Bots and Azure Innovation with Microsoft
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Bots and Azure Innovation with Microsoft
- 4. 750 million 194 billion 188 billion 340 billion >90% of Fortune 500 use Microsoft Cloud
- 6. Transform data into intelligent action DATA Business apps Custom apps Sensors and devices INTELLIGENCE ACTION People Automated Systems Azure SQL Data Warehouse Bot Service
- 7. Transform data into intelligent action DATA Business apps Custom apps Sensors and devices INTELLIGENCE ACTION People Automated Systems Azure SQL Data Warehouse Bot Service
- 8. Transform data into intelligent action DATA Business apps Custom apps Sensors and devices INTELLIGENCE ACTION People Automated Systems Azure SQL Data Warehouse Bot Service
- 9. Platform Services Infrastructure Services Compute Storage Datacenter Infrastructure Application Platform Web Apps Mobile Apps API Apps Notification Hubs Hybrid Cloud Backup StorSimple Azure Site Recovery Import/Export Networking Data SQL Database DocumentDB Redis Cache Azure Search Storage Tables SQL Data Warehouse Azure AD Health Monitoring Virtual Network Express Route Blob Files DisksVirtual Machines AD Privileged Identity Management Traffic Manager App Gateway Operational Analytics Compute Services Cloud Services Batch RemoteApp Service Fabric Developer Services Visual Studio Application Insights VS Team Services Containers DNS VPN Gateway Load Balancer Domain Services Analytics & IoT HDInsight Machine Learning Stream Analytics Data Factory Event Hubs Data Lake Analytics Service IoT Hub Data Catalog Security & Management Azure Active Directory Multi-Factor Authentication Automation Portal Key Vault Store/ Marketplace VM Image Gallery & VM Depot Azure AD B2C Scheduler Xamarin HockeyApp Power BI Embedded SQL Server Stretch Database Mobile Engagement Functions Intelligence Cognitive Services Bot Framework Cortana Security Center Container Service Queues VM Scale Sets Data Lake Store Dev/Test Lab Integration BizTalk Services Service Bus Logic Apps API Management Media & CDN Content Delivery Network Media Services Media Analytics
- 10. © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
Editor's Notes
- We're moving from what is today's mobile-first, cloud-first world to a new world - one that is going to be made up of an intelligent cloud and an intelligent edge. One way to think about the intelligent edge is the interface between the cloud and the real world. It is the layer of the mobile devices that we use to access the data in the cloud. Currently not all of those devices are connected. You can’t always easily get the stuff off of your Surface and on to your phone. Or the stuff off of your tablet and on to your Xbox. Or the stuff off of your smart fridge and into your smart car. However, if we ensure that all of those devices are interconnected we can leverage AI everywhere and have true serverless computing power to make it easier and quicker access to that data and a more seamless experience. So by pushing boundaries with the applications and experiences they build — through innovations like agents, bots and new conversational interfaces — developers can drive the evolution of these platforms– that’s what makes this feedback loop that Satya talks about and that pushes our products and services forward. Check out this example of innovations in artificial intelligence in action …
- We’ve had incredible momentum in the last year with over 85% of Fortune 500 companies using the Microsoft Cloud.
- Finally, Microsoft is moving beyond big data and even machine learning capabilities, to be able to infuse cognitive capabilities, like computer vision and understanding natural language, into the applications we build. Also true that the core currency of any business will be the ability to convert their data into AI. We see this in our own advances in Microsoft Research and in product experiences with Bing, Cortana, LinkedIn Newsfeed, Skype Translator, Editor and PowerPoint Designer in Office, Relationship Health in Dynamics, and across HoloLens. With Azure we want to democratize AI so every company can be an AI company, and everyone can build AI solutions, while helping customers build AI capability to transform.
- 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.
- 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.
- 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.
- Why this Slide: It shows we have a very broad platform. It about BOTH IaaS and PaaS, that these work together. It shows that we continue to lead in world class IT capabilities and that there’s really nothing missing. Key Points: We have already seen how the Azure Platform is IaaS + Pass – but I want you to understand that this is a huge number of capabilities – IT building blocks if you will. Every one of these blocks you provision anytime, self-service anywhere in the world 24x7. You pay for what you use, you can get more or less anytime and you can fully automate everything… DON’T spent too much time on this slide – you are going to DEMO (aren’t you!!!)… DON’T go through each block… Transition to NEXT Slide: Make the build go backwards to show JUST IaaS and then you will go to the demo to show it.