Advanced Analytics in Azure

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1 Explore What s Possible. Advanced Analytics in Azure Amie Mason, Practice Lead Data Science & Analytics amiem@attunix.com

2 The Attunix Difference business technology Attunix delivers results at the intersection of business and technology.

3 Attunix Solutions Attunix provides technology advising and systems integration to help you get more from your operations with core services that bring your vision to life, including: Modern Datacenter Application Modernization Advanced Analytics Internet of Things Managed Services

4 Attunix Advanced Analytics Data to insights at scale Traditional SQL Based Data Warehouse Full lifecycle SQL, SSIS, SSAS, SSRS development End to End Analytics Planning Develop strategies to extract value and insight from your data Accelerate Cloud Based Business Intelligence Power BI, Azure SQL Database, and how does it transform modern analytics Big Data Platforms Plan and execute big data platforms using Hadoop, Cortana Intelligence Suite, and other Big Data tools Machine Learning and Data Sciences Using Attunix s Data Scientists, build models that enable the competitive edge

5 DATA The world is changing CLOUD AI

6 Attunix Advanced Analytics Business Impact Manual process

7 Traditional BI vs. Advanced Analytics

8 Barcelona realizes vision of innovative city Saved 30 percent of the cost of an on-premises solution by migrating to the cloud. Centralized business intelligence Centralized access to analytics, project data, and collaboration tools by more than 12,000 employees. Empowering global operations Collected data from 40,000 sensors around the world to create a best-in-class forecast that helps customers make critical operational decisions. Building efficiency with IoT Connected chillers are back online 9x faster than unconnected equipment, avoiding more than $300,000 in hourly downtime costs Transforming the urban landscape Gathered data from sensors and systems to create valuable business intelligence and shift from reactive to proactive maintenance. IoT-enabled Smart Fridge Weka builds a life-saving smart fridge using Azure IoT Suite and Windows 10 IoT Building a connected hospital Reduce medication delivery times and inventory costs by connecting dispensary devices with electronic medical records. Filtering the signal from the noise Used analytics to discover actionable insights around fuel usage, predictive maintenance and stop unscheduled delays. Click Click

9 How Customers Are Staying Ahead Data Sources Information Management Data Factory Big Data Stores Data Lake Store Machine Learning & Analytics Machine Learning Intelligence Cognitive Services People Apps Data Catalog SQL Data Warehouse Data Lake Analytics Bot Framework Web Event Hub Cosmos DB HDInsight (Hadoop & Spark) Cortana Apps Apps Mobile Bots Sensors & Devices *Blob Storage *SQL Database Stream Analytics Azure Databricks Dashboards & Visualizations Power BI Automated Systems Data Intelligence Action

10 Power BI Overview Data sources Power BI Service Cloud-based SaaS solutions e.g. Marketo, Salesforce, Quickbooks, Google Analytics, On-premises data e.g. Analysis Services, SQL Server Organizational content packs Corporate data sources or external data services Azure services Azure SQL, Stream Analytics Excel and CSV files Workbook data, flat files Power BI Desktop files Data from files, databases, Azure, Online Services, and other sources Content packs Live dashboards Visualizations Reports Datasets Data refresh Natural language query Sharing & collaboration Power BI Desktop Prepare Explore Report Share Power BI Platform </> embed, extend, integrate

11 Artificial Intelligence? Machine Learning? Deep Learning?

12 The Old Machine Learning Landscape Expensive Expensive Siloed data Siloed data Fragmented tools Disconnected tools Deployment complexity Deployment complexity Huge set-up costs including tools, expertise, and computer/storage capacity create unnecessary barriers to entry Siloed and cumbersome data management restricts access to data Complex and fragmented tools limit participation in exploring data and building models Many models never achieve business value because they encounter difficulty when deployed into production environments The cloud changes the landscape

13 Cognitive Services From faces to feelings, allow your apps to understand images and video Hear and speak to your users by filtering noise, identifying speakers, and understanding intent Process text and learn how to recognize what users want Tap into rich knowledge amassed from the web, academia, or your own data Access billions of web pages, images, videos, and news with the power of Bing APIs Emerging Cognitive Services technologies for early adopters Custom Custom Custom Custom Custom

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20 The Microsoft AI platform: Azure+AI Services Cloud-powered AI for every developer Tools Infrastructure

21 ML Studio

22 ATTUNIX ))

23 Import Data

24 Build Experiment

25 Deploy Web Service

26 Operationalize Model with Data Factory

27 Visualize your Results with Power BI & Cortana

28 Workbench

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30 Data Wrangling and Experimentation

31 Notebooks

32 Azure Machine Learning AI-powered Data Wrangling Program Synthesis + E2E ML Dev Productivity + Deploy = Anywhere SPARK, GPU, Open Source Lifecycle Management Docker, Spark, IOT Edge, On prem, AWS/GCP E2E Tooling for AI Development

33 Databricks

34 Easily Manage Clusters

35 Autoscaling

36 Business Opportunity with Machine Learning/AI Churn analysis Social network analysis Recommendation engines Location-based tracking and services Vision analytics Supply Chain Optimization Legal discovery and document archiving Equipment monitoring Advertising analysis Pricing analysis Fraud detection Personalized Advertisements

37 Attunix Advanced Analytics Lifecycle Advanced Analytics models can only be as good as the data supporting them. Business Assessment What are our top business objectives? What business questions help drive our business objectives? What models and tools can answer our questions? Which have the greatest impact? Iterate Production Productionize model Deploy model Continuous improvement process Develop & Proof Collect & store data Clean & enhance data Develop & test models Rapid UI development Evaluate the accuracy of the model Pilot Integrate model into business process & tools Run side-by-side pilot (existing process vs. statistical model) Evaluate the effectiveness of the model

38 Potential Next Steps BI Strategic Assessment Attunix SmartBot POC Power BI, ML, Platform POCs Deeper training & workshops

39 Resources/Demo Links AI Solutions Gallery Text Analytics Power BI Demo Iris ML Workbench Demo ML Studio

40 Questions?

41 Thank You

42 Demo

43 Demand Forecasting and Price Optimization

44 Demand Forecasting and Price Optimization

45 Azure Functions

46 Azure Blob Storage

47 HDInsight Dashboard

48 Azure Data Factory Pipeline

49 Azure Data Factory Monitoring

50 Power BI Visualization