A NEW PLATFORM FOR A NEW ERA. Russell Acton, VP &GM EMEA,
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1 A NEW PLATFORM FOR A NEW ERA Russell Acton, VP &GM EMEA, Pivotal
2 Three Examples of Data Driven Companies 2
3 Don t we do all these today? Retail CRM Customer Scoring Store Siting and Layout Fraud Detection / Prevention Supply Chain Optimization Advertising & Public Relations Demand Signaling Ad Targeting Sentiment Analysis Customer Acquisition Financial Services Algorithmic Trading Risk Analysis Fraud Detection Portfolio Analysis Media & Telecommunications Network Optimization Customer Scoring Churn Prevention Fraud Prevention Manufacturing Product Research Engineering Analytics Process & Quality Analysis Distribution Optimization Energy Smart Grid Exploration Government Market Governance Counter-Terrorism Econometrics Health Informatics Healthcare & Life Sciences Pharmaco-Genomics Bio-Informatics Pharmaceutical Research Clinical Outcomes Research 3
4 Data Driven Hard When in Silos Speed to deploy & Data Growth Over 60% Floods These Silos Finance Manufacturing Marketing IT 4
5 Data Driven: And Harder Than it Sounds Real Time Near Real Time Batch Analytical Transactional Analytical Transactional Analytical Transactional Operationalize Operationalize Operationalize Ingest Interface Ingest Interface Ingest Interface Distill Process Distill Process Distill Process Predictive Call Routing, Fraud Prediction, Dynamic Pricing, Re-Marketing, Stream Analytics Analytic Model Designs, Transaction Analysis, Trend Analysis ETL, Archive, Trending, Monthly and Weekly Jobs 5
6 So We Have a Big Data Utility Gap First Movers ~7X $290B ~20X $120B ~30X$4 B ~20X $2.9B 70% of data generated by customers 80% of data being stored 3% being prepared for analysis 0.5% being analyzed Average Enterprises <0.5% being operationalized 3 Exabytes per day now 40 Trillion total Gigabytes in 2020 (Or 162 iphones of storage for every human) Smart Enterprises 6
7 Value of Big Data insights grow 7
8 Better Data Insights Fuel Innovation The more data you have, the easier it is to solve a problem, pursue an opportunity, and build smarter software. ACCURACY DATA 8
9 An Example - New Sources of Data. 9
10 Product View understand the Car. 10
11 Product View Add New Sources. 11
12 360 Deg View. 12
13 To Understand Lifetime Customer Value 13
14 Or Change your business Totally like GE Predix is GE s software platform for the Industrial Internet. Predix enables asset and operations optimization by providing a standard way to run industrial-scale analytics and connect machines, data, and people. Deployed on machines, on-premise, or in the cloud, Predix combines an industry-leading stack of technologies for distributed computing and big data analytics, asset data management, machine-to-machine communication and mobility. Predix Platform 24 Predictivity Solutions Aviation Healthcare Manufacturing Mining Machine-Centric Easily connect machines to the Industrial Internet Embed analytics into machines, making them intelligent and selfaware Retrofit and upgrade machine software without mechanical modifications Industrial Big Data Gain actionable insights from massive amounts of high-velocity machine data Manage all your assets, from steel bolts to smart factories Orchestrate analytics processing in real-time across distributed machines and data, over deterministic networks Modern Architecture Deliver consumer-grade mobile experiences for industry-grade control and insights Big data computing fabric including Apache Hadoop, historians, and graphs Cloud-agnostic platform; runs on machines, in your data centers, or in public clouds Resilient & Secure Ensure high-availability for mission critical operations Protect sensitive data across machines, networks, and clouds Comply with industry and government regulations and for security-sensitive industries Oil & Gas Power Distribution Power Generation Rail Water Air predictivity 14
15 Even Predicting Commodity Futures via Twitter Customer A major a agri-business cooperative Business Problem Predict price of commodity futures through Twitter Challenges Solution Built Sentiment Analysis and Text Regression algorithms to predict commodity futures from Tweets Established the foundation for blending the structured data (market fundamentals) with unstructured data (tweets) Language on Twitter does not adhere to rules of grammar and has poor structure No domain specific label corpus of tweet sentiment problem is semi-supervised 15
16 Major TV Network Replaces Teradata with Pivotal Builds Infrastructure to Capture $40 Million in Untapped Revenue Pivotal solution includes: Pivotal HD, HAWQ, Pivotal Chorus, Pivotal Data Lab and Pivotal Labs Challenge: Ad Inventory is an inherently perishable product, and is subject to inefficient, traditional selling process. Upward trend in volume and traffic due to higher ad quality, mobile devices. Inability to react: 7 hour lag time in communication between ad fulfillment and sales teams, this was exacerbated by major broadcast events. Solution: Reduced 7-hour lag time to under 1 hour enabling network sales to communicate delivered impressions, forecast spend inventory and sell more effectively Maximized profit by selling across brands/channels allowing network to better leverage non-premium inventory 16
