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EXAMPLE SOLUTIONS
Support HBase as NoSQL columnar
database on Azure Blobs
Support Storm as stream processing
Hadoop in Azure
Data Node Data Node Data Node Data Node
Task Tracker Task Tracker Task Tracker Task Tracker
Name Node
Job Tracker
HMaster
Coordination
Region Server Region Server Region Server Region Server
HBase as a columnar NoSQL transactional database running on Azure Blobs
Storm as a streaming service for near real time processing
Hadoop 2.4 support for 100x query gains on Hive queries
Mahout support for machine learning + Hadoop
Graphical User Interface for HIVE queries
Publish-subscribe data
distribution
Managed PaaS (Platform
as a Service) solution
Scales with your needs to
millions of events per
second
Provides a durable buffer
between event publishers
and event consumers
Azure Event Hubs
Process real-time data in Azure using a simple SQL language
Consumes millions of real-time events from Event Hub collected from
devices, sensors, infrastructure, and applications
Performs time-sensitive analysis using SQL-like language against
multiple real-time streams and reference data
Outputs to persistent stores, dashboards or back to devices
Point of
Service Devices
Self Checkout
Stations
Kiosks
Smart
Phones
Slates/
Tablets
PCs/
Laptops
Servers
Digital
Signs
Diagnostic
EquipmentRemote Medical
Monitors
Logic
Controllers
Specialized
DevicesThin
Clients
Handhelds
Security
POS
Terminals
Automation
Devices
Vending
Machines
Kinect
ATM
Fully managed service to support orchestration of data movement
and processing
Connect to relational or non-relational data that is on-premises or in
the cloud
Single pane of glass to monitor and manage data processing
pipelines.
Publish to Power BI
Compose and orchestrate data services at scale
C#
MapReduce
Trusted data
BI & analytics
Hive
Pig
Stored Procedures
Azure Machine Learning
ML Algorithms are best of breed and embrace OSS
• MS + R + Python + BYOA
ML Studio for productive development
• Faster experiments results in faster improvements
• Visual Workflows & ML Experiments
ML Operationalization to remove deployment friction
• Build entire ML Apps & Deploy as Cloud APIs
ML Gallery
• Provide ML applications like apps in an ‘app store’
• Publish/consume APIs in a 2 sided market
Help organizations eliminate undifferentiated heavy lifting
Powerful predictive analytics in Azure
Azure Machine Learning
Enable enterprise-wide self-service data source registration and discovery
A metadata repository that allow users to register, enrich,
understand, discover, and consume data sources
Delivers differentiated value though
‒ Data source discovery; rather than data discovery
‒ Support for data from any source; Structured and
unstructured, on premises and in the cloud
‒ Publishing, discovery and consumption through any tool
‒ Annotation crowdsourcing: empowering any user to
capture and share their knowledge.
This, while allowing IT to maintain control and oversight
Excel BI Investments
Power Map with custom maps allows
deeper geospatial explorations and
storytelling
Power Query brings modern data discovery,
connectivity, shaping and publishing to
Excel
Analysis Services connectivity for Power
View allows users to leverage existing IT
investments
Support for more sophisticated data
models in Power Pivot – date and calc
tables, many-to-many relationships, etc
Power Map
w/ Custom
Maps
Power Query
Power BI dashboards and KPIs for
monitoring the health of your business
New data visualizations and touch-
optimized exploration in HTML5
Power BI mobile apps across devices
including iPad and iPhone
Support for new data sources including
SalesForce.com, Dynamics CRM online
and SQL Server Analysis Services
Dashboard
Tree Map
A hyper scale repository for big data analytic workloads
• Hadoop File System compatible with
HDFS™
• Integrated with HDInsight, Revolution
R, Hortonworks, Cloudera
• Based on YARN
• Petabyte-sized files
• No size limits to data in single account
• Massive throughput to increase
performance
• AAD based access control
• Data management
Devices
Azure
Data Lake
Analytics Service
A new distributed
analytics service
Built on Apache YARN
Scales dynamically with the turn of a dial
Pay by the query
Supports Azure AD for access control,
roles, and integration with on-prem
identity systems
Built with U-SQL to unify the benefits of
SQL with the power of C#
Processes data across Azure
29
Saas
Azure
Public
Cloud
Office 365Office 365
AzureAzure
Stream Analytics
TransformIngest
Example overall data flow and Architecture
Web logs
Present &
decide
IoT, Mobile Devices
etc.
