HP SummerSchool TechTalks Kenneth Donau Presale Technical Consulting, HP SW

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HP SummerSchool TechTalks 2013 Kenneth Donau Presale

2013 Hewlett-Packard Development Development

1 HP SummerSchool TechTalks 2013 Kenneth Donau Presale Technical Consulting, HP SW Copyright Copyright Hewlett-Packard Development Development Company, Company, L.P. The L.P. information The information contained contained herein herein is subject is subject to change to change without without notice. notice.

2 HP Strategy : Solution focus Cloud Security Information 86% of corporations cannot deliver the right information, at right time to support enterprise outcomes all of the time (Coleman Parkes Survey Nov 2012) 2 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Fundamental shift For the first time in the IT industry, there is a fundamental shift from the T to the I : information management is the new source of competitive advantage.

3 Fundamental shift For the first time in the IT industry, there is a fundamental shift from the T to the I : information management is the new source of competitive advantage. 3 Copyright Hewlett-Packard Autonomy Inc., an Development HP Company. Company, All rights reserved. L.P. The information Other trademarks contained are herein registered subject trademarks to change and without the properties notice. of their respective owners.

Market dynamics of BI and Analytics Data explosion Human and machine information growth can t be contained Data growth over past 5-10 years surpasses all data from last 5 decades Evolving delivery

4 Market dynamics of BI and Analytics Data explosion Human and machine information growth can t be contained Data growth over past 5-10 years surpasses all data from last 5 decades Evolving delivery models Every phone call, tweet, Facebook update, and generates new information Consumerization of IT blurs line between employees and consumers Real time decision making Organizations can t react and respond quickly enough Only 20% of CIOs have real-time access to customer data 4 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Fundamental change Information optimization: Big Data Velocity For the

van the Opstal I : Human Sales information Manager Benelux Autonomy,

Real clickstreams, time nature sensor of new data, information images,

see 36 hours of video uploaded per minute Copyright 2013

5 Fundamental change Information optimization: Big Data Velocity For the first time in the IT industry, there is a fundamental Ewout shift in van the Opstal I : Human Sales information Manager Benelux Autonomy, Information an in HP the Company form of social media, rich media, Real clickstreams, time nature sensor of new data, information images, and more. YouTube, Blinkx, ebay, Amazon, etc. see 36 hours of video uploaded per minute Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

6 Big Data Not Just Big VOLUME Social media Telephone call records Gene sequencing Sensors Customer purchasing history Algorithmic trading Click streams Game interactions VELOCITY BIG DATA COMPLEXITY VARIETY 6 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

complexity Social Media Video Email HRMS

Procurement Texts Messages ERP CRM Images

Clickstream Data 85% 15% HP handles 100% of

7 The challenges of unmanaged information Missed opportunity Increased risk Cost & complexity Social Media Video HRMS Supply Chain Management/ Inventory Mgmt Procurement Texts Messages ERP CRM Images Word, Excel Audio Transactional Data Logs Clickstream Data 85% 15% HP handles 100% of this information 7 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Why is processing human information different?

Social Media Video Audio Email Texts Mobile

9 Why is processing human information different? Human Information is made up of ideas, is diverse, and has context. Ideas don t exactly match like data does; they have distance. Human Information is not static it s dynamic and lives everywhere. Legacy techniques have all fallen short. Social Media Video Audio Texts Mobile Transactional Data Documents Search Engine Images IT/OT 9 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

10 The New Look of the Data Lifecycle Executive Dashboards Enterprise Search Customer Interaction Predictive Analytics Web Engagement BI and Big Data Ecosystems Information Infrastructure Information Management Information Insight Social Media Video Audio MGD Texts Transactional Data Word, Excel Logs Clickstream Data Images Transactional Operational Strategic CRM (Sales) Web ERP (Procurement) Supply Chain (Ops) HR Smart Meters 10 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

11 IDOL: the OS for human information Big Data & Analytics Search & Collaboration Information Governance Customer Experience Mgmt Marketing Optimization Autonomy Social Media Video Audio Texts Mobile Transactional Documents Data Over 400 Connectors IT/OT Search Engine Images Unstructured repositories Databases Mail servers CRM/ERP/BI LDAP 11 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

12 The Changing Nature of BI systems The lines between traditional OLTP, OLAP and Analytics workloads have blurred Transactional Data Sales ETL and Information Management Analytics and Reports/Dashboards Finance Marketing Data warehouse Analytics cubes Reporting, analysis & visualization tools Operations CRM HR Sales Targets, Finance Targets, etc. Data extract, cleanse, integrate Homogenized grain, time relationships, dimensionality Business calculations, Summarization, hierarchies 12 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

