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Leveraging Data Analytics in the Cloud to Support Data-Driven Decisions

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Learn about AWS business intelligence (BI), analytics, visualisation, AI, and machine learning services that can transform data into insights.

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Leveraging Data Analytics in the Cloud to Support Data-Driven Decisions

  1. 1. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Neil Mackin, Technical Business Development Manager Data and Analytics, AI/ML Wednesday 18th September Data Lifecycle – Leveraging Data Analytics in the Cloud to Data Driven Decisions
  2. 2. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Driving Insights: Deliver decision-makers the insights to transform an organization by identifying unmet needs within the organization or by optimizing operational processes Questions to ask: What business question is being answered? Does the data support answering them? Who are the users driving the insights? What skills do those users have?
  3. 3. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Business needs come in various forms: • Present actionable information and reporting to executives and managers • Combined heterogeneous datasets together to be able to answer additional questions • Query and Investigate your datasets • Understand what’s happening in the business now • Exploit AI/ML to predict what happens next
  4. 4. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Analytics solutions Data Warehousing Big Data Processing Interactive Query Operational Analytics Real time Analytics Analytics
  5. 5. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Data Warehousing Data Warehousing Big Data Processing Interactive Query Operational Analytics Real time Analytics Present actionable information and reporting to executives and managers Analytics
  6. 6. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Redshift – data warehousing Fast, powerful, simple, and fully managed data warehouse at 1/10th the cost Massively parallel, scale from gigabytes to petabytes Fast at scale Columnar storage technology to improve I/O efficiency and scale query performance $ Inexpensive As low as $1,000 per terabyte per year, 1/10 the cost of traditional data warehouse solutions; start at $0.25 per hour Open file formats Secure Audit everything; encrypt data end-to-end; extensive certification and compliance Analyze optimized data formats on the latest SSD, and all open data formats in Amazon S3 Analytics
  7. 7. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Redshift Data Warehouse Relational data Gigabytes to petabytes scale Reporting and analysis Schema defined prior to data load AWS Glue ETL On Prem Amazon QuickSight Existing or new BI tool Redshift COPY Analytics
  8. 8. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Complementary to EDW (not replacement) Data lake can be source for EDW Schema on read (no predefined schemas) Schema on write (predefined schemas) Structured/semi-structured/Unstructured data Structured data only Fast ingestion of new data/content Time consuming to introduce new content Data Science + Prediction/Advanced Analytics + BI use cases BI use cases Data at low level of detail/granularity Data at summary/aggregated level of detail Loosely defined SLAs Tight SLAs (production schedules) Flexibility in tools (open source/tools for advanced analytics) Limited flexibility in tools (SQL only) Elastic storage and compute capacity – decoupled Explicitly sized environments, compute and storage scaled in linearly A Data Lake is not an Enterprise Data Warehouse Data Lake EDW Analytics
  9. 9. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Redshift Spectrum E x t e n d t h e d a t a w a r e h o u s e t o e x a b y t e s o f d a t a i n A m a z o n S 3 d a t a l a k e Amazon S3 Data Lake Amazon Redshift data Amazon Redshift Spectrum query engine Exabyte Redshift SQL queries against Amazon S3 Join data across Amazon Redshift and Amazon S3 Scale compute and storage separately Stable query performance and unlimited concurrency CSV, ORC, Grok, Avro, & Parquet data formats Pay only for the amount of data scanned Analytics
  10. 10. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Data Lakes extend the traditional data warehouse Data warehouse Business intelligence OLTP ERP CRM LOB • Relational and nonrelational data • TBs–EBs scale • Diverse analytical engines • Low-cost storage & analytics Devices Web Sensors Social Data lake Big data processing, real-time, machine learning Analytics
  11. 11. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Visual insights for everyone with Amazon QuickSight Pay only for what you use Scale to tens of thousands of users Embedded analytics Build end-to-end BI solutions Visualization
  12. 12. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Create beautiful, interactive dashboards. • Add rich interactivity like filters, drill downs, zooming, and more • Blazing fast navigation • Accessible on any device • Data Refresh • Publish to everyone with a click
  13. 13. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Insights Delivered to Your Inbox QuickSight lets you send report snapshots directly to your users inbox. • Schedule email reports on a daily, weekly, or monthly basis • Sent to individual users or groups • Users can opt out of any report so they can focus on what’s important. • Uses Pay-per-Session Pricing
  14. 14. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Introducing ML Insights Cutting edge ML tools that automatically discover powerful insights for your users. • ML powered Anomaly Detection • ML Powered Forecasting • Auto-generated natural language narratives and summaries.
