Big Data Analytics: Today's Gold Rush November 20, 2013

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1 Copyright 2013 Vivit Worldwide Big Data Analytics: Today's Gold Rush November 20, 2013

2 Brought to you by Copyright 2013 Vivit Worldwide

3 Hosted by Bernard Szymczak Vivit Leader Ohio Chapter TQA SIG Copyright 2013 Vivit Worldwide

4 Today s Presenter Chris Selland VP Marketing at HP Vertica HP Software Copyright 2013 Vivit Worldwide

5 Housekeeping This LIVE session is being recorded Recordings are available to all Vivit members Session Q&A: Please type questions in the Questions Pane Copyright 2013 Vivit Worldwide

6 Webinar Control Panel Toggle View Window between Full screen/window mode. Questions Copyright 2013 Vivit Worldwide

7 Big Data Analytics Today s Gold Rush Chris Selland HP Vertica

8 In data, there is gold In Data There is Gold 8

9 We are in a new era of accelerated innovation 2013 Every 60 seconds 98,000+ tweets 695,000 status updates 11million instant messages 698,445 Google searches 168 million+ s sent 1,820TB of data created Growing Internet of Things (IoT) By 2020 Devices DATA Mobile Apps 30 Billion (1) 40 Trillion GB (2) 10 Million (3) 217 new mobile web users Pervasive Connectivity Smart Device Expansion Explosion of Information for 8 Billion (4) A new style of IT required for IoT solutions 9 (1) IDC Directions 2013: Why the Datacenter of the Future Will Leverage a Converged Infrastructure, March 2013, Matt Eastwood ; (2) & (3) IDC Predictions 2012: Competing for 2020, Document , December 2011, Frank Gens; (4)

10 The challenges of big data Variety, velocity, volume, time to value 90% of digital content created by 2015 will be mixed data types ¹ 75% of currently deployed data warehouses will not scale sufficiently to meet new information velocity and complexity of demands by 2016² 48% Worldwide information volume growth of digital content¹ 86% of corporations cannot deliver the right information, at right time to support enterprise outcomes all of the time³ ¹Source: IDC Predictions 2012: Competing for 2020 ²Source: Gartner - The State of Data Warehousing in 2012 ³Source: Coleman Parkes Survey Nov

11 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. 11 Copyright Copyright Hewlett-Packard Development Company, Company, L.P. L.P. The information The information contained contained herein herein is subject is subject to change to change without without notice. notice.

12 Accuracy and Insight Shining a Light on Dark Data Traditional Enterprise Data Big Data Dark Data CRM ERP Data Warehouse Web Social Log Files Machine Data Semi-structured Data Volumes Unstructured 12 Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

13 Legacy architectures were built for a different world Yesterday s data warehouse and analytic infrastructure Proprietary Expensive Centralized, monolithic Process laden Batch Summary Slow 13

14 Imagine a world where a conversation with your data can bring answers in real time Unlimited scope across structured and unstructured data Near real time, iterative queries Dramatically lower TCO 14

15 HP Vertica Analytics Platform Blazing fast analytics Gain insights into your data in near-real time by running queries 50x-1,000x faster than legacy products Massive scalability Infinitely and easily scale your solution by adding an unlimited number of industry-standard servers Open architecture Protect your investment in hardware and software, with built-in support for Hadoop, R Easy set-up and administration Get to market quickly with your analytics initiatives at low cost of administration and maintenance Optimized data storage HP Vertica Analytics Platform High-performance data analytics platform purpose built for big data Store 10x-30x more data per server than row databases with patented columnar compression Speed, scalability, simplicity, and openness at lower TCO 15

16 Today s organizations move from Return on Infrastructure to Return on Information 16

17 Integrating Structured & Semi-Structured Data Select Customers with < 2 Months Remaining on Contract with 5+ dropped calls per week and lifetime value > $500 Customer expressed negative sentiment through social media and/or support within the last 3 months Get me all matches from our structured enterprise systems - CRM and Call Detail Records - that match the query From semi-structured sources get me all matches for social, , calls that were negative for those customers Structured Data Semi-Structured Data 17

18 Disrupting Elections "We were going to demand data on everything, we were going to measure everything, We were going to put an analytics team inside of us to study us the entire time to make sure we were being smart about things. Jim Messina Campaign Manager, Obama 2012 Replay available at 18

19 Customers across industries finding answers with HP Vertica Promotional testing Claims analyses Patient records analyses Clinical data analyses Fraud monitoring Financial tracking Tick data back-testing Behavior analytics Click stream analyses Network analyses Customer analytics Compliance testing Loyalty analysis Campaign management 19

20 HAVEn big data platform HAVEn Hadoop/ HDFS Autonomy IDOL Vertica Enterprise Security n Apps Catalog massive volumes of distributed data Process and index all information Analyze at extreme scale in real-time Collect & unify machine data Powering HP Software + your apps 20 Transactional Social media Video Audio Texts Mobile data Documents IT/OT Search engine Images hp.com/haven

21 Monetize Real time Statistics Better decisions Analysis 21 Make smarter decisions in real time.

22 Thank you Chris Selland (508)

23 Thank you Complete the short survey and opt-in for more information from HP. Copyright 2013 Vivit Worldwide

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