13 HP is leading in Big Data innovations Fastest Time to Value; Purpose Built for Big Data Scale and Performance HP solutions deliver more choice to meet specific workloads, data volumes and variety versus our competitors one-size-fits-all approach AppSystem for Apache Hadoop AppSystem for SAP HANA AppSystem for Vertica AppSystem for Autonomy AppSystem for Microsoft PDW 13 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

14 HP SummerSchool TechTalks 2013 René Witteveen Presales consultant HP App Systems Copyright Copyright Hewlett-Packard Development Development Company, Company, L.P. The L.P. information The information contained contained herein herein is subject is subject to change to change without without notice. notice.

workloads, data volumes and variety versus our competitors one-size-fits-all

AppSystem for Autonomy AppSystem for Microsoft PDW 15 Copyright 2012

15 HP is leading in Big Data innovations Fastest Time to Value; Purpose Built for Big Data Scale and Performance HP solutions deliver more choice to meet specific workloads, data volumes and variety versus our competitors one-size-fits-all approach AppSystem for Apache Hadoop AppSystem for SAP HANA AppSystem for Vertica AppSystem for Autonomy AppSystem for Microsoft PDW 15 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

16 Relative Positioning of HP Solutions For Transactional (OLTP) Data For structured data, OLAP and analytics For semi-structured or unstructured data Apache Hadoop n/a AppSystem for Apache Hadoop Reference Architectures for Cloudera, MapR and Hortonworks AppSystem for Apache Hadoop Reference Architectures for Cloudera, MapR and Hortonworks Autonomy n/a n/a Autonomy IDOL Autonomy ediscovery Appliance Microsoft Universal Db Sol for Mission Critical x86 SQL Server 2012 (Windows Only) Database Consolidation Reference Architecture Oracle Oracle 11g on DL980 with Fusion IO for up to 5TB or DL980/Violin for larger HP AppSystem for SQL 2012 Parallel Data Warehouse SQL Server 2012 Fast Track Data Warehouse Reference Architecture Universal Database Solution for Oracle Data Accelerator Solution for Oracle HP AppSystem for SQL 2012 Parallel Data Warehouse (Polybase & HDInsight for unstructured data) n/a SAP Sybase ASE 15.5 SAP Business Suite on HANA for ERP customers SAP HANA for NetWeaver BW or SAP ERP customers Sybase IQ EDMT SAP HANA Vertica n/a Vertica Analytics Platform Vertica Analytics Platform 16 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

17 Detailed Relative Positioning for OLAP/Analytic Workloads Customer Needs Workload Requires Other Considerations Apache Hadoop Microsoft PDW SAP HANA A Data Lake with multiple data types A pilot departmental analytics project that could scale to an enterprise-wide initiative in the long term Unified, simplified management with low admin costs Close Integration with Excel, Power View, Power Pivot and other Microsoft OLAP/BI tools A single database for transactional and business warehouse deployments Close integration with VMware vsphere Vertica Extreme low latency query performance To build user defined analytics procedures and functions Low cost data warehousing option without Schema less data capture Up to 6 PB of data capacity Querying Hadoop data without pre-loading data into warehouse first and then view results in single spreadsheet Data not be moved but kept in one place for all analytics Superior query and load performance Near real time statistical or graph analysis (e.g. Monte Carlo) Customer doesn t want to infect warehouse with potentially hazardous unstructured data Use of standard SQL queries, instead of MapReduce, to access and join Hadoop data with relational data at node level (Polybase) Low TCA, TCO and server footprint Pricing based on an incremental of 64GB RAM and total amount of data held in memory Close integration of R, without ETL Close integration with MicroStrategy for mobile analytics 17 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Appsystems are like the Bankras Model 18 Copyright 2012 Hewlett-Packard Development

Fast time to market Starts with configuring and ordering 19 Copyright 2012 Hewlett-Packard

Similar setup for most appliances Network switches Storage switches Management Nodes Scheduler, Jobtracker nodes Compute nodes Storage nodes Operating System Additional Software Support Factory

20 Similar setup for most appliances Network switches Storage switches Management Nodes Scheduler, Jobtracker nodes Compute nodes Storage nodes Operating System Additional Software Support Factory Express Installation Challenge: find the right balance between CPU, RAM, IOPS, amount of DATA for the specific workload AND TCO! 20 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

21 Microsoft PDW Active scale unit Modular, Flexible, and cost effective Active scale unit Active scale unit 8 10* compute node functionality Active scale unit Base scale unit Base scale unit 21 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. * 10-node plan to be supported in next software release

