Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Enrich a 360-degree Customer View with Splunk and Apache Hadoop


Published on

What if your organization could obtain a 360 degree view of the customer across offline, online and social and mobile channels? Attend this webinar with Splunk and Hortonworks and see examples of how marketing, business and operations analysts can reach across disparate data sets in Hadoop to spot new opportunities for up-sell and cross-sell. We'll also cover examples of how to measure buyer sentiment and changes in buyer behavior. Along with best practices on how to use data in Hadoop with Splunk to assign customer influence scores that online, call-center, and retail branches can use to customize more compelling products and promotions.

Published in: Technology
  • Sex in your area is here: ♥♥♥ ♥♥♥
    Are you sure you want to  Yes  No
    Your message goes here
  • Dating direct: ❤❤❤ ❤❤❤
    Are you sure you want to  Yes  No
    Your message goes here

Enrich a 360-degree Customer View with Splunk and Apache Hadoop

  1. 1. Enrich a 360-degree Customer View with Splunk® and Apache™ Hadoop® © Hortonworks Inc. 2014
  2. 2. Your Presenters • Brett Sheppard (@zettaforce) – Director, Big Data, Splunk – Former analyst at Gartner and DoD (civilian contractor), big data, enterprise architectures – Weekend volunteer with my dog in hospitals • Bob Page (@bobpage) – VP Products, Hortonworks – Ran eBay’s data platform – Enjoys good wine
  3. 3. Today’s Topics • Drivers for the Modern Data Architecture • From Raw Data to Digital Intelligence • Demo: 360-degree Customer View • Q&A © Hortonworks Inc. 2014
  4. 4. Hadoop Adoption “Hadoop’s momentum is unstoppable as its open source roots grow wildly into enterprises. Its refreshingly unique approach to data management is transforming how companies store, process, analyze, and share big data.” -- Mike Gualtieri, Principal Analyst, Forrester © Hortonworks Inc. 2014
  5. 5. DATA    SYSTEM   APPLICATIONS   A Traditional Approach Under Pressure Custom   Applica4ons   Business     Analy4cs   Packaged   Applica4ons   2.8  ZB  in  2012   85%  from  New  Data  Types   RDBMS   EDW   MPP   REPOSITORIES   15x  Machine  Data  by  2020   40  ZB  by  2020   SOURCES   Source: IDC Exis4ng  Sources     (CRM,  ERP,  Clickstream,  Logs)   © Hortonworks Inc. 2014 Emerging  Sources     (Sensor,  Sen4ment,  Geo,  Unstructured)  
  6. 6. APPLICATIONS   Emerging Modern Data Architecture Custom   Applica4ons   Business     Analy4cs   Packaged   Applica4ons   DEV  &  DATA   TOOLS   SOURCES   DATA    SYSTEM   BUILD  &  TEST   OPERATIONAL   TOOLS   RDBMS   EDW   MANAGE  &   MONITOR   MPP   REPOSITORIES   Exis4ng  Sources     (CRM,  ERP,  Clickstream,  Logs)   © Hortonworks Inc. 2014 Emerging  Sources     (Sensor,  Sen4ment,  Geo,  Unstructured)  
  7. 7. The Common Journey with Hadoop MDA/Data Lake Cost, Insight IT Driven SCALE More data and analytic apps New Analytic Apps New Types of Data LOB Driven SCOPE © Hortonworks Inc. 2014
  8. 8. Unlock Value in New Types of Data 1.  Social Understand how people are feeling and interacting – right now 2.  Clickstream Capture and analyze website visitors’ data trails and optimize your website 3.  Sensor/Machine Discover patterns in data streaming from remote sensors and machines 4.  Geographic Analyze location-based data to manage operations where they occur Value 5.  Historical Logs Diagnose process failures and prevent security breaches 6.  Unstructured (txt, video, pictures, etc..) Understand patterns in files across millions of web pages, emails, and documents © Hortonworks Inc. 2014 + Online archive Data that was once purged or moved to tape can be stored in Hadoop to discover long term trends and previously hidden value
