchies • Explore data in a variety of ways and across multiple visualizations • Select, transform and mashup data via a freeform, drag-and-drop canvas • Visualize data and author reports • Change color, format and customize Prepare Build ExploreReport Power BI Power Query Power Pivot Power View
- 5. Prepare Power BI Ecosystem • Power BI • SQL • SSIS • Custom API • R Language Visualize Model • Power BI • SSAS • Excel Power Pivot • Power BI • SSRS • D3 • Excel • Custom Visuals Share • Power BI • Power BI Report Server • Power BI Premium • Power BI Mobile • Power BI Embedded • Connectors • Power Apps • Microsoft Flow
- 6. It’s a New BI World Out there IT to end user Analyst to end user Everyone 3rd wave End user BI 1st wave Corporate BI 2nd wave Self-service BI IT Governance – Build Enterprise Business Models, Measures and Logic Analyst and Power User querying BI models IT, analysts, managers interact with the data
- 7. For Analysts Who is being Empowered? Quickly go from data to insight to action. Connect to hundreds of sources, prep data with ease, and create beautiful reports all in minutes • Extract your data with APIs • Enrich your data with analytics tools • Out of the box machine learning For IT For Business Users Always be in the known. View dashboards on the web or on your phone, get alerts when data changes, and drill into details • Consume data anywhere any time • Take decisions in a click • Define alerts Simplify management, achieve compliance, and keep data secure while giving people access to the reports they need • Manage permissions • Monitor reports and measures usage For Developers Bring your apps to life with data. Easily embed interactive data visuals and deliver compelling reports • Build your own custom visual using D3 • Embed dashboard in applications
- 8. Beyond BI: From Hindsight to Foresight Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics What happened? Why did it happen? What will happen? How can we make it happen?
- 9. Demo
- 10. POWER BI Likes and Dislikes Rapid release cycles Microsoft office look and feel Q&A Bookmarks Quick insights Alerts Can be stored on local hardware Analyze in excel Custom connectors and visuals Usage metric report DAX DMV No Global Filters Look and feel when hovering an object No traditional Pivot Table No CRUD Real time collaboration environment In memory technology – data latency Likes Dislikes
- 21. Appendix
- 22. Pricing Author Share and collaborate Scale large deployments Power BI Desktop Power BI Pro Power BI Premium Free 9.99$ user/month Capacity Pricing node/month • Connect to hundreds of data sources • Clean and prepare data using visual tools • Analyze and build stunning reports with custom visualizations • Publish to the Power BI service • Embed in public websites • Build dashboards that deliver a 360- degree, real-time view of the business • Keep data up-to-date automatically, including on-premises sources • Collaborate on shared data • Audit and govern how data is accessed and used Starting 5,000 a month Power BI Report Server Enterprise license
- 23. Data Generation Storage Data Processing Data Distribution Better Together! Excel Workbook XLSX Power Query Power Pivot Pivot tables Charts Formulas Power BI Desktop PBIX ETL MODEL Dashboards Drill throw Custom Visuals SSRS Cube Store Proc Paginated Reports Data Driven Document D3 D3 libraries Java Script base Interactive Chart Out-of-the-box visuals Analytical reports Interactive Reports Paginated Reports Reporting Ecosystem Interactive Reports
- 24. Useful links • First Experience Using Power BI Desktop • Power BI General Availability: Features • Introduction to Power BI • Excel to Power BI webinar • Custom Power BI Visualizations
- 25. Request features and share your ideas: https://ideas.powerbi.com/ Ask questions in the forums: http://community.powerbi.com/ Read the documentation: http://docs.microsoft.com/power-bi/
Editor's Notes
- Prepare – Get and Clean the data Modeling - Create relationships between tables and measures Visualize – analyze and visualize the data Share & collaborate – share the report and keep it up to date
- Magic Quadrant (MQ) refers to a series published by IT consulting firm Gartner of market research reports that rely on proprietary qualitative data analysis methods to demonstrate market trends, such as direction, maturity and participants. Positioning Technology Players Within a Specific Market Which are the competing players in the major technology markets? How are they positioned to help you over the long haul? A Gartner Magic Quadrant is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market's competitors. By applying a graphical treatment and a uniform set of evaluation criteria, a Magic Quadrant helps you quickly ascertain how well technology providers are executing their stated visions and how well they are performing against Gartner's market view.
- 1. Project Gemini is the Analysis Services 2. It is next version of Analysis Services, which will ship before SQL11, as part of SQL Server “Kilimanjaro” 3. It uses column oriented processing and in memory storage as core technological principals
- The 1st wave of BI, what is often called "traditional BI", required IT support to serve the end users in their quest for data analysis. You probably all have that in your organization - an Analysis Services pulling data from various data sources in the data warehouse and doing some complex modeling to provide processed data which was then consumed through Excel or other analysis tools. This is an amazing technology, which launched the BI capabilities of organizations lightyears ahead and provided real data driven decision making. But the life cycle of those requests were often months, for altering the model, which made the actions that were taken from the data driven decisions less effective. Then came the 2nd wave, what is called the "self-service BI", which allowed the business analysts to analyze data on the fly and provide value to the end user. This is also familiar to all of you, since this is what all of us are doing when we analyze data in Excel, for example, or the more analysis focused tools like Tableau or Qlik. These 1st and 2nd wave solutions and tools are still super important for BI, and will remain so for many years to come. They are part of the what the 3rd wave of BI is providing, and that is "BI for everyone". It is the ability of the end user to get data, analyze it, and gain insights with almost no technical skills. It does not replace the other two waves, it is built on top of them, to provide a better BI solution to end users in the organization.
- Arima Corr plot Clustering Decision trees
- Team collaboration through support for Office 365 Groups Seamless navigation to other workloads in Office 365 Use Excel data and pin live charts to your Power BI dashboards View Excel spreadsheets through support for Excel Online
- Native apps for iPad, iPhone, Android and Windows devices Receive alerts to important changes in your data Share and collaborate with colleagues and take action Mobile Q&A
- Its not about what they can do. Its about who can do it