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Using HP Vertica and Apache Hadoop 
…for customer analytics 
Page 1 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
We do Hadoop.
Your speakers… 
John Kreisa, VP Strategic Alliance Marketing 
Hortonworks 
Chris Selland, VP Business Development 
HP Software, Big Data Group 
Page 2 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
Poll 
Where are you in your Hadoop journey? 
• Researching our options 
• Currently evaluating some software 
• Deep in a trial 
• What’s Hadoop? 
Page 3 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
Big Data Market Trends & Projections 
Big 
Data 
Explosion 
Page 4 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
% by which org’s 
leveraging modern info 
management systems 
outperform peers by 2015 
85% 
from new 
data types 
ñ 
Hadoop 
enabled 
DBMS’s 
50x 
data growth 2010 to 
2020 
1 Zettabyte (ZB) 
= 
1 Billion TBs 
15x 
growth rate of 
machine generated 
data by 2020 
The US has 1/3 of the world’s data 
Big Data is 1 of 5 US GDP Game Changers $325 billion 
incremental annual GDP from big data analytics in retail and manufacturing by 
2020
Over 50% of Internet connections are things: 
2011: 15+ billion permanent, 50+ billion intermittent 
2020: 30+ billion permanent, >200 billion intermittent 
Cameras and microphones widely 
deployed 
Page 5 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
New routes to market via intelligent 
objects 
Content and services via 
connected products 
Everything has 
a URL 
Remote sensing of objects and 
environment 
Augmented 
reality 
Situational decision 
support 
Building and 
infrastructure management 
Source: Gartner Keynote at Hadoop Summit 2013
A Data Architecture Under Pressure From New Data 
DATA 
SYSTEM 
APPLICATIONS 
Business 
Analy4cs 
RDBMS 
EDW 
MPP 
REPOSITORIES 
SOURCES 
Exis4ng 
Sources 
Custom 
Applica4ons 
(CRM, 
ERP, 
Clickstream, 
Logs) 
Page 6 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
Packaged 
Applica4ons 
2.8 
ZB 
in 
2012 
85% 
from 
New 
Data 
Types 
15x 
Machine 
Data 
by 
2020 
40 
ZB 
by 
2020 
Source: IDC 
OLTP, 
ERP, 
CRM 
Systems 
Unstructured 
documents, 
emails 
Server 
logs 
Clickstream 
Sen>ment, 
Web 
Data 
Sensor. 
Machine 
Data 
Geoloca>on
Hadoop Within An Emerging Modern Data Architecture 
Page 7 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
DEV 
& 
DATA 
TOOLS 
Build & 
Test 
OPERATIONS 
TOOLS 
Provision, 
Manage & 
Monitor 
DATA 
SYSTEM 
REPOSITORIES 
SOURCES 
RDBMS 
EDW 
MPP 
OLTP, 
ERP, 
CRM 
Systems 
Documents, 
Emails 
Web 
Logs, 
Click 
Streams 
Social 
Networks 
Machine 
Generated 
Sensor 
Data 
Geoloca>on 
Data 
Governance 
& Integration 
Security 
Operations 
Data Access 
Data Management 
APPLICATIONS 
Business 
Analy4cs 
Custom 
Applica4ons 
Packaged 
Applica4ons
Hadoop: Typically Used For New Analytic Applications 
SCALE SCOPE 
New Analytic Apps 
New types of data 
LOB-driven 
Page 8 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
Clickstream 
Capture and 
analyze website 
visitors’ data trails 
and optimize your 
website 
Sensors 
Discover patterns in 
data streaming 
automatically from 
remote sensors and 
machines 
Page 9 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
Server Logs 
Research logs to 
diagnose process 
failures and prevent 
security breaches 
Hadoop Value: New types of data 
Sentiment 
Understand how 
your customers 
feel about your 
brand and products 
– right now 
Geographic 
Analyze location-based 
data to 
manage operations 
where they occur 
Unstructured 
Understand patterns 
in files across 
millions of web 
pages, emails, and 
documents
New Analytic Applications For New Types Of Data 
$ 
Page 10 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
• Supplier Consolidation 
• Supply Chain and Logistics 
• Assembly Line Quality Assurance 
• Proactive Maintenance 
• Crowdsourced Quality Assurance 