Social Data
Event Hubs HDInsight
Azure Data
Factory
Azure SQL DB
Azure Data Lake
Azure Machine
Learning
(Fraud detection
etc.)
Power BI
Web
dashboards
Mobile devices
DW / Long-term
storage
Predictive
analytics
Event & data
producers
Azure SQL DW
The Internet of Things – Manufacturing
GLOBAL
OPERATIONS
I can see my
production line
status and
recommend
adjustments to
better manage
operational cost.
I know when to
deploy the right
resources for
predictive
maintenance to
minimize equipment
failures and reduce
service cost.
I gain insight into
usage patterns from
multiple customers
and track equipment
deterioration,
enabling me to
reengineer products
for better
performance.
MANUFACTURING PLANT
Aggregate product data,
customer sentiment, and
other third-party
syndicated data to identify
and correct quality issues.
Manage equipment remotely, using
temperature limits and other settings
to conserve energy and reduce costs.
Monitor production flow in near-real
time to eliminate waste and
unnecessary work in process inventory.
GLOBAL FACILITY INSIGHT
Implement condition-
based maintenance
alerts to eliminate
machine down-time
and increase
throughput.
THIRD-PARTY LOGISTICS
Provide cross-channel visibility into inventories
to optimize supply and reduce shared costs in
the value chain.
CUSTOMER SITE
Transmits operational information to the
partner (e.g. OEM) and to field service
engineers for remote process
automation and optimization.
Management
R&D
Field Service
From zero to finished, analytical apps and scenarios
Pre-Configured
Allows customers to accelerates the process of building analytical apps
Go from zero to sample app in minutes, from sample app to finished solution in a week
Learn More on the Main Page
Microsoft.com/cortanaanalytics
Try CA services today
Microsoft.com/cortanaanalytics
Links on “What’s Included” page
Find (or become) a trained partner
cortanaanalyticspartners.microsoft.com
Stay tuned to our blog
http://blogs.technet.com/b/machinelearning/
How do you get started?
microsoft.com/cortanaanalytics
Cortana Analytics Suite

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Cortana Analytics Suite

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  • 9. Support HBase as NoSQL columnar database on Azure Blobs Support Storm as stream processing Hadoop in Azure Data Node Data Node Data Node Data Node Task Tracker Task Tracker Task Tracker Task Tracker Name Node Job Tracker HMaster Coordination Region Server Region Server Region Server Region Server HBase as a columnar NoSQL transactional database running on Azure Blobs Storm as a streaming service for near real time processing Hadoop 2.4 support for 100x query gains on Hive queries Mahout support for machine learning + Hadoop Graphical User Interface for HIVE queries
  • 10. Publish-subscribe data distribution Managed PaaS (Platform as a Service) solution Scales with your needs to millions of events per second Provides a durable buffer between event publishers and event consumers Azure Event Hubs
  • 11. Process real-time data in Azure using a simple SQL language Consumes millions of real-time events from Event Hub collected from devices, sensors, infrastructure, and applications Performs time-sensitive analysis using SQL-like language against multiple real-time streams and reference data Outputs to persistent stores, dashboards or back to devices Point of Service Devices Self Checkout Stations Kiosks Smart Phones Slates/ Tablets PCs/ Laptops Servers Digital Signs Diagnostic EquipmentRemote Medical Monitors Logic Controllers Specialized DevicesThin Clients Handhelds Security POS Terminals Automation Devices Vending Machines Kinect ATM
  • 12. Fully managed service to support orchestration of data movement and processing Connect to relational or non-relational data that is on-premises or in the cloud Single pane of glass to monitor and manage data processing pipelines. Publish to Power BI Compose and orchestrate data services at scale C# MapReduce Trusted data BI & analytics Hive Pig Stored Procedures Azure Machine Learning
  • 13. ML Algorithms are best of breed and embrace OSS • MS + R + Python + BYOA ML Studio for productive development • Faster experiments results in faster improvements • Visual Workflows & ML Experiments ML Operationalization to remove deployment friction • Build entire ML Apps & Deploy as Cloud APIs ML Gallery • Provide ML applications like apps in an ‘app store’ • Publish/consume APIs in a 2 sided market Help organizations eliminate undifferentiated heavy lifting Powerful predictive analytics in Azure Azure Machine Learning
  • 14. Enable enterprise-wide self-service data source registration and discovery A metadata repository that allow users to register, enrich, understand, discover, and consume data sources Delivers differentiated value though ‒ Data source discovery; rather than data discovery ‒ Support for data from any source; Structured and unstructured, on premises and in the cloud ‒ Publishing, discovery and consumption through any tool ‒ Annotation crowdsourcing: empowering any user to capture and share their knowledge. This, while allowing IT to maintain control and oversight
