Next Generation Microsoft Business Analytics

Transcription

1 Next Generation Microsoft Business Analytics Self-Service Service BI Corporate BI Big Data Machine Learning Peter Myers Bitwise Solutions Pty Ltd v5 20Mar2015

2 Presenter Introduction Peter Myers Independent BI Expert, Bitwise Solutions BBus, SQL Server MCSE, MCT, SQL Server MVP (since 2007) Experienced in designing, developing and maintaining Microsoft database and application solutions, since 1997 Focuses on education and mentoring Based in Melbourne, Australia

3 Seminar Aim Provide IT decision makers, IT professionals, business analysts and data scientists with the information they need to effectively explore, analyze, visualize and discover insights from data structured or unstructured Introduce the next generation of Microsoft business analytics: Self-Service BI with Microsoft Power BI Corporate BI with Microsoft SQL Server Cloud-Based Big Data with Azure HDInsight Cloud-Based Predictive Analytics with Azure Machine Learning

4

5 Seminar Outline Introduction Introducing Microsoft Business Analytics Self-Service BI, with Power BI Corporate BI, with Microsoft SQL Server Big Data, with Azure HDInsight Machine Learning, with Azure Machine Learning Conclusion, Q&A

6 Logistics Please silence mobile phones Seminar hours Meal breaks Restrooms Feedback

7 Presentation Download This presentation can be downloaded in PDF from: NextGenerationMicrosoftBusinessAnalytics.pdf

8

9 Module Outline Introducing Microsoft Business Analytics Introducing Microsoft SQL Server Defining Roles

10 Introducing Microsoft Business Analytics Data provides organizations with the insight to: Analyze its past Optimize its present, and Make strategic decisions for the future The key question is: In a world of increasing volumes and complexities of data, and information on demand, how can we provide insight to enable action?

11 Introducing Microsoft Business Analytics Strategy and Vision To improve organizations by providing business insights to all employees, leading to better, faster, more relevant decisions Microsoft has a demonstrated long-term commitment delivering complete and integrated BI SQL Server has led innovation in the BI space for more than 15 years There is widespread delivery of BI through Office Solutions can span from on-premises to the cloud The platforms are enterprise-grade and affordable

12 Introducing Microsoft Business Analytics Microsoft Products and Services In line with Microsoft s vision, Microsoft continues to deliver products and services to enable powerful data solutions These products and services make it easier and faster to gather and prepare data, and deliver it to the people who need it Self-Service Business Intelligence, with Microsoft Power BI Corporate Business Intelligence, with Microsoft SQL Server Big Data, with Azure HDInsight Machine Learning, with Azure Machine Learning

13 Microsoft Power BI Power BI is a cloud-based business analytics service (software-as-aservice) for non-technical business users to visualize and analyze data Power BI securely connects to a broad set of data sources residing both on-premises and in the cloud

14 Azure HDInsight Microsoft s Hadoop-based service that enables Big Data solutions in the cloud, available as a Microsoft Azure service Empowers organizations with new insights on previously untouched unstructured data, while connecting to the most widely used BI tools on the planet

15 Azure Machine Learning Armed with nothing but a browser, professionals can log on to Azure and start developing prediction models from anywhere and deploy new analytic models quickly Azure Machine Learning also retains a practically unlimited number of files on Azure Storage and connects seamlessly with other Azure data-related services, including: HDInsight SQL Database, and Virtual Machines

16 Introducing Microsoft SQL Server SQL Server is the foundation of Microsoft s comprehensive data platform It delivers breakthrough performance for mission-critical applications, using in-memory technologies It enables faster insights from any data to any user in familiar tools like Excel, and a resilient platform for building, deploying, and managing solutions that span on-premises and cloud

17 Introducing Microsoft SQL Server

18 Introducing Microsoft SQL Server SQL Server 2014 SQL Server 2014 enables customers to build mission-critical applications and Big Data solutions by using highperformance, in-memory technology across different workloads: OLTP Data warehousing Business Intelligence, and Analytics

19 Introducing Microsoft SQL Server SQL Server 2014: Breakthrough Data Platform Performance Mission critical performance Faster insights from any data Platform for hybrid cloud