  15. 15. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Big Data Processing Data Warehousing Big Data Processing Interactive Query Operational Analytics Real time Analytics Combined heterogeneous datasets together to be able to answer additional questions Analytics
  16. 16. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon EMR – big data processing Analytics and ML at scale Run other popular distributed frameworks such as Apache Spark, HBase, Presto, and Flink, and many others Enterprise-grade security $ Latest versions Updated with the latest open source frameworks within 30 days of release Low cost Flexible billing with per- second billing, Amazon EC2 Spot, Reserved Instances, and Auto Scaling to reduce costs 50%-80% Amazon S3 storage Process data directly in the Amazon S3 data lake securely with high performance using the EMRFS connector Easy Launch fully managed Hadoop & Spark in minutes; no cluster setup, node provisioning, cluster tuning Data Lake 100110000100101011100 1010101110010101000 00111100101100101 010001100001 Analytics
  17. 17. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Interactive Query Data Warehousing Big Data Processing Interactive Query Operational Analytics Real time Analytics Query and Investigate your datasets Analytics
  18. 18. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Athena – interactive analysis Interactive query service to analyze data in Amazon S3 using standard SQL No infrastructure to set up or manage and no data to load $ SQL Query instantly Zero setup cost; just point to Amazon S3 and start querying Pay per query Pay only for queries run; save 30%–90% on per- query costs through compression Open ANSI SQL interface, JDBC/ODBC drivers, multiple formats, compression types, and complex joins and data types Easy Serverless: zero infrastructure, zero administration Integrated with Amazon QuickSight Analytics
  19. 19. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Operational Analytics Data Warehousing Big Data Processing Interactive Query Operational Analytics Real time Analytics Present actionable information and reporting to executives and managers Analytics
  20. 20. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Operational analytics for logs and search with Amazon Elasticsearch Service Fully managed; deploy production-ready cluster in minutes Direct access to Elasticsearch open-source APIs, Logstash, and Kibana Amazon VPC support; at-rest and in-transit encryption Easily scale up and down Analytics
  21. 21. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Machine Learning solutions AI Services ML Services ML Frameworks and Infrastructure
  22. 22. 22© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 40% of digital transformation initiatives supported by AI in 2019 —IDC 2018 InnovationDecision making Customer experience C E N T E R P I E C E F O R D I G I T A L T R A N S F O R M A T I O N Business operations Competitive advantage
  23. 23. 23© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Our mission at AWS Put machine learning in the hands of every developer
  24. 24. 24© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | W H Y A W S F O R M L ? 200 new features and services launched this last year alone Unmatched flexibility Broadest and deepest set of AI and ML services 70% cost reduction in data-labeling 10x faster performance 75% lower inference cost Accelerate your adoption of ML with SageMaker Built on the most comprehensive cloud platform optimized for ML AWS holds the top spots on Stanford’s benchmark, for fastest training time, lowest cost, lowest inference latency
  25. 25. 25© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | FRAMEWORKS INTERFACES INFRASTRUCTURE AI Services Broadest and deepest set of capabilities T H E A W S M L S T A C K VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS ML Services ML Frameworks + Infrastructure P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E X F O R E C A S TR E K O G N I T I O N I M A G E R E K O G N I T I O N V I D E O T E X T R A C T P E R S O N A L I Z E Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker F P G A SE C 2 P 3 & P 3 D N E C 2 G 4 E C 2 C 5 I N F E R E N T I AG R E E N G R A S S E L A S T I C I N F E R E N C E
  26. 26. 26© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | FRAMEWORKS INTERFACES INFRASTRUCTURE AI Services Broadest and deepest set of capabilities T H E A W S M L S T A C K VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS ML Services ML Frameworks + Infrastructure P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E X F O R E C A S TR E K O G N I T I O N I M A G E R E K O G N I T I O N V I D E O T E X T R A C T P E R S O N A L I Z E Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker F P G A SE C 2 P 3 & P 3 D N E C 2 G 4 E C 2 C 5 I N F E R E N T I AG R E E N G R A S S E L A S T I C I N F E R E N C E
  27. 27. 27© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers A M A Z O N S A G E M A K E R Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment
  28. 28. 28© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers A M A Z O N S A G E M A K E R Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems
  29. 29. 29© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers A M A Z O N S A G E M A K E R Collect and prepare training data Choose and optimize your ML algorithm Pre-built notebooks for common problems Built-in, high performance algorithms • K-Means Clustering • Principal Component Analysis • Neural Topic Modelling • Factorization Machines • Linear Learner (Regression) • BlazingText • Reinforcement learning • XGBoost • Topic Modeling (LDA) • Image Classification • Seq2Seq • Linear Learner (Classification) • DeepAR Forecasting
  30. 30. 30© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers A M A Z O N S A G E M A K E R Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training
  31. 31. 31© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers A M A Z O N S A G E M A K E R Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization
  32. 32. 32© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers A M A Z O N S A G E M A K E R Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization One-click deployment
  33. 33. 33© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Collect and prepare training data Choose and optimize your ML algorithm Set up and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization One-click deployment Fully managed with auto-scaling, health checks, automatic handling of node failures, and security checks Bringing machine learning to all developers A M A Z O N S A G E M A K E R
  34. 34. 34© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 34© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Fueling product innovation Using Amazon SageMaker, Intuit developed ML models that can pull a year’s worth of bank transactions to find deductible business expenses for customers. Using SageMaker, Intuit reduced machine learning deployment time by 90%, from 6 months to 1 week.