  • 15. Excel BI Investments Power Map with custom maps allows deeper geospatial explorations and storytelling Power Query brings modern data discovery, connectivity, shaping and publishing to Excel Analysis Services connectivity for Power View allows users to leverage existing IT investments Support for more sophisticated data models in Power Pivot – date and calc tables, many-to-many relationships, etc Power Map w/ Custom Maps Power Query
  • 16. Power BI dashboards and KPIs for monitoring the health of your business New data visualizations and touch- optimized exploration in HTML5 Power BI mobile apps across devices including iPad and iPhone Support for new data sources including SalesForce.com, Dynamics CRM online and SQL Server Analysis Services Dashboard Tree Map
  • 17. A hyper scale repository for big data analytic workloads • Hadoop File System compatible with HDFS™ • Integrated with HDInsight, Revolution R, Hortonworks, Cloudera • Based on YARN • Petabyte-sized files • No size limits to data in single account • Massive throughput to increase performance • AAD based access control • Data management Devices
  • 18. Azure Data Lake Analytics Service A new distributed analytics service Built on Apache YARN Scales dynamically with the turn of a dial Pay by the query Supports Azure AD for access control, roles, and integration with on-prem identity systems Built with U-SQL to unify the benefits of SQL with the power of C# Processes data across Azure 29
  • 20. Stream Analytics TransformIngest Example overall data flow and Architecture Web logs Present & decide IoT, Mobile Devices etc. Social Data Event Hubs HDInsight Azure Data Factory Azure SQL DB Azure Data Lake Azure Machine Learning (Fraud detection etc.) Power BI Web dashboards Mobile devices DW / Long-term storage Predictive analytics Event & data producers Azure SQL DW
  • 21. The Internet of Things – Manufacturing GLOBAL OPERATIONS I can see my production line status and recommend adjustments to better manage operational cost. I know when to deploy the right resources for predictive maintenance to minimize equipment failures and reduce service cost. I gain insight into usage patterns from multiple customers and track equipment deterioration, enabling me to reengineer products for better performance. MANUFACTURING PLANT Aggregate product data, customer sentiment, and other third-party syndicated data to identify and correct quality issues. Manage equipment remotely, using temperature limits and other settings to conserve energy and reduce costs. Monitor production flow in near-real time to eliminate waste and unnecessary work in process inventory. GLOBAL FACILITY INSIGHT Implement condition- based maintenance alerts to eliminate machine down-time and increase throughput. THIRD-PARTY LOGISTICS Provide cross-channel visibility into inventories to optimize supply and reduce shared costs in the value chain. CUSTOMER SITE Transmits operational information to the partner (e.g. OEM) and to field service engineers for remote process automation and optimization. Management R&D Field Service
  • 22. From zero to finished, analytical apps and scenarios Pre-Configured Allows customers to accelerates the process of building analytical apps Go from zero to sample app in minutes, from sample app to finished solution in a week
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  • 26. Learn More on the Main Page Microsoft.com/cortanaanalytics Try CA services today Microsoft.com/cortanaanalytics Links on “What’s Included” page Find (or become) a trained partner cortanaanalyticspartners.microsoft.com Stay tuned to our blog http://blogs.technet.com/b/machinelearning/ How do you get started? microsoft.com/cortanaanalytics

Editor's Notes

  1. TODO: Business solutions vs product solutions IoT suite Security slide Like a cable service Show Cortana Halo picture
  2. Data is now the key strategic business asset. Every device, every customer, every activity – everything that’s happening in the world around us - is producing incredibly rich data that can help us create new experiences, new efficiencies, new business models and even new inventions. Leveraging this data can be the differentiator for your business. For example, IDC estimates companies that are leaders in using data assets to their advantage will capture $1.6 trillion more in business value than those that lag behind.   While data is pervasive, actionable intelligence from data is elusive. Our customers want to transform data to intelligent action and reinvent their business processes. To do this they need to more easily analyze massive amounts of data – so they can move from seeing “what happened” and understanding “why it happened” to predicting “what will happen” and ultimately, knowing “what should I do”. Only then can they create the intelligent enterprise.