20

21

22 Introducing Microsoft SQL Server SQL Server 2014: Editions

23 Introducing Microsoft SQL Server SQL Server 2014: Complete and Consistent Data Platform

24 Summary Microsoft has a demonstrated long-term commitment delivering complete and integrated BI Self-Service Business Intelligence, with Microsoft Power BI Corporate Business Intelligence, with Microsoft SQL Server Big Data, with Azure HDInsight Machine Learning, with Azure Machine Learning SQL Server 2014 enables building mission-critical applications and Big Data solutions by using high-performance, in-memory technology across different workloads

25 Customer Stories Edgenet Edgenet provides optimized product data for suppliers, retailers, and search engines including Bing and Google The company powers its online selling guide with an In-memory OLTP solution delivered with SQL Server 2014 By taking advantage of Microsoft in-memory technologies, the company can provide real-time access to product data, gains seven times faster throughput, and improves both customer satisfaction and business insight CustomerStory.aspx?recid=12499

26 Defining Roles IT Professional: A skilled employee who is a member of the IT department and who creates or maintains corporate BI solutions, or supports managed BI solutions: Database administrator, developer, or BI developer Analyst: A proficient non-it employee who is empowered to create or maintain SSBI solutions: Business analyst, or power user Data Scientist: A highly educated and proficient employee who can solve complex data problems by employing deep expertise in some scientific discipline (mathematics, statistics or computer science) User: An employee who has permission and requirements to browse, and interact with, all types of BI solutions: Information worker, consumer or decision maker

27 Resources Microsoft Power BI Microsoft SQL Server Azure HDInsight web site Azure Machine Learning web site

28

29 Module Outline Defining Self-Service BI Introducing Power BI Power BI Authoring New Power BI Features and Capabilities New Power BI Pricing

30 Defining Self-Service BI The goal of Self-Service BI (SSBI) is to empower analysts so that they can design, customize and maintain their own BI solutions Without SSBI, they are otherwise forced to rely entirely upon data and resources made available by IT In reality, though, it is probably happening in an unmanaged way, whether IT allow it or not

31 Defining Self-Service BI (Continued) SSBI is not a complete solution nor a replacement for corporate BI IT Pros still need to deliver corporate BI So, SSBI is a combination of corporate BI and extensions to empower analysts to more fully exploit it It is not about analysts working in isolation Rather, it is about analysts working more closely with IT Pros to share some of the BI workload Used and managed appropriately, it usually proves itself to be invaluable to the organization

32 Defining Self-Service BI Advantages The organization becomes more agile, and benefits from the ability to gather and analyze data more quickly IT Pros can remained focused on corporate BI Analysts can: Access and work with corporate data without reliance on IT Create ad hoc solutions Create personal and team-centric solutions Base decisions on data instead of intuition Make faster and more accurate decisions

33 Defining Self-Service BI Disadvantages SSBI can be expensive and time consuming to implement and maintain Analysts will require training, specialized tools and data access Metadata dictionaries should be maintained to provide consistent and reliable access to data SSBI queries can impact on corporate system performance and availability

34 Defining Self-Service BI Disadvantages (Continued) SSBI solutions can result in duplication of effort, data and logic Commonly referred to as multiple versions of the truth or spreadmart SSBI solutions may not be known to IT, documented, reviewed, approved, backed up, or adequately secured Knowledge of, and expertise to maintain, SSBI solutions could be lost when an analyst leaves the organization

35 Defining Self-Service BI Managed BI Managed BI is about mutual benefit for IT Pros and analysts, and IT governance The goal of clear IT governance is to ensure that the investment in IT generates business value and mitigates risk

36 Defining Self-Service BI Managed BI (Continued) For SSBI, this means ensuring responsible BI by managing with oversight to: Review, approve and audit solutions Ensure trustworthy data is delivered in a compliant, responsive and secure way Ensure data, metadata and logic remain available and current, and is backed up Have visibility into how data is used throughout the organization Ensure appropriate access permissions are enforced Incorporate or upgrade SSBI solutions into corporate BI solutions, if appropriate

