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3 Accelerating Modernization Across the Enterprise Cloud Computing User Experience Enterprise Mobility Customer Relationship Management Business Analysis Managed Services Custom Application Development Ideation Engagement Management Application & Systems Integration Business Intelligence Portals and Collaboration

4 Today s Agenda: Morning: For business managers, architects, developers, analysts and data scientists. 10:00 AM Registration 10:30 AM Big Data Use Cases 12:00 PM Lunch & Registration for Afternoon Sessions Afternoon: A Deeper Dive: For architects, developers and data scientists. 1:00 PM Understanding Apache Hadoop 2:00 PM Big Data Solution Deployment Models 3:00 PM Advanced Analytics Architectures 4:30 PM Open Q&A 4

5 Upcoming Roadshow Stops: Orange County: Wednesday, August 19th Los Angeles: Thursday, August, 20th Philadelphia: Tuesday, September 22nd New York: Wednesday, September 23rd Denver: Wednesday, October 14th Seattle: Wednesday, October 21st Portland: Thursday, October 22nd Chicago: Tuesday, November 10th Dallas: Wednesday, December 9th Houston: Thursday, December 10th Phoenix: Wednesday, January 20th,

6 Today s Presenters: 6

7 Intro to Big Data Analytics Presented by: Tom Marek Senior Solution Partner

8 Information is the oil of the 21st century, and analytics is the combustion engine. ~ Peter Sondergaard

9 Questions How many of your organizations are using Hadoop? How many of you in this room have used Hadoop? How many of your organization use cloud services? How many of you have a use case in mind now? 9

10 Forces Challenging the Traditional Data Warehouse Approach

11 Increasing Data Volumes From the beginning of recorded time until 2003, we created 5 exabytes of data (5 billion gigabytes). In 2011 the same amount was created every two days. ~ The Human Face of Big Data (Rick Smolan, Jennifer Erwit) 11

12 Internet / Social Data Clickstream API Economy Twitter / Facebook Insert newest Social site 12

13 Internet of Things Wearables Smart meters Machine sensors Leak detectors Temperature gauges 13

14 Audio and Video Call center calls Manufacturing line video Surveillance video Police cameras Sports video 14

15 Speed of Business Business needs change Self service has become the new standard ETL is too slow 15

16 New Technologies 16

17 History and Fundamentals of Big Data Processing

18 Yahoo! And Google Prototypes aimed at improving Yahoo's search engine Originally called Nutch, now an Apache project Scaled better after publication of Google's File System and MapReduce papers, in 2003 and 2004 respectively 18

19 Innovators 19

20 Early Adopters 20

21 The 3 V s of Big Data There has been a number of industry trends that have driven the need for and the adoption of Big Data: Volume Ø 40 Zettabytes of data will be created by Times increase from 2005 Ø Most companies in the U.S have at least 100Tb of data Variety Ø NYSE captures 1TB of trade information every day Ø The average modern car has over 100 sensors Velocity Ø Nearly 420 Million wearable health monitors Ø Over 4 Billion hours of video watched on YouTube everyday

22 ROI Should Drive Your Next Step Do you have a data driven culture? Utilize Neudesic s ROI Focused Development Approach User adoption must be a focus 22

23 User Adoption Increase adoption by exposing the right data through the right tools Sophistication of User Access to Hadoop / Data Feeds & Advanced Data Visualization Tools Social Marketing Global Market Research New Product Research Competitive Analysis Pricing & Risk Management Access to Semantic Models & Self- Service BI Tools Marketing Analyst Market Analyst Product Analyst Customer Support Finance Data Alerts, Structured Reports & Dashboards CxO s Customer Analysis Product Support Sales Operations Volume of Data

24 Popular Use Cases for Big Data Analytics

25 Use Case: ETL Offloading Have you outgrown your data delivery SLAs? Get the right data at the right time 25

26 Use Case: Iterative Exploration What can we do with all of this data? Mine for answers, one question at a time 26

27 Use Case: Self Service Are your self service reports only telling half the story? Quickly deliver large datasets for ad hoc analysis. 27

28 Use Case: IoT What action does your IoT device drive? Help guide the buyers of the device to the action they are looking to take 28

29

30 Neudesic s Offer: Find Your Quick Wins!

31 ROI Focused Development APPLICATION ISSUE TIMELINE COST MONETARY ROI NON- MONETARY ROI SALES S TATUS REPORTS 50 sales p eople worldwide manually creating status reports (2 h ours e ach week) 2 weeks $20k Hourly wages recovered pay for this in 5 weeks Sales force more focused o n selling DEVICE MONITORING Equipment failure prediction for d evices across the US, with over 5 00M monitored devices 16 weeks $500k Limit warranty e vents proactively a nd in d oing so lower cost o f e ach interaction b y a pprox. $250 per e vent Improved customer e xperience TEAM S TRENGTH & RETENTION Unwanted a ttrition % Team S trength 10 weeks Less than $50k Avoid u nwanted a ttrition for 3 p eople: Recruiting $ 2k Interviewing $ 2k, 2 weeks of lost p roductivity = $ 14k Prevent u nwanted a ttrition; mitigate loss o f a dditional team members preventing a dditional losses in productivity, recruiting, d omain knowledge, customer satisfaction, external b randing impacts, e tc. 31

32 ROI Focused Development APPLICATION BUSINESS VALUE FEASIBILITY ROI MINUS COST SALES STATUS REPORTS 7 9 $162k DEVICE MONITORING 9 3 $7M TEAM STRENGTH & RETENTION 4 6 $60k Device Monitoring: Example Team Strength & Rentention: Example ROI Calculation ROI Calculation Sales Status Reports: Example ROI Calculation M [employees] [all devices] x 50 [sales people] x The Business Value is provided The Feasibility is provided by 1% [attrition [failures per year] saved] x = by the business the technical team with a 10 being end users with a 2 [hours per week] x 10 1M [employees saved per year] [warranty events] x 10 being the highest the most feasible $35 [salary per hour] x x $2k 5% [recruiting] [preventative fix] x $3500 [cost each week] $2k 50k [interview time [cost effective warranty event] lost] x 52 [weeks per year] $10k $150 [lost productivity] [savings per event] x x = $182K [ROI for first year] $7.5M $140K [ROI for first year] [ROI for first year] 32 $20k [weeks per year] - - $500k $100k [weeks per year] [weeks per year] - $162K [ROI minus cost] $7M $40k [ROI minus cost] [ROI minus cost]

33 Find Your Quick Wins Quick Wins Device Monitoring Sales Status Reports Team Strength & Retention 33

34 Next Step: Become the BI Superhero ü Information Management ü Big Data Storage ü Apache Hadoop ü Real- time intelligence ü Machine learning ü IoT ü Dashboards and Visualizations ü and more! Ideate, chart your quick wins, ask questions and get answers to your real Big Data challenges. It s insightful, it s easy and can be done from the comfort of your conference room 34

35 Tom Marek Questions? Orion Gebremedhin

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