  35. 35. 35© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 35© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Driving better healthcare outcomes Using Amazon SageMaker, GE Healthcare developed an ML model that can learn from thousands of medical scans to detect anomalies more accurately and efficiently, allowing radiologists to prioritize patients needing immediate attention.
  36. 36. 36© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 36© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Increasing customer engagement Using Amazon SageMaker, Tinder analyzes millions of match requests a minute, billions of swipes a day, across more than 190 countries to make the perfect match. With Amazon Rekognition, Tinder creates tags to highlight photos, resulting in 20% increase in engagement.
  37. 37. 37© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | FRAMEWORKS INTERFACES INFRASTRUCTURE AI Services Broadest and deepest set of capabilities T H E A W S M L S T A C K VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS ML Services ML Frameworks + Infrastructure P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E X F O R E C A S TR E K O G N I T I O N I M A G E R E K O G N I T I O N V I D E O T E X T R A C T P E R S O N A L I Z E Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker F P G A SE C 2 P 3 & P 3 D N E C 2 G 4 E C 2 C 5 I N F E R E N T I AG R E E N G R A S S E L A S T I C I N F E R E N C E
  38. 38. 38© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Use AI services to strengthen safety and security P U T M L T O W O R K F O R Y O U R B U S I N E S S accurate facial analysis | identity protection | metadata extraction REKOGNITION IMAGE COMPREHEND & COMPREHEND MEDICAL REKOGNITION VIDEO
  39. 39. 39© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 39© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Real-time identity verification Aella Credit uses Amazon Rekognition to analyze images to verify an individual’s identity in real-time without human intervention, allowing it to provide instant loans to eligible customers through its mobile app.
  40. 40. 40© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Automate media workflows to reduce costs and monetize content P U T M L T O W O R K F O R Y O U R B U S I N E S S content moderation | contextual ad insertion | searchable media library custom facial recognition | multi-language metadata search REKOGNITION IMAGE REKOGNITION VIDEO COMPREHEND TRANSCRIBE TRANSLATE TEXTRACT
  41. 41. 41© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 41© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Scaling video indexing C-SPAN uses Amazon Rekognition to automatically index video news footage for search. With Rekognition, C-SPAN reduced indexing time per video from 1 hour to 20 minutes and uploaded 97,000 images in under 2 hours.
  42. 42. 42© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | FRAMEWORKS INTERFACES INFRASTRUCTURE AI Services Broadest and deepest set of capabilities T H E A W S M L S T A C K VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS ML Services ML Frameworks + Infrastructure P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E X F O R E C A S TR E K O G N I T I O N I M A G E R E K O G N I T I O N V I D E O T E X T R A C T P E R S O N A L I Z E Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker F P G A SE C 2 P 3 & P 3 D N E C 2 G 4 E C 2 C 5 I N F E R E N T I AG R E E N G R A S S E L A S T I C I N F E R E N C E
  43. 43. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Analytics solutions Data Warehousing Big Data Processing Interactive Query Operational Analytics Real time Analytics Machine Learning solutions AI Services ML Services ML Frameworks and Infrastructure
  44. 44. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Getting Started: • Start Small, build upon successes • Use MVP principles incrementally building • Build Loosely/De-coupled solutions • Pick the right tool for the right job • Based on business question • Users • Data • Leverage Managed/Serverless solutions
  45. 45. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Questions?

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