  3. Data is pervasive, yet insights are elusive. According to Gartner, more than 85 percent of the data available to organizations is automatically generated – from every device, sensor, upload, tweet, purchase, shipment and keystroke. Yet many organizations experience challenges as they try to draw actionable insights from a world of big data… Reactively seeking small patterns and insights from data, and then having the ability to act on it. Shifting from the analysis of what happened in the past to predicting what might happen in the future  the key to shaping new business outcomes. And ultimately moving from manual, people-heavy decision making to automated machine-assisted decisions that accelerate business and aid competitive advantage.
  4. Cortana Analytics is a fully managed big data and advanced analytics suite that transforms your data into intelligent action.   It is a comprehensive suite that brings together technologies throughout Microsoft and provides fast and flexible deployment with a simple monthly subscription to reduce the time and cost.   With Cortana Analytics, we are taking years of research and innovation – spanning technology & infrastructure for advanced analytics, including capabilities such as machine learning, big data storage and processing in the cloud, perceptual intelligence e.g. vision, face and speech recognition and integration with Cortana, Microsoft’s personal digital assistant with the goal of helping enterprise customers make better, faster decisions to accelerate their speed of business.
  5. The Cortana Analytics Suite integrates with Cortana, Microsoft’s digital personal assistant. Cortana works with the Cortana Analytics Suite to enable your business, and or your customers business, to get things done in more helpful, proactive, and natural ways. Building on years of Microsoft’s research and innovation in perceptual intelligence including speech recognition, natural user interaction, predictive and advanced analytics, Cortana brings the capabilities of a personal digital assistant to business. Cortana Analytics helps you Interact with customers and stakeholders in new ways and infer intent with vision, face, speech, text and sentiment analysis to customize responses and drive appropriate actions. We call this Perceptual Intelligence. The Vision, Face, Text and Speech APIs enable these new types of scenarios. What we showcased with www.how-old.net is a small example of what is possible.
  6. Cortana Analytics Suite delivers an end-to-end platform with integrated and comprehensive set of tools and services to help you build intelligent applications that let you easily take advantage of Advanced Analytics. First Cortana Analytics Suite provides services to bring data in, so that you can analyze it.  It provides information management capabilities like Azure Data Factory so that you can pull data from any source (relational DB like SQL or non-relational ones like your Hadoop cluster) in an automated and scheduled way, while performing the necessary data transforms (like setting certain data colums as dates vs. currency etc).  Think ETL (Extract, Transform, Load) in the cloud. Event hub does the same for IoT type ingestion of data that streams in from lots of end points. The data brought in then can be persisted in flexible big data storage services like Data Lake and Azure SQL DW. You can then use a wide range of analytics services from Azure ML to Azure HDInsight to Azure Stream Analytics to analyze the data that are stored in the big data storage.  This means you can create analytics services and models specific to your business need (say real time demand forecasting). The resultant analytics services and models created by taking these steps can then be surfaced as interactive dashboards and visualizations via Power BI These same analytics services and models created can also be integrated into various different UI (web apps or mobile apps or rich client apps) as well as via integrations with Cortana, so end users can naturally interact with them via speech etc., and so that end users can get proactively be notified by Cortana if the analytics model finds a new anomaly (unusual growth in certain product purchases- in the case of real time demand forecasting example given above) or whatever deserves the attention of the business users.
  7. Analytics that enables action Take action ahead of your competitors by going beyond looking in the rear-view mirror to predicting what’s next. Enhance your business applications with machine intelligence to evolve from simple descriptive analytics to prescriptive recommendations. KEY BENEFITS Predict: Predict what will happen with state-of-the-art machine learning algorithms Prescribe: Augment and improve your decision making processes with proactive alerting and recommendations on actions to take Automate: Simplify and automate decision making when dealing with complex problems that involve multiple variables that may change in real time Personal Digital Assistant – Cortana Integrate with Cortana, your truly personal digital assistant.  Cortana works with the Cortana Analytics Suite to enable your business, and your customers business, to get things done in more helpful, proactive, and natural ways. KEY BENEFITS: Helpful: By intelligently learning about your business needs over time, Cortana becomes increasingly helpful when it comes to connecting data into intelligent action. Natural interaction: Interact with you data with natural language and speech, through Cortana.   Proactive: Always looking out for you and your customers, Cortana can analyze business and customer data to pro-actively suggest helpful actions, trends and insights.   