37 Defining Self-Service BI Summary IT Pros implement corporate BI, and solutions do not usually deliver all user information requirements IT Pros can remain focused on delivering enterprise requirements, and can deliver and support a managed BI environment A partnership between IT and analysts encourages and supports SSBI SSBI is not a replacement for, but an extension of, corporate BI A good governance process will increase the adoption of BI and mitigate risk

38 Introducing Power BI Power BI is a service that empowers anyone to: Securely connect and explore data sources Create dashboards Receive intelligent real-time insights and proactive alerts Solutions can be authored in Excel, or in the new standalone designer (in preview)

39 Introducing Power BI Power BI solutions can be authored with: Power Pivot Power Query Power View Power Map

40 Introducing Power BI (Continued) Once published to a Power BI site, additional sharing and collaboration features are available: Forecasting with Power View Natural language queries (in English only) with Power BI Q&A Query and data management with the Data Catalog Power BI mobile apps Cloud-based data refresh, including from on-premises data sources

41 Introducing Power BI Power Pivot Use Power Pivot to develop an intuitive query-able data resource that serves business user experiences Integrates data from a variety of data sources, including: Traditional data source, such as relational databases Non-traditional sources, such as data feeds, text files and spreadsheets Delivers accelerated access to extremely large data volumes

42 Introducing Power BI Power Query Use Power Query to discover, transform and consume data Allows defining queries which run a sequence of steps to import and reshape data from one or more data sources Query steps are defined by using Power Query Formula Language (also known as M ) Simple query step logic does not require writing formulas Advanced query step logic can be written to leverage the full power of the language Includes many data connectors to popular data stores

43 Introducing Power BI Power Query: Data Source Types

44 Introducing Power BI Power Query: Data Source Types: Continued

45 Introducing Power BI Power View Use Power View to produce interactive data exploration, visualization, and presentation experiences Highly visual design experience Rich meta-driven interactivity Presentation-ready at all times

46 Introducing Power BI Power View: Example

47 Introducing Power BI Power Map Use Power Map to interactively visualize spatial data in 3D Requires a tabular data model, including a Power Pivot data model Animated tours can be created and played in the Excel client or exported to MP4 video A soundtrack can be added to the video Available only in Excel

48 Power BI Authoring Power BI solutions can be authored in: Excel, or The new standalone Power BI Designer (desktop) The new standalone Power BI Dashboards (browser)

49 Power BI Authoring Excel Access Share Clean Power View Power Map Visualize Mash-up Explore

50

51 Power BI Authoring Next Generation: Power BI Designer Standalone offline designer for creating content specifically for the Power BI Service Provides an option for those who do not have access to the latest version of Excel, giving them the capability to connect to data and create models and interactive reports for the service Freely downloadable, so you can get started with SSBI at no cost Enables connecting to data and publishing data and reports to Power BI Unifies the formerly separate power tools into one enriched user experience and one Power name

52 Power BI Authoring Next Generation: Power BI Designer (Continued) Power Query Power Pivot Power View

53

54 New Power BI Features and Capabilities Power BI dashboards New out-of-the-box connectors New data visualizations Live connectivity to SQL Server Analysis Services Native mobile apps Power BI for developers

55 New Power BI Features and Capabilities Power BI Dashboards Monitor live dashboards for the data that matters most Ask questions of your data through natural language query Drill through to underlying reports to explore and discover new insight View or author HTML5 responsive dashboards in a web browser Pin new visualizations and KPIs to monitor performance Share dashboards with your team

56 New Power BI Features and Capabilities New Out-of-the-box Connectors Build new dashboard with out-of-the-box connectors for popular SaaS solutions

57 New Power BI Features and Capabilities New Data Visualizations

58

59 New Power BI Features and Capabilities Live Connectivity to SQL Server Analysis Services Live Connectivity Manage and secure data onpremises with SQL Server Analysis Services tabular Faster time to insight with a hybrid BI solution Optimized query performance for interactive exploration Role-based security is honored

60 New Power BI Features and Capabilities Native Mobile Apps Native apps for ipad, iphone, and Windows devices Receive alerts to important changes in your data Share and collaborate with colleagues and take immediate action