• New Account Risk Screens 
• Fraud Prevention 
• Trading Risk 
• Maximize Deposit Spread 
• Insurance Underwriting 
• Accelerate Loan Processing 
• Call Detail Records (CDRs) 
• Infrastructure Investment 
• Next Product to Buy (NPTB) 
• Real-time Bandwidth 
Allocation 
• New Product Development 
• 360° View of the Customer 
• Analyze Brand Sentiment 
• Localized, Personalized 
Promotions 
• Website Optimization 
• Optimal Store Layout 
Financial 
Services 
Retail Telecom Manufacturing 
Healthcare Utilities, 
Oil & Gas 
Public 
Sector 
• Genomic data for medical trials 
• Monitor patient vitals 
• Reduce re-admittance rates 
• Store medical research data 
• Recruit cohorts for 
pharmaceutical trials 
• Smart meter stream analysis 
• Slow oil well decline curves 
• Optimize lease bidding 
• Compliance reporting 
• Proactive equipment repair 
• Seismic image processing 
• Analyze public sentiment 
• Protect critical networks 
• Prevent fraud and waste 
• Crowdsource reporting for 
repairs to infrastructure 
• Fulfill open records requests
360° Customer View for Home Supply Retailer 
Problem 
Lack of a unified customer record across all channels 
• Global distribution online, in home and across 2000+ stores 
• No “golden record” for analytics on customer buying behavior across all channels 
• Data repositories on website traffic, POS transactions and in-home services existed 
in isolation of each other 
• Limited ability for targeted marketing to specific segments 
• Data storage costs increasing 
Solution 
HDP delivers targeted marketing & data storage savings 
• Golden record enables targeted, customized marketing 
• Data warehouse offload saved millions in recurring expense 
• Customer team continues to find unexpected, unplanned uses for their 360 degree 
view of customer buying behavior 
• New use case: price optimization versus competitors à several millions in top-line 
revenue growth 
Page 11 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
Creating Opportunity 
Data: Clickstream, 
Unstructured, Structured 
Retail 
Major home improvement 
retailer 
>$74B in revenue 
>300K employees 
>2,200 stores 
RT2
Hadoop Incrementally Delivers A ‘Data Lake’ 
A Modern Data Architecture/Data Lake 
SCALE SCOPE 
RDBMS 
MPP 
EDW 
New Analytic Apps 
New types of data 
LOB-driven 
Page 12 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
Governance 
& Integration 
Security 
Operations 
Data Access 
Data Management 
Data Lake 
An architectural shift in the 
data center that uses Hadoop 
to deliver deeper insight across 
a large, broad, diverse set of 
data at efficient scale
Hadoop: An Integrated Part Of The Modern Data Architecture 
Page 13 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
DEPTH 
Hortonworks engages 
in deep engineered 
relationships with the 
leaders in the data center, 
applications and 
operations 
BREADTH 
Hundreds of partners work 
with us to certify their 
applications to work with 
Hadoop so they can 
extend big data to their 
users 
DEV 
& 
DATA 
TOOLS 
Provision, 
Manage & 
Monitor 
DATA 
SYSTEM 
APPLICATIONS 
OPERATIONAL 
TOOLS 
INFRASTRUCTURE 
HDP 2.1 
Governance 
& Integration 
Security 
Operations 
Data Access 
Data Management 
Business 
Analy4cs 
Custom 
Applica4ons 
Packaged 
Applica4ons 
REPOSITORIES 
Build & Test 
On Premise or in 
the Cloud 
SOURCES 
OLTP, 
ERP, 
CRM 
Systems 
Documents, 
Emails 
Web 
Logs, 
Click 
Streams 
Social 
Networks 
Machine 
Generated 
Sensor 
Data 
Geoloca>on 
Data
Customer Analytics with HP Vertica + 
Hortonworks 
Chris Selland, VP Business Development 
HP Software, Big Data Group 
Page 14 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
Completing Analytical Vision 
Structured Semi-Structured Unstructured 
CRM ERP Data Warehouse Web Social Log Files Machine Data Images 
Data Types 
Accuracy and Insight 
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 15 without notice. 
