Big Data Analytics with PowerPivot and Power View Peter Myers Global Sponsors:
Presenter Introduction Peter Myers BI Expert BBus,MCSE, MCT, SQL Server MVP 15 years of experience designing, developing and maintaining software solutions based on Microsoft database and development platforms Based in Melbourne, Australia peter@myers.net.au
Session Objectives To introduce big data To introduce Hadoop-based Services for Windows Azure To introduce self-service Business Intelligence (BI) with: PowerPivot Power View To introduce the new self-service BI features in Excel 2013 To demonstrate how to create a self-service big data BI solution with Excel 2013 To provide relevant resources for further investigation 4
Session Outline Introducing: Big Data and Hadoop Hadoop-based Services for Windows Azure PowerPivot in Excel 2013 Power View in Excel 2013 Big Data Modeling with PowerPivot Benefits Considerations Demonstrations Resources 5
Introducing Big Data and Hadoop Big data is a collection of data sets so large and complex that it becomes awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analysis, and visualization. Wikipedia Big data solutions deal with complexities of high volume, velocity and variety of data Apache Hadoop, one big data platform, is a set of open source projects that transform commodity hardware into a service that: Stores petabytes of data reliably Allows huge distributed computations Key attributes: Redundant and reliable (no data loss) Batch processing centric Easy to program distributed applications Runs on commodity hardware 6
Introducing Hadoop-based Services for Windows Azure Supports Hadoop-based distributed processing of large data sets across cloudbased clusters of computers on the Windows Azure computing platform Key benefits: Broader access of Hadoop to end users, IT professionals, and developers, through easy installation and configuration and simplified programming with JavaScript Enterprise-ready Hadoop distribution with greater security, performance, ease of management and options for Hybrid IT usage Breakthrough insights through the use of familiar tools such as Excel, PowerPivot, SQL Server Analysis Services and Reporting Services The services are presently available as developer preview 7
Introducing PowerPivot PowerPivot empowers business users to create self-service, BI solutions in Excel A client add-in extends Excel s capabilities to support creating data models Achieved with a client-side version of SQL Server Analysis Services, known as the xvelocity in-memory analytics engine Can efficiently store data volumes far greater than what Excel worksheets can achieve A separate window is used to load, explore, relate, and enrich data with calculations Can import and relate data from corporate, local, and ad hoc data stores The add-in for Excel 2010 is available for download from Microsoft at no cost The add-in Excel 2013 will be automatically available 8
Introducing Power View Power View is an interactive data exploration, visualization, and presentation experience Highly visual design experience Rich meta-driven interactivity Presentation-ready at all times It delivers intuitive ad-hoc reporting for business users Reports can be based on tabular data models, including PowerPivot It will be available inside Excel 2013, and with new features: Pie charts Maps KPIs Hierarchies Drill down/drill up Report styles, themes and text resizing Backgrounds and background images Hyperlinks Printing 9
Big Data Modeling with PowerPivot Benefits Data models can surface big data in an intuitive way to promote rapid exploration, analysis and reporting Big data can be easily integrated with other data sources Self-service BI potential: PowerPivot can load big data results by using the Table Import Wizard ODBC direct to Hadoop On Azure OLE DB with a SQL Server linked server PowerPivot workbooks can become a data source for: Local Excel reports (within the same workbook) with PivotTables, PivotCharts and Power View Other analytic and reporting tools (once published to SharePoint Server) 10
Big Data Modeling with PowerPivot Considerations Big data results may be too large for processing or in-memory storage Workaround: Minimize the amount of data to retrieve and store Decrease the dimensionality, and/or Increase the grain Sample with a random distribution of data Once data is processed (cached), the model can deliver high query performance over big data 11
Demonstrations 1. Creating a Hadoop On Azure Cluster 2. Preparing the Big Data 3. Creating a PowerPivot Workbook Based on Big Data 4. Creating Power View Reports 12
Resources Microsoft Office Customer Preview http://www.microsoft.com/office/preview/en Sign up and evaluate today! Wikipedia: Big Data http://en.wikipedia.org/wiki/big_data Apache Hadoop -based Services for Windows Azure https://www.hadooponazure.com Hadoop Based Services for Windows Includes an excellent set of resources in the section named Using Hadoop with other BI Technologies http://social.technet.microsoft.com/wiki/contents/articles/6204.hadoop-based-servicesfor-windows-en-us.aspx Blog: Big Data for Everyone: Using Microsoft s Familiar BI Tools with Hadoop http://blogs.msdn.com/b/microsoft_business_intelligence1/archive/2012/02/24/big-datafor-everyone-using-microsoft-s-familiar-bi-tools-with-hadoop.aspx 13
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