61 New Power BI Features and Capabilities Power BI for Developers Create and manipulate Power BI objects via the REST API: Dashboards and Reports Data source connections and Data Sets Package reusable solutions, apps, custom data sources and add-ins: Power BI Packaged Apps Power BI Dev Portal Power BI REST API

62 New Power BI Pricing Today, you can register to use the preview of Power BI for free Power BI: A freemium offering Limited to 1GB data capacity, and basic features Power BI Pro: USD 9.99 per user per month 10GB data capacity, and full feature access

63 Summary SSBI is not a replacement for, but an extension of, corporate BI When managed appropriately, SSBI usually proves invaluable to the business Power BI, with its choice of authoring tools and cloud services, enables rapid and agile business analytics Immediate Value Flexible and Extendable Built-in Best Practices Elastic Scale

64 Customer Stories Numerous customer stories are available to learn how Power BI solutions have been developed to address various industryspecific challenges

65 Customer Stories Helse Vest Helse Vest is a state-owned regional health authority that manages 10 hospitals in Western Norway It can now easily view hospital data, and has cut report time by 93 percent with a cloud BI solution By using Power BI for Office 365, it experiences many benefits: Employees can easily and quickly view medical data from multiple hospitals Analytical reports are created in less than one day (down from up to 14 days) The organization can quickly comply with national safety program requirements CustomerStory.aspx?recid=2223

66 Resources Power Pivot Power Pivot web site Book: Microsoft Excel 2013: Building Data Models with PowerPivot Publisher: Microsoft Press Authors: Alberto Ferrari and Marco Russo DAX Resource Center

67 Resources Power Pivot (Continued) Whitepaper: DAX in the BI Tabular Model Includes a sample Excel workbook Book: DAX Formulas for PowerPivot: The Excel Pro's Guide to Mastering DAX Publisher: Holy Macro! Books Author: Rob Collie

68 Resources Power Query Microsoft Download Center Microsoft Power Query for Excel TechEd North America 2013 DBI-B324: What s New in Power Query for Excel by Faisal Mohamood and Miguel Llopis Power Query for Excel Formula Language Specification

69 Resources Power Map Microsoft Download Center Power Map Preview for Excel

70 Resources (Continued) Web site: Microsoft Power BI Sign up for the free 30 day trial to preview the Power BI service MSDN Blog: Power BI Power BI Pricing (and feature matrix) Microsoft Customer Power BI Stories bi

71 Resources Resources Power BI Demo Contest Over 50 imaginative solutions produced with real data by using Power BI Finalists:

72 Get Started Today Sign up for a free Preview account Take the Power BI Tour Read through Getting Started Knowledgebase and Tutorials Watch YouTube Videos Register on the Developer Portal

73

74 Module Outline Implementing Corporate BI Introducing the SQL Server BI Services

75 Implementing Corporate BI 1: 2: 3: 4: 5: 6: 7: 8: The Data Staging Manual Clients data sources warehouse need may cleansing areas various access can may is be may periodically simplify data tools mirrored/replicated manages data be sources to required query the populated data directly the to for warehouse data cleanse analyzing to from warehouse reduce dirty data population and contention data sources reporting Data Sources Data Warehouse Data Marts Staging Area Client Access Manual Cleansing Client Access

76 Introducing the SQL Server BI Services End-to-End BI Enterprise Information Management Integration Services Master Data Services Data Quality Services Analysis Services Reporting Services

77 Enterprise Information Management Enterprise Information Management (EIM) is a best practice for creating, managing, sharing, and leveraging information in an enterprise, holistic manner that s aligned with strategic, data-driven business objectives Philip Russom, TDWI EIM more concisely is about improving the Four Cs of data: Completeness Consistency Cleanliness Currency SQL Server delivers EIM with three services

78 Enterprise Information Management Integration Services Master Data Services Data Quality Services Complete, Consistent, Clean and Current Data

79 Enterprise Information Management SQL Server Integration Services Primarily designed to implement ETL processes Provides a robust, flexible, fast, scalable and extensible architecture Its capabilities are useful in many other scenarios: Assessing data quality Cleansing and standardizing data Merging data from heterogeneous data stores Implementing ad hoc data transfers Automating administrative tasks