Dark Data 
Traditional Big Data 
Enterprise Data 
Audio Video
Customer Analytics in the Big Data Era 
Select Customers with < 2 Months Remaining on 
Contract with 5+ dropped calls per week and lifetime 
value > $500 
From a database get me all matches from the CRM and Call Detail Records that match the query 
Customer expressed negative sentiment through 
social media, web log and/or support within the last 3 
months 
From unstructured sources get me all matches for weblogs, calls, chat, email that were negative for the structured results 
Structured Data 
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 16 without notice. 
Unstructured Data
Introducing HP Vertica Dragline 
Faster answers from Big Data at a fraction of the cost of traditional data warehouses 
Store all your data in any format cost-effectively across 
Vertica + Hadoop 
Explore all your data directly in Hadoop without moving 
or changing it 
Serve all of your data consumers without compromise 
from individualized queries to large complex reports 
HP Vertica 
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 17 without notice.
HP Vertica Dragline: 
The Richest, Most Open SQL on Hadoop 
Page 18 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
Challenge 
Extracting Data from Hadoop 
requires complex and brittle ETL 
processes 
Solution: 
Hadoop Navigation and Analytics 
Benefits: 
• Navigate Hadoop data using its 
native catalog 
• Quickly & easily load native data 
types from Hadoop to Vertica 
• Avoid creating and maintaining 
time-consuming schemas 
• Use the full power of HP Vertica 
SQL and Analytics 
DEV 
& 
DATA 
TOOLS 
Provision, 
Manage & 
Monitor 
DATA 
SYSTEM 
APPLICATIONS 
OPERATIONAL 
TOOLS 
INFRASTRUCTURE 
HDP 2.1 
Governance 
& Integration 
Security 
Operations 
Data Access 
Data Management 
Business 
Analy4cs 
Custom 
Applica4ons 
Packaged 
Applica4ons 
REPOSITORIES 
Build & Test 
On Premise or in 
the Cloud 
SOURCES 
OLTP, 
ERP, 
CRM 
Systems 
Documents, 
Emails 
Web 
Logs, 
Click 
Streams 
Social 
Networks 
Machine 
Generated 
Sensor 
Data 
Geoloca>on 
Data
Flexible Vertica Hadoop Connectivity 
Leverage existing tools in shared Vertica and Hadoop storage environment 
HDP 2.1 
Hortonworks Data Platform 
HCatalog Connector 
Hadoop Connector webHCAT 
webHDFS 
ANSI SQL 
webHDFS 
Page 19 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
Provision, 
Manage & 
Monitor 
Ambari 
Zookeeper 
Scheduling 
Oozie 
Data Workflow, 
Lifecycle & 
Governance 
Falcon 
Sqoop 
Flume 
NFS 
WebHDFS 
BATCH, INTERACTIVE & REAL-TIME SECURITY 
DATA ACCESS 
YARN: Data Operating System 
DATA MANAGEMENT 
GOVERNANCE 
& INTEGRATION 
Authentication 
Authorization 
Accounting 
Data Protection 
Storage: HDFS 
Resources: YARN 
Access: Hive, … 
Pipeline: Falcon 
Cluster: Knox 
OPERATIONS 
Script 
Pig 
Search 
Solr 
SQL 
Hive 
HCatalog 
NoSQL 
HBase 
Accumulo 
Stream 
Storm 
1 ° ° ° ° ° ° ° ° ° 
° ° ° ° ° ° ° ° ° ° 
° ° ° ° ° ° ° ° ° ° 
° 
° 
N 
HDFS 
(Hadoop Distributed File System) 
In-Memory 
Spark 
TezTez 
Batch 
Map 
Reduce 
Storage Tiering 
HDFS Connector 
External Tables and Copy
Data Tiering and Cost Optimization 
Tier-off 
older data 
Cool 
Cold 
Hot 
Dark Data 
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 20 without notice. 
Value 
Discovery 
Interactive Data 
Frequently queried 
Vertica data cache 
Batch Data 
Archive Data 
Serve 
Convert data to 
Vertica storage format 
Explore 
Any format 
Store 
Location Format Any format
More than 140 Characters 
JSON Record-Unstructured Data 
{"filter_level":"medium","contributors":null,"text":“Listening to Meg Whitman talk about the New 
Style of IT at #HPDiscover","geo":null,"retweeted":false,"in_reply_to_screen_name":null,"truncated":false, 
"lang":"en","entities":{"symbols":[],"urls":[],"hashtags":[{"text":"nope","indices":[51,56]}], "user_mentions": 
[]},"in_reply_to_status_id_str":null,"id":346104750565097474,"source":"! 