  9. 9. Example Journey Towards a Data Lake PB’s Data Lake PB Risk Management E.g., Fraud Reduction New Business E.g., Data as a Product DATA TB’s Customer Intimacy E.g., 360 Degree View of the Customer DATA LAKE Operational Excellence E.g., Network Maintenance VALUE © Hortonworks Inc. 2014 An architectural shift in the data center that uses Hadoop to deliver deep insight across a large, broad, diverse set of data at efficient scale
  10. 10. Enabling Hadoop for the Enterprise 1 2 3 Capabilities Ensure enterprise capabilities are delivered in 100% open source to benefit all Integration Interoperable with existing data center investments Skills Leverage your existing skills: development, analytics, operations 2006 © Hortonworks Inc. 2014 2007 2008 2009 2010 2011 2012 2013 2014 2015
  11. 11. Core Capabilities of Enterprise Hadoop 1  Presenta4on  &  Applica4on    Opera4ons   Enable  both  exis4ng  and  new  applica4ons  to  provide     value  to  the  organiza4on   Empower  Current  opera4ons  and   security  tools  to  manage  Hadoop   Data   Governance    BROAD  INSIGHT   Integrate  with   exis4ng  systems   and  move  data  in/ out  and  within  the   environment   Access  your  data  simultaneously  in  mul4ple  ways   (batch,  interac4ve)   Opera4ons   Security   Allow  you  to   Provide  layered   deploy  and   approach  to   security  through   effec4vely  manage   Authen4ca4on,   the  environment   Authoriza4on,   Accountability  and   Data  Protec4on   Capabilities Ensure enterprise capabilities are delivered in 100% open source to benefit all Data  Access    EFFICIENT  SCALE   Data  Management   Store  and  process  all  of  your  Corporate  Data  Assets    Deployment  Model   Provide  the  efficient  deployment  op4on  for  your  organiza4on     © Hortonworks Inc. 2014
  12. 12. Skills Leverage your existing skills: development, analytics, operations Integration Interoperable with existing data center investments © Hortonworks Inc. 2014 COLLECT   PROCESS   BUILD   ANALYST   Ensure enterprise capabilities are delivered in 100% open source to benefit all SEARCH   ANALYSE   VISUALIZE   OPERATOR   1 2 3 Capabilities DEVELOPER   Enabling Familiar and Existing Tools PROVISION   MANAGE   MONITOR  
  13. 13. Requirements for Enterprise Hadoop DATA    SYSTEM   APPLICATIO NS   1 2 SOURCES   3 Capabilities Business     Ensure enterprise capabilities Custom   Analy4cs are delivered in   100% open Applica4ons   source to benefit all Packaged   Applica4ons   Skills Interoperable with existing Exis4ng  Sources     data center investmentsLogs)   (CRM,  ERP,  Clickstream,   © Hortonworks Inc. 2014 Applications DEV  &  DATA   TOOLS   Business  TEST   Intelligence, BUILD  & Developer IDEs, Data Integration OPERATIONAL   TOOLS   Systems Leverage your existing RDBMS   EDW   MPP   skills: development, REPOSITORIES   analytics, operations Integration Integrate with MANAGE  &   MONITOR   Data Systems & Storage, Systems Management Platforms Emerging  Sources     (Sensor,  Sen4ment,  Geo,  Unstructured)   Operating Systems, Virtualization, Cloud, Appliances
  14. 14. Splunk + Hortonworks © Hortonworks Inc. 2014
  15. 15. © Hortonworks Inc. 2014
  16. 16. Big  Data  Comes  From  Machines   Volume | Velocity | Variety | Variability GPS, RFID, Hypervisor, Web Servers, Email, Messaging Clickstreams, Mobile, Telephony, IVR, Databases, Sensors, Telematics, Storage, Servers, Security Devices, Desktops