80 Enterprise Information Management SQL Server Master Data Services Master Data Services (MDS) is a product for master data management delivered in SQL Server V1: First released with SQL Server 2008 R2 V2: The SQL Server 2012 release included many new features and enhancements V3: The SQL Server 2014 release included no new capabilities or features Delivers credible, consistent data with user-centric data governance It addresses several problems: No authoritative source reports cannot be trusted No formal dimension maintenance capability Multiple stakeholders for the same record Inability to enforce data stewardship processes

81 Enterprise Information Management SQL Server Master Data Services: Sample Implementation Source System(s) MDS WCF Data Service Administration Data Changes Data Steward via MDM or Excel SSIS Outlook Data Warehouse

82

83 Enterprise Information Management SQL Server Data Quality Services Data Quality Services (DQS) is a knowledge-driven data cleansing product delivered in SQL Server It enables data stewards to cleanse, match, standardize, and enrich data Data cleansing can be performed in a Data Quality Project Results are output to a SQL Server table, Excel workbook or CSV file Data cleansing can be integrated with: Integration Services: DQS Cleansing transform Master Data Services: Matching in the Excel MDS Add-in

84 Analytics with Analysis Services Data Modeling (BI Semantic Model) Developed using tabular or multidimensional development approaches Delivers intuitive browsing and high performance query results Performs calculations difficult to perform using relational queries Supports advanced Business Intelligence, including KPIs Data Mining component Discovers patterns in both relational and OLAP data Can enhance the Data Modeling component with discovered results

85 Analytics with Analysis Services BI Semantic Model Power View Third-Party Applications Reporting Services Excel Power Pivot SharePoint Insights DAX MDX Relational Databases Files OData Feeds Cloud Services Hadoop Big Data Deployed BISMs

86 Analytics with Analysis Services BI Semantic Model: One Model For All End User Experiences Personal BI Power Pivot for Excel Team BI Power Pivot for SharePoint Corporate BI Analysis Services

87

88 Analytics with Analysis Services Data Mining Algorithms Classify Estimate Cluster Forecast Associate Decision Trees Logistic Regression Naïve Bayes Neural Networks Decision Trees Linear Regression Logistic Regression Neural Networks Clustering Time Series Association Rules Decision Trees

89

90 Reporting with Reporting Services Delivers enterprise, web-enabled reporting functionality Key attributes: Queries a wide variety of data sources Publishes reports in various formats Manages security on content and tasks centrally Supports pull- or push-driven report delivery Scales to support thousands of users Enables extensions to core functionality Delivers self-service reporting with Report Builder and Power View

91

92 Summary SQL Server delivers complete end-to-end corporate BI: Staging Data Mart ETL Master Data Management Data Quality Assurance Data Modeling Data Mining Managed Reporting

93 Customer Stories Yahoo! California-based Yahoo! operates one of the most popular websites in the world They implemented a solution that takes data from its vast data stores within the Apache Hadoop open-source framework and ultimately processes it in an Analysis Services cube 135 gigabytes of data per day is processed by the cube, making it the largest known SQL Server Analysis Services cube in the world CustomerStory.aspx?recid=14678

94 Resources Microsoft Business Intelligence Microsoft Business Intelligence Analysis Microsoft Business Intelligence Predictive Analytics

95 Resources (Continued) White Paper: Choosing a Tabular or Multidimensional Modeling Experience in SQL Server 2012 Analysis Services Free download from Microsoft Authors: Liz Vitt, Scott Cameron and Hilary Feier Book: Data Mining for SQL Server 2008 Authors: ZhaoHui Tang and Jamie MacLennan Publisher: Wiley Press

96

97 Module Outline Introducing Big Data Introducing Hadoop Introducing Azure HDInsight

98

99 Introducing Big Data

100 Introducing Big Data 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

101 Introducing Big Data Big Data solutions deal with complexities of: VOLUME (Size) VARIETY (Structure) VELOCITY (Speed)

102 Introducing Big Data Petabytes Terabytes Gigabytes Megabytes Data Complexity: Variety and Velocity

103 Introducing Big Data Responding to New Questions What s the social sentiment of my product? How do I better predict future outcomes? How do I optimize my services based on patterns of weather, traffic, etc.?