<a href="http://twitter.com/download/iphone" rel="nofollow">Twitter for iPhone</a>", 
"in_reply_to_user_id_str":null,"favorited":false,"in_reply_to_status_id":null,"retweet_count": 
0,"created_at":“Tue Jun 11 03:19:37 +0000 2013","in_reply_to_user_id":null, "favorite_count":0,"id_str": 
"346104750565097474","place":null,"user": 
{"location":"","default_profile":false,"profile_background_tile":true,"statuses_count": 
2354,"lang":"en","profile_link_color":"FF0000","profile_banner_url":"https://pbs.twimg.com/profile_banners/ 
271588683/1370571522","id":271588683,"following":null,"protected":false,"favourites_count": 
121,"profile_text_color":"3D1957","description":"Dance It is a part of me A part of who I am It has entered my 
life Taken over my body It is in my walk In my movements In my thoughts I have become a 
DANCER","verified":false,"contributors_enabled": false,"profile_sidebar_border_color":"65B0DA","name":"ashley 
tousignant", "profile_background_color":"642D8B","created_at": "Thu Mar 24 20:25:59 +0000 
2011","default_profile_image":false,"followers_count":434,"profile_image_url_https":"https://si0.twimg.com/ 
profile_images/3765534455/ 
eee814d484d70b8eb9ca5db08a122cbb_normal.jpeg","geo_enabled":true,"profile_background_image_url":"http:// 
a0.twimg.com/images/themes/theme10/bg.gif","profile_background_image_url_https":"https://si0.twimg.com/images/ 
themes/theme10/ 
bg.gif","follow_request_sent":null,"url":null,"utc_offset":null,"time_zone":null,"notifications":null,"profile_u 
se_background_image":true,"friends_count": 
844,"profile_sidebar_fill_color":"7AC3EE","screen_name":"01ashleymt","id_str":"271588683","profile_image_url":"h 
ttp://a0.twimg.com/profile_images/3765534455/eee814d484d70b8eb9ca5db08a122cbb_normal.jpeg","listed_count": 
0,"is_translator":false},"coordinates":null}! 
! 
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 21 without notice.
HP Vertica Flex Zone 
Avoid creating and maintaining time-consuming schemas 
Faster SQL querying 
Auto-schematization 
Flexible parsers 
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 
22 
on semi-structured data 
semi-structured data loading 
for JSON and delimited data 
One-step schema 
for blazing-fast performance 
Load, manage, and explore semi-structured data
Major Computer Products Manufacturer 
© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 
23 
Analyzing Billions of Clicks 
Challenge online 
• Millions of website visitors 
generate billions of clicks per 
month 
• Must store 5 years worth of 
data to get full value of year-over- 
year clickstream analysis 
• Legacy database had sluggish 
performance – queries took 
48 hours after each day’s 
transactions 
• Extremely complex website – 
many pages are generated 
dynamically creating complex 
clickstream trails 
HP Vertica Solution 
• Queries run in hours or even 
minutes; 48x – 100x faster 
• Industry-standard SQL 
accelerated acceptance and 
proficiency 
• Speed of HP Vertica allows 
iterative and recursive 
analysis for deeper dives 
• Functionality tailored to 
individual interactions based 
on nuanced understanding of 
user behavior at an individual 
level
Next steps… 
More about HP Vertica & Hortonworks 
http://hortonworks.com/partner/HP/ 
Download the Hortonworks Sandbox 
Learn Hadoop 
Build Your Analytic App 
Try Hadoop 2 
Don’t miss our next webinar! HP Converged Systems and Hortonworks 
Planning for the Impacts of Big Data in the Data Center 
http://info.hortonworks.com/hpconvergedandhortonworks.html 
Page 24 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
End 
Page 25 © Hortonworks Inc. 2011 – 2014. All Rights Reserved

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Hortonworks and HP Vertica Webinar

  • 1. Using HP Vertica and Apache Hadoop …for customer analytics Page 1 © Hortonworks Inc. 2011 – 2014. All Rights Reserved We do Hadoop.