  17. 17. Machine  Data  Contains  Powerful  Insights  
  18. 18. Delivering  the  360-­‐Degree  Customer  View   Synthesize  data  from   all  customer  touch   points  –  360°  view   "  "  "  "  "  "  "  Screen  new  account  applicaAons   Improve  customer  service  experience   Reduce  customer  churn     Recommend  next  product  to  buy   Localize  and  personalize  promoAons   Track  markeAng  channel  effecAveness   Empower  omni-­‐channel  retailing   Why this is hard: data lives in separate silos with incompatible formats
  19. 19. Big  Data  Doesn’t  Have  to  Be  a  Science  Project  
  20. 20. Get  Started  with  Hunk  +  Hortonworks  in  <  1  Hour   1 Download Hortonworks Sandbox and Hunk 3 Immediately Explore   Analyze   2 Point Hunk at Hadoop Cluster HDFS and MapReduce Visualize   Dashboards   Share   start exploring, analyzing and visualizing raw data in Hadoop
  21. 21. Challenges  of  AlternaAve  Approaches  
  22. 22. More 360-­‐Degree  Customer  View   Complete Customer View ese ze th y Anal ve, ured i truct s es mas e data hanc ion with w s En diver Hadoop mat is ra s in infor sis of thfrom   "   Screen  new  account  applicaAons   Synthesize  data   for a set y anal op t ata all  customer  douch   view o plete Had360°  miew   havio r Improve  customer  service  experience   " points  –ore co v r be   m me usto "   Reduce  customer  churn     of c "  eb ta in e da pache w te or St p: A e si adoo ommerc H ec i ogs, , Akama gs, l lo ity activ hosting s e imag proxy log d Squi Recommend  next  product  to  buy   "  Localize  and  personalize  promoAons   "  Empower  omni-­‐channel  retailing  
  23. 23. Deep  Insight  into  Customer  Behavior  and  SenAment  
  24. 24. Search,  Explore  and  Analyze   Rapidly  interact  with  data   Pause or stop MapReduce jobs •  Powerful  Search  Processing   Search interface •  Preview results •  •  •  Language  (SPL™)   Ad  hoc  exploratory  analyAcs   across  massive  datasets   Preview  results   No  fixed  schema   No  requirement  to   “understand”  data  upfront   Drill down to raw data
  25. 25. Inform,  Upsell  and  Cross-­‐sell   Measure  a_enAon  to   specific  content   Analyze  click-­‐through  and   how  consumers  navigate   Compare  product  bundle   promoAons  with   mulAvariate  tesAng  
  26. 26. PrioriAze  PromoAons  with  Customer  Influence  Scores  
  27. 27. Understand  Web  OperaAons  and  AdverAsing   Weblog Traffic Data Web User Clickstreams 750 million 12 million queries per month monthly visits Maintain Protect Track high performance content against malicious bots traffic sources for advertisers
  28. 28. Analyze  Mobile  App  Performance  and  Usage   •  •  •  •  •  •  •  Product adoption trend Users and clients Feature adoption User engagement Usage patterns Mobile devices Client dashboard
  29. 29. Easy  and  Fast  to  Get  Started,  Learn  and  Use   Configure Hortonworks Sandbox with Hunk: Splunk Analytics for Hadoop
  30. 30. Configure  Hunk  with  Hortonworks  Sandbox  1.3
  31. 31. Hortonworks  +  Hunk  =  Business  Value   “Splunk’s Hunk is perhaps the most promising technology to deliver a true interactive experience. Especially powerful are Splunk’s capabilities for discovering the structure of machine data and other unstructured data on the fly.”
  32. 32. About Splunk and Hortonworks Get started with Hortonworks Sandbox Tr y Now Get started with Hunk: Splunk Analytics for Hadoop Follow us: @hortonworks @splunk Question & Answer session will be conducted electronically, using the panel to the right of your screen