104 Introducing Hadoop Apache Hadoop is for Big Data It is a set of open source projects that transform commodity hardware into a service that can: Store petabytes of data reliably Execute huge distributed computations Key attributes: Open source Highly scalable Runs on commodity hardware Redundant and reliable (no data loss) Batch processing centric using a Map-Reduce processing paradigm

105 Introducing Hadoop Comparison to Traditional RDBMS TRADITIONAL RDBMS HADOOP Data Size Access Updates Structure Integrity Scaling DBA Ratio

106 Introducing Azure HDInsight HDInsight is Microsoft s Hadoop-based service that enables Big Data solutions in the cloud Available as a Microsoft Azure service HDInsight Server is available to install on-premises only for the purpose of development and testing Empowers organizations with new insights on previously untouched unstructured data, while connecting to the most widely used BI tools on the planet

107 Introducing Azure HDInsight (Continued) Key attributes: 100% Apache Hadoop solution, in the cloud Built on Hortonworks Data Platform (HDP) Map-Reduce logic can be developed with.net and Java Can be automated with PowerShell and Command Line Insights can be delivered with Excel Power add-ins

108 Introducing Hadoop How it Works

109

110 Introducing Hadoop How it Works RUNTIME Server Server Server Server

111 Introducing the Hadoop Ecosystem Legend Red = Core Hadoop Blue = Data processing Event Pipeline (Flume) Distributed Processing (MapReduce) Distributed Storage (HDFS) Data Integration ( ODBC / SQOOP/ REST) Green = Packages Purple = Microsoft integration points and value adds Orange = Data Movement

112

113 Traditional E-Commerce Data Flow

114 New E-Commerce Big Data Flow

115 The Hadoop Data Flow Data Hadoop Analytics

116

117 Summary Big Data refers to data sets so large and/or complex that they become awkward to work with in conventional ways Hadoop can store petabytes of data reliably and execute huge distributed computations Azure Blog storage provides a persistent and economical data store Azure HDInsight provides computational power Big Data queries often involve significant latency Use traditional BI techniques to cache data in advance of business user queries Big Data is just another data source! The Power add-ins can query, analyze and visualize Big Data

118 A Microsoft customer story describes how Klout produced a multidimensional BI Semantic Model (cube) based on their open-source Hive data warehouse system

119

120 Resources Azure HDInsight web site Videos: PASS Big Data Virtual Chapter Hortonworks tutorials Numerous tutorials are available to learn about Big Data by using the Hortonworks Sandbox Klout customer story

121

122 Module Outline Introducing Machine Learning Introducing Azure Machine Learning

123 Introducing Machine Learning Machine learning is a subfield of computer science and statistics that deals with the construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions. Wikipedia

124 Introducing Machine Learning (Continued) How can I add two numbers together? f() num1, num2

125 Introducing Machine Learning (Continued) How can I predict customer profit? f() Age, Marital Status, Gender, Total Children, Education, Occupation, Home Owner, Commute Distance

126 The United States Postal Service processed over 150 billion pieces of mail in 2013 far too much for efficient human sorting But as recently as 1997, only 10% of hand-addressed mail was successfully sorted automatically

127 The challenge in automation is enabling computers to interpret endless variation in handwriting

128 By providing feedback, the Postal Service was able to train computers to accurately read human handwriting Today, with the help of machine learning, over 98% of all mail is successfully processed by machines

129 Microsoft & Machine Learning Microsoft and Machine Learning 15 years of realizing innovation 15 Years of Realizing Innovation Computers work on users behalf, filtering junk SQL Server enables data mining Microsoft search engine built with machine learning Bing Maps ships with ML trafficprediction service Microsoft Kinect can watch users gestures Successful, real-time, speech-tospeech translation Microsoft launches Azure Machine Learning John Platt, Distinguished scientist at Microsoft Research Machine learning is pervasive throughout Microsoft products.