Perceptual intelligence Interact with customers and stakeholders in new ways and infer intent with vision, face, speech, text and sentiment analysis to customize responses and drive appropriate actions. KEY BENEFITS See: Recognize your users and customers with face detection, identification and verification. Recognize objects within images to tailor your responses to your customers Hear: Add speech recognition and response to your applications and translate spoken words into intent to drive actions needed for the business Read: Understand and analyze text, e.g. customer feedback on your site or forum, to determine overall sentiment and key phrases Fast and flexible Why start from scratch when you don’t have to? Build with partner solutions for your industry or extend our basic building blocks to tailor the solution to your specific needs. KEY BENEFITS Get started quickly: Build on top of industry-specific partner solutions or customize machine learning models, APIs and templates from our Solutions Gallery Use all your data: Connect to and get value from data of any volume, variety and velocity both on premises and in the cloud Open and extensible: Empower your organization to work with the languages and frameworks they already know and use like R, Python and Hadoop Secure and scalable Your business needs will grow over time; so should your infrastructure. Continue to get value from your data in a secure, compliant and scalable way. KEY BENEFITS Secure: Keep your customers’ data safe on a trusted and secure cloud platform with encrypted communications, threat management, mitigation practices and regular penetration testing Compliant: Ensure infrastructure compliance with your industry through our broad set of compliance standards such as ISO 27001, HIPAA, FedRAMP, SOC 1 and SOC 2 Scalable: Elastically scale to petabytes of data as your business needs grow over time, while keeping the flexibility and choice to manage multiple data repositories in the cloud Tried and tested innovation Industry leading performance of machine learning algorithms and technology built with over a decade of investments by Microsoft Research and operated at global scale in our businesses like XBox, Skype and Bing. KEY BENEFITS Cutting edge technology: Maintain your competitive edge with a rich pipeline of technologies from Microsoft Research in areas such as machine learning, artificial intelligence, computer vision, speech recognition and computational linguistics Continuous improvement: Your investment gets better over time with continuous improvement and testing of new technologies in global scale businesses like XBox, Skype and Bing One simple subscription: Simplify your costs for building a comprehensive Big Data and advanced analytics solution that is billed with a predictable monthly cost
  8. Cortana Analytics enables core business scenarios such as real-time recommendations, customer churn forecasting, fraud detection, predictive maintenance and many more.   For e.g. we are working with Dartmouth-Hitchcock Medical Center, the largest hospital in northern New England, to develop a remote monitoring and predictive analytics solution to lower re-admittance rates called “ImagineCare.” Leveraging predictive analytics, ImagineCare will be to enable dynamic treatment plans based on the individual patient’s history and profile. ImagineCare aims to significantly enhance patient outcomes by predicting catastrophic events such as, heart attacks before they happen. It will also reduce the number of “readmissions” because each patient will be proactively monitored and Dartmouth-Hitchcock can contact the patient with tweaks/recommendations to the individual’s pathway based on the data collected. Other customers who are using Cortana Analytics capabilities include: Pier 1 https://customers.microsoft.com/Pages/CustomerStory.aspx?recid=11257 Carnegie Mellon https://customers.microsoft.com/Pages/CustomerStory.aspx?recid=8576 Wash https://customers.microsoft.com/Pages/CustomerStory.aspx?recid=11768 Stanford Linear Accelerator https://news.microsoft.com/features/from-atoms-to-quarks-to-the-cosmos-internet-of-things-helps-lab-explore-the-origins-of-the-universe/ Ziosk http://news.microsoft.com/features/tabletop-tablets-provide-a-better-experience-for-diners-and-valuable-data-for-restaurants/ Genscape https://customers.microsoft.com/Pages/CustomerStory.aspx?recid=21394
  9. As I mentioned, these products and services are available to transact today. Our data science team and field teams have seen 4 key areas in which there is the most opportunity. For example, sales and marketing is an area where there is an explosion of non-sensitive customer sentiment and transaction data which is a perfect match for the scalability of the cloud. In customer and channel, we’re also seeing a tremendous level of demand for personalized offers across retail and financial services online and in store. Cortana Analytics is the Suite that can deliver on these scenarios and more.
  10. As we’re looking at key scenarios, we’re also finding industries in which the radical change in the market is driving innovation and opportunity for our field. For example, in Retail the explosion of online shopping has put a strain on brick and mortar stores not only in staying relevant and connected, but also stocking the right thing at the right time. In Healthcare, the Affordable Care Act’s focus on paying for performance in positive patient outcomes makes a data-driven culture no longer optional. And it’s impossible to miss in the news how the marketplace and regulatory focus has changed infrastructure needs in the financial services industry. You’ll see marketing making specific investments in content in these areas in the coming months.
