Microsoft Advanced Analytics @ Data Science Ghent '16
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This document discusses Microsoft's Cortana Intelligence Suite and related machine learning and analytics tools. It provides an overview of the different components in the Cortana Intelligence Suite including the Azure Machine Learning workspace, HDInsight, Stream Analytics, Data Lake Analytics, Machine Learning and various data stores. It also discusses how R can be integrated with SQL Server for scalable in-database analytics and the benefits this provides. Contact information is provided at the end for getting started with Cortana Intelligence.
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Microsoft Advanced Analytics @ Data Science Ghent '16
- 1. Nathan Bijnens Jeroen Bolle Microsoft Advanced Analytics
- 3. Transform Data into Intelligent Action Everything built-in OLTP, analytical and MPP Continuous innovation Deep integration with Hadoop using T-SQL R Integration Enterprise-ready R Multi-threaded Massive Parallel Processing Reproducible R Fast path to industrialization Commercial support Scalable value-adding services Stand-alone or hybrid solutions Perceptual intelligence Business templates Industrialize in seconds Open platform (R, Spark, Python)
- 4. Cortana Intelligence Action People Automated Systems Apps Web Mobile Bots Dashboards & Visualizations Power BI Information Management Event Hubs Data Catalog Data Factory Machine Learning and Analytics HDInsight (Hadoop and Spark) Stream Analytics Intelligence Data Lake Analytics Machine Learning Big Data Stores SQL Data Warehouse Data Lake Store Data Sources Apps Sensors and devices Data Intelligence Cortana Bot Framework Cognitive Services
- 5. Data Scientist Interacts directly with data Creates models and experiments Data Analyst/DBA Manages data and analytics together Example Solutions • Fraud detection • Sales forecasting • Warehouse efficiency • Predictive maintenance 010010 100100 010101 Relational Data Extensibility ? R R Integration Analytic Library Open Source R Revolution PEMA T-SQL Interface How is it Integrated? • T-SQL calls a Stored Procedure • Script is run in SQL through extensibility model • Result sets sent through Web API to database or applications Benefits • Faster deployment of ML models • Less data movement, faster insights • Work with large datasets: mitigate R memory and scalability limitations Scalable in-database Analytics
- 7. Microsoft & Data Science Ghent will bring a Training for Data Scientists. Early Summer 2016.
- 9. nathan.bijnens@microsoft.com jeroen.bolle@microsoft.com How do I get started? microsoft.com/cortanaintelligence
- 10. © 2016 Microsoft Corporation. All rights reserved.
Editor's Notes
- MS allows you to accelerate the speed of business, by Allowing fast experimentation Deep integration of all data sources Preconfigured solutions Easy productizing of experiments Automate Secure Hyper scalable From experiment to full supported application without the hassle A comprehensive platform with deep integration for open communities and open source R, Hadoop, Spark, Python, … Leader in perceptual as well as contextual intelligence Cloud & Big Data are Microsofts big bets Cutting edge technology Continuous improvement
- Analytics that enables action - Using 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
- We have a comprehensive offering, with 3 major platforms: SQL Build on the rock solid foundations of THE oltp and analytical db Deep integration with R Bring R to your data, not the other way around Also in-memory columnar store And MPP R platform Revolutions product to productize R Fast and optimized Strong commercial support Cortana Intelligence on Azure Hyper scale Both Open Source as well as Microsoft’s own, all working nicely together. Brings the latest in Perceptual Intelligence to you
- Some services to zoom into as a Data Scientist Obviously AzureML Browser based Boring parts of ML: data massaging made quick Integrates your Python and R scripts, as well as Python based notebooks. Data Lake Store, where you use this data in Data Lake Analytics (SQL), HDInsight (or Cloudera) or ML HDInsight with Spark, Spark + R and Hadoop Perceptual and Contextual Intelligence APIs, as well as Bot Visualize using PowerBI, comes with R support
- R integration in SQL Server 2016 is based on a new extensibility model that allows secure hosting of external ‘runtimes’. R is the first to benefit from this architecture. There are two key scenarios: As a SQL Developer: I can operationalize an R script/model over SQL Server data by calling familiar T-SQL stored procedures from my application. As a data scientist I can use my R IDE to analyze datasets and build predictive models, with the compute happening on the SQL Server machine. In both cases, customers can use Revolution Analytics PEMA (Parallel External Memory Algorithms) to analyze large datasets and overcome R limitations with memory and scalability.
- Power BI is a cloud-based business analytics service that enables anyone to visualize and analyze data with greater speed, efficiency, and understanding. It connects users to a broad range of live data through easy-to-use dashboards, provides interactive reports, and delivers compelling visualizations that bring data to life. Through of the course of the preview over 90,000 companies, cross 185 countries have used Power BI. That is a decade's worth of growth in last generation business intelligence where I have to go get software, install software, get servers, get analysts involved, get all sorts of people involved before anyone got any value, that's a long road from "I want to do it" to "I've done it". With Power BI, this is an enormous user population of people that are now connected with data in a way that was either previously very difficult or for many impossible. Power BI in many ways is a connector between people and the power of the Microsoft Data Platform including data that lives in our cloud, other peoples clouds, or your on-premise systems and also processed by this wide variety of intelligence analytical capabilities that we have - statistical analysis, machine learning, building custom application - all of this technology and the value of converting data into intelligence flows through Power BI.