130 Microsoft & Machine Learning Microsoft and Machine Learning 15 years of realizing innovation Analytics Yesterday High Competition Strategic Change Expensive Isolated Data Yesterday s Approach Guessing Rules of thumb Trial and error New Markets Lots of Buzz Words Tool Chaos Complexity Consequences Lost opportunities Expensive operative mistakes DATA SCIENTIST

131 Microsoft & Machine Learning Microsoft and Machine Learning 15 years of realizing innovation Analytics Today

132 Azure Machine Learning How It Works Azure Portal Azure Ops Team ML Studio Data Scientists & BI Devs ML API service Developers

133 One Solution for Machine Learning Web Apps Mobile Apps Power BI/Dashboards ML API service Developer Azure Portal & ML API service Azure Ops Team ML Studio Data Scientist & BI Dev HDInsight Azure Storage Desktop Data

134 One Solution for Machine Learning Web Apps Mobile Apps Power BI/Dashboards Business users easily access results: from anywhere, on any device ML API service ML API service and the Developer Developer Tested models available as an url that can be called from any end point Azure Portal & and the Azure Ops Team ML API service Azure Portal & ML API service Create ML Studio workspace Assign storage account(s) Monitor ML consumption See alerts when model is ready Azure Ops Team Deploy models to web service ML Studio and the Data Scientist Access and prepare data Create, test and train models Collaborate One click to stage for production via the API service Data Scientist HDInsight Azure Storage Desktop Data

135 Solutions at the Speed of the Market Manage and Deploy Machine Learning from the Azure Portal Fully managed Easy to use Tested solutions Deploy in minutes No software to install, no hardware to manage, and one portal to view and update Simple drag, drop and connect interface you can access and share from anywhere Access to sample experiments, tested algorithms, support for custom R and Python, and over 350 R packages Tooled for quick deployment, hand-off and updates

136

137 Opportunities Imagine what you could use Machine Learning for Ad targeting Churn analysis Image detection & classification Equipment monitoring Recommendations Forecasting Spam filtering Fraud detection Anomaly detection

138 Summary Machine Learning is a subfield of computer science and statistics that deals with the construction and study of systems that can learn from data Azure Machine Learning key attributes: Fully managed: No hardware or software to buy Integrated: Drag, drop and connect Best in Class Algorithms: Proven solutions from Xbox and Bing R Built In: Use over 350 R packages, or bring your own R or Python code Deploy in Minutes: Operationalize with a click

139 Customer Stories Pier 1 Imports Retailer Pier 1 Imports wanted to better connect with its customers using insights and data. To do that, the company took to the cloud to pilot a predictive analytics solution based on Microsoft Azure Machine Learning and Microsoft Power BI As a result of the pilot, Pier 1 Imports may use data insights to predict which products customers will want in the future, create a dynamic website using predictive modelling and create more efficient and effective marketing campaigns CustomerStory.aspx?recid=11257

140 Customer Stories Carnegie Mellon University Carnegie Mellon University uses Microsoft Azure to reduce building maintenance and energy costs They have used Azure Machine Learning for better fault detection, diagnosis, and more efficient operations With these capabilities, CMU personnel gain advanced analytics for improved operational insights and decisions, and gains a way to cut energy use by 20 percent We see Azure ushering in an era of self-service predictive analytics for the masses. We can only imagine the possibilities CustomerStory.aspx?recid=8576 Bertrand Lasternas Carnegie Mellon

141 Announcement Microsoft have recently announced an agreement to acquire Revolution Analytics, the leading commercial provider of software and services for R R is the world s most widely used language for statistical computing and predictive analytics

142 Resources Azure Machine Learning web site Sign up for a free trial Machine Learning Blog Videos: PASS Data Science Virtual Chapter Revolution Analytics

143 Resources Learning Resources Project Botticelli Register at Online videos: What is Azure ML Introduction to Azure ML Training courses

144

145 Conclusion

146 Conclusion

147 Bitwise Solutions Training Services My company offers training in SQL Server BI and Power BI All training courses in the Microsoft BI Academy program have been specifically designed to enable students to quickly commence developing and maintaining state-of-the-art integrated Business Intelligence (BI) solutions developed by using Microsoft products SQL Server EIM (2 days) SQL Server SSAS (3 days) SQL Server SSRS (3 days) Office Power BI (2 days) Training courses can be delivered remotely, or in-person

148 Presentation Download This presentation can be downloaded in PDF from: NextGenerationMicrosoftBusinessAnalytics.pdf

149