17 Business and IT beginning to merge. Analytics Applications.to thrive 17
18 The New Product Development Process..creating Data Driven Businesses 18
19 Integrates ibeacon tracking to serve timely, locationbased content and promos to users at bars and stadiums We worked with the NFL to build a mobile app for Windows, BlackBerry, ios and Android with features such as live scores, live streaming, articles, statistics, fantasy leagues, and links to ticket sales. 19
20 Users can favorite: Actors Directors Movies Theaters With that data, Cineplex sends personalized push notifications and coupons for specific films at a specific theater based on the user s location The Cineplex ios app is regularly featured on the itunes App Store, and secured a spot in the Hall of Fame and was named a Best of 2012 app. 20
21 Keys To Success: Maximize Opportunities Current Situation Unclear business cases Skills deficits Lack of experience Rigid app dev procedures Complex app deployment Data silos Escalating data management costs People Process Technology Data-Driven Enterprise Optimal use cases Trained & experienced staff Agile dev methodology PaaS Data Lake Simplified data mgmt 21
22 The Journey to Data-Driven Applications PDL Data Architecture COLLECT PDL Data Science ANALYZE Pivotal Labs Agile DEVELOP Pivotal CF Services INNOVATE Store Everything Generate Insights Operationalize Iterate Rapidly Business Data Lake Big Data Analytics Data-Driven Applications Agile Enterprise Enterprise PaaS Agile Development Predictive Analytics Big Data 22
23 To Start: Architect For A Data Lake Centralize Data Storage, Processing, And Application Services Ingest Store Analyze Surface Act Capture data from a wide range of sources, traditional and new. Store everything in one environment for cross data-set analysis. Use advanced algorithms to discover new, predictive patterns. Share insight with business domain experts. Build data-driven applications that meet business needs. 23
24 A Proven Architecture Unified Sources Real-time ingestion Micro batch ingestion Batch ingestion Centralized Management System monitoring System management Unified Data Management Tier Data mgmt. services MDM RDM Workflow Management Processing Tier In-memory MPP database HDFS Audit and policy mgmt. Flexible Actions Real-time insights Interactive insights Batch insights New Data Sources Existing Sources 24
25 If you don t have the people - Pivotal Data Labs Gain Experience Through Big Data Projects Led By Expert Data Scientists Discovery Insights Results 1-12 week engagement 25
26 EMC Big Data Vision Workshop Collaborative Process To Uncover Optimal Big Data Use Cases Research Analysis Ideation Prioritize Document 1 day workshop (2 week engagement) 26
27 Adoption Journey of a Major Healthcare Provider Prove that better technology can speed up discovery Code-a-thon Prove that better technology can improve model quality Length of Stay Modeling Prove that technology is accessible to my clinicians and researchers Comorbidity Feature Generation App Prove that data science can help in areas other than clinical analytics Fraud Detection for Accounts Payable Prove that, once trained, our scientists can get to insights as quickly as the Pivotal DS team EDIP Modeling in 4 days 27
28 Proven Infrastructure - EMC Isilon Scale compute & storage independently HDFS-enable existing data: no ingest necessary Easily import & export via next-gen communications: HDFS, NFS, SMB, HTTP, & FTP Mobile HPC Real Batch time Shares Hadoop Analytics Fault-tolerant, end-to-end data protection Archive Surface Cloud Act 28
29 EMC ViPR Software Defined Storage Reduce Data Storage Silos Through Multi-Protocol Access Analytics-enable existing storage arrays HDFS, S3, Swift & Atmos API support Storage hardware choice: Enterprise, commodity, ECS appliance 29
30 Tying It All Together: Appliances Easily Deploy Hadoop With Pre-Integrated Appliances EMC DCA Pre-integrated data computing & storage: Pivotal GPDB, Pivotal HD, EMC Isilon VCE vblock Pre-integrated server, storage, networking, virtualization, & management Supports all major Hadoop distributions 30
31 Engage With Pivotal and EMC People: Pivotal offers experienced Big Data/Data Science practitioners to train your people for successful execution Processes: Pivotal offers proven methodologies to implement business-driven, agile processes that deliver more value Technology: EMC offers the latest, best-ofbreed infrastructure solutions to simplify your data architectures and evolve into a Data Lake 31
32 A NEW PLATFORM FOR A NEW ERA
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