22 Example HADOOP solution Hortonworks on SL4540 servers The SL4540 Gen8 Server is a server purpose built for big data. 22 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Hortonworks on SL4540 servers 23 Copyright 2012 Hewlett-Packard Development

24 SAP HANA line up From X-Small (128GB RAM) up to 8TB Scalable Single node 24 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Scale-out

App System for Vertica 25 Copyright 2012 Hewlett-Packard Development

HP Uniquely Addresses Top Customer Pain Points Lowest Cost and Most Customer Choice at Multiple Levels Open standards Choice of deployment Integration 27 Copyright 2012 Hewlett-Packard 27 Copyright

27 HP Uniquely Addresses Top Customer Pain Points Lowest Cost and Most Customer Choice at Multiple Levels Open standards Choice of deployment Integration 27 Copyright 2012 Hewlett-Packard 27 Copyright Development 2012 Company, Hewlett-Packard L.P. The Development information contained Company, herein L.P. The is subject information to change contained without herein notice. is subject to change without Powered notice. by Intel

28 HP SummerSchool TechTalks 2013 Big Data Discovery Experience Andre van der Griend Information Systems Architect Copyright Copyright Hewlett-Packard Development Development Company, Company, L.P. The L.P. information The information contained contained herein herein is subject is subject to change to change without without notice. notice.

29 Big Data Discovery Experience Accelerating the discovery and implementation of business insights and innovations into business process Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

30 Take time to test the potential of Big Data how to make it work for you. - HP Big Data Discovery Experience - HP Big Data Implementation Service HP Enterprise Services Information Management & Analytics 30 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

31 The HP Big Data Discovery journey HP Discovery Workshop: 1 to 2 days Introduction of teams, review of the client s state of affairs, and infusion of the discovery cloud initiative concepts and initial use case planning HP Discovery Diagnostics: 2 weeks Establishment of the core parameters people, data, strategy, readiness, and time HP Discovery Experience: 12 weeks A facilitated and assisted with expert resources engagement to discover key insights based on client data, deliver a functional proof of concept (POC), a roadmap and business justification of innovation HP Discovery Services and Solutions Services to define, plan and enable the deployment of Discovery Experience insights-based applications in production processes 31 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

32 HP Big Data Discovery Experience An innovative solution enabling the discovery of valuable business insights using all available data and agile decision-making for improved business outcomes The Discovery Experience is a methodology and service that enables customers Services to rapidly discover the business value of their data The Discovery Environment is a platform that enables the discovery of valuable insights from all available customer data 32 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

33 HP Big Data Discovery Experience Method Client structured and unstructured data samples Web content Telemetrics Semi-structured Client data Ingestion Discovery environment Insights lead to more questions Client s business operations Place Product Target market Price Promotion Intelligent networks Analysis and discovery Patterns insights and ideas Phase 1 Phase 2 Phase 3 Phase 4 New and revised business and analytical processes to be implemented in the enterprise 33 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

34 HP Big Data Discovery Environment How does it work? A private environment in our space Bring the data in and get started Joint work with support technical, data scientists, and analysts At the end of discovery you can move to production Ready configurations will be leveraged based on client use cases. Base configuration includes Hadoop and Vertica, as well as core Autonomy/IDOL components. 34 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

$The benefits of your HP Big Data Discovery Experience Explore at a fraction of a cost of owning them Accelerate innovation by integrating a wide range of structured and unstructured data Establish$

35 The benefits of your HP Big Data Discovery Experience Explore at a fraction of a cost of owning them Accelerate innovation by integrating a wide range of structured and unstructured data Establish the value through your use cases Justify the technology Innovate your business 35 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

36 Why the HP Discovery Experience solution? What we offer in the Big Data Discovery Experience solution that others in the market may not be providing Rich functionality in a standard configuration Quick start-up options Guided and assisted engagements Private rather than public environment Predictable costs 36 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

37 Big Data Implementation Service Using the framework of HP Global Methodology for IM&A Deliver complete solutions against the end-user requirements. How? Develop a custom Big Data solution or Productize the results of the Big Data Discovery Experience 37 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Infrastructure. Self Build Reference Architecture or Appliance? René Witteveen Consultant HP

Infrastructure. Self Build Reference Architecture or Appliance? René Witteveen Consultant HP Infrastructure for BIG DATA Self Build Reference Architecture or Appliance? René Witteveen Consultant HP rene.witteveen@hp.com BIG DATA BIG BROTHER What s Obama saying? Psssssst what s BIG DATA? amount