  • 2. Your speakers… John Kreisa, VP Strategic Alliance Marketing Hortonworks Chris Selland, VP Business Development HP Software, Big Data Group Page 2 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
  • 3. Poll Where are you in your Hadoop journey? • Researching our options • Currently evaluating some software • Deep in a trial • What’s Hadoop? Page 3 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
  • 4. Big Data Market Trends & Projections Big Data Explosion Page 4 © Hortonworks Inc. 2011 – 2014. All Rights Reserved % by which org’s leveraging modern info management systems outperform peers by 2015 85% from new data types ñ Hadoop enabled DBMS’s 50x data growth 2010 to 2020 1 Zettabyte (ZB) = 1 Billion TBs 15x growth rate of machine generated data by 2020 The US has 1/3 of the world’s data Big Data is 1 of 5 US GDP Game Changers $325 billion incremental annual GDP from big data analytics in retail and manufacturing by 2020
  • 5. Over 50% of Internet connections are things: 2011: 15+ billion permanent, 50+ billion intermittent 2020: 30+ billion permanent, >200 billion intermittent Cameras and microphones widely deployed Page 5 © Hortonworks Inc. 2011 – 2014. All Rights Reserved New routes to market via intelligent objects Content and services via connected products Everything has a URL Remote sensing of objects and environment Augmented reality Situational decision support Building and infrastructure management Source: Gartner Keynote at Hadoop Summit 2013
  • 6. A Data Architecture Under Pressure From New Data DATA SYSTEM APPLICATIONS Business Analy4cs RDBMS EDW MPP REPOSITORIES SOURCES Exis4ng Sources Custom Applica4ons (CRM, ERP, Clickstream, Logs) Page 6 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Packaged Applica4ons 2.8 ZB in 2012 85% from New Data Types 15x Machine Data by 2020 40 ZB by 2020 Source: IDC OLTP, ERP, CRM Systems Unstructured documents, emails Server logs Clickstream Sen>ment, Web Data Sensor. Machine Data Geoloca>on
  • 7. Hadoop Within An Emerging Modern Data Architecture Page 7 © Hortonworks Inc. 2011 – 2014. All Rights Reserved DEV & DATA TOOLS Build & Test OPERATIONS TOOLS Provision, Manage & Monitor DATA SYSTEM REPOSITORIES SOURCES RDBMS EDW MPP OLTP, ERP, CRM Systems Documents, Emails Web Logs, Click Streams Social Networks Machine Generated Sensor Data Geoloca>on Data Governance & Integration Security Operations Data Access Data Management APPLICATIONS Business Analy4cs Custom Applica4ons Packaged Applica4ons
  • 8. Hadoop: Typically Used For New Analytic Applications SCALE SCOPE New Analytic Apps New types of data LOB-driven Page 8 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
  • 9. Clickstream Capture and analyze website visitors’ data trails and optimize your website Sensors Discover patterns in data streaming automatically from remote sensors and machines Page 9 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Server Logs Research logs to diagnose process failures and prevent security breaches Hadoop Value: New types of data Sentiment Understand how your customers feel about your brand and products – right now Geographic Analyze location-based data to manage operations where they occur Unstructured Understand patterns in files across millions of web pages, emails, and documents
  • 10. New Analytic Applications For New Types Of Data $ Page 10 © Hortonworks Inc. 2011 – 2014. All Rights Reserved • Supplier Consolidation • Supply Chain and Logistics • Assembly Line Quality Assurance • Proactive Maintenance • Crowdsourced Quality Assurance • New Account Risk Screens • Fraud Prevention • Trading Risk • Maximize Deposit Spread • Insurance Underwriting • Accelerate Loan Processing • Call Detail Records (CDRs) • Infrastructure Investment • Next Product to Buy (NPTB) • Real-time Bandwidth Allocation • New Product Development • 360° View of the Customer • Analyze Brand Sentiment • Localized, Personalized Promotions • Website Optimization • Optimal Store Layout Financial Services Retail Telecom Manufacturing Healthcare Utilities, Oil & Gas Public Sector • Genomic data for medical trials • Monitor patient vitals • Reduce re-admittance rates • Store medical research data • Recruit cohorts for pharmaceutical trials • Smart meter stream analysis • Slow oil well decline curves • Optimize lease bidding • Compliance