  11. Looking back: It’s been a big year for HDInsight, our 100% Apache Hadoop distribution in Azure.  HDInsight launched as a Globally Available service on October 2013 (Q2, FY14).  From that time there has been major updates including having HDInsight be updated to the latest Hadoop 2.2 clusters and now on Hadoop 2.4 clusters. Microsoft has made major contributions to the Apache open source community through the Stinger project that have improved Hive queries up to 100x faster.  This was made possible by taking some of Microsoft’s know-how in SQL Server and translating that into the open source community.  Finally, Microsoft continues to add Hadoop sub-projects to HDInsight including Hbase, a columnar NoSQL database as a preview feature and Mahout for a library of Machine Learning. Looking forward: For FY15, HDInsight will continue its relatively fast release cadence.  In Q1, FY15, you’ll see HDInsight release HBase, a columnar NoSQL database as a GA feature.  You’ll also see HDInsight arrive in many Azure data centers like Japan, China and Brazil which will give you the ability to sell HDInsight in these regions.  In Q2, FY15, you’ll hear about Hortonworks releasing the next version of Hortonworks Data Platform (HDP 2.2) which will have built-in connectors to move data from on-premise to Azure as well as HDInsight being refreshed on this newest version.  You’ll also hear about the release of Storm as a streaming service for near real time processing on data in HDInsight.
  12. Areas of investment for BI in Excel: Filtering for Power Map: Available Sept 2014: With filtering in Power Map, use familiar Excel filter controls to uncover more insights from your 3D geospacial visualizations. When using filters, you can adjust the amount of data shown, toggle between different categories or simply search and select specific values for more targeted analyses. Custom Maps for Power Map: Available Sept 2014: Custom Maps extends all the features of Power Map so you can tell rich and interactive stories using any map type. Simply choose an image – like building floor maps, the human body, public transit routes, and system architectures - and Excel will guide you through transforming your data into visualizations that can be explored and shared. OLAP Connectivity within Power View: Connect Power View in Excel to an external Analysis Services model without the need to import the data into Excel. Richer Data Models with Power Pivot: We are enhancing Power Pivot to enable you to create and analyze richer data models, like calculated tables and many-to-many relationships. The relationship between your business data can be complex and Power Pivot, with more powerful data modeling capabilities, allows you to analyze that data effectively to uncover deeper insights that will boost your competitive edge. Deeper Integration of BI in Excel: Power BI for Office 365 adds value to your businesses because it makes BI accessible to your entire team through the familiarity of Excel. The Power BI features in Excel will be integrated more deeply to make it even easier for any business user to discover and start benefiting from the collective intelligence of your business community.
  13. Areas of investment for Power BI Power BI dashboards and KPIs – Power BI will provide new capabilities to allow for the creation of live dashboards and easy to create KPIs that can be pinned to the dashboard - from which you can drill into underlying Power View reports for additional detail and data exploration. New data visualizations – we will introduce a host of new data visualizations for Power BI. eg. Tree Map. Touch optimized data exploration in Power View HTML5 – Power View will gain new touch optimized data exploration features allowing users to explore data more easily on touch devices. Power BI mobile applications – beyond the mobile experiences provide through HTML5 we also continue to invest in providing native mobile apps and will soon support both iPad and iPhone. Support for new data sources such as SalesForce.com and Dynamics CRM – new data sources will be added such as SalesFoce.com and tighter integration with CRM online. Support for SQL Server Analysis Services – Power Query will support SQL Server Analysis Services as a data source. Power BI will also support interactive query directly to SQL Server Analysis services on-premises. This will be to both tabular and multidimensional cubes. This will allow organizations to managing and maintain their existing Analysis Services models without having to move their data to the cloud. Users will be able to view and explore their data from Power View in Power BI and the system will directly connect and query against SQL Server Analysis Service on-premises.
  14. In a moment Sanjay will show you how Pier 1 is truly putting their data to work. They’re experimenting with monitoring in-store activity with the power of Kinect sensors and combining that with data from customer activity on the web. They’re ingesting that through Event hubs and then putting the data that needs further processing into Azure Data Factory to use HDInsight for batch processing. Stream Analytics takes on data as well. Data Factory then moves that data into Blob storage, where it’s further processed and combined with the Analytics data already sent to Azure SQL Database. Then that Azure DB data is sent to Azure ML, where it can then be modeled, made sense out of, to then deliver predictive results to any number of devices and visualization tools. Does this sound like a lot and a lot of things to buy? Perhaps it does. But what you have bought here – all you need to do all this is Azure. That’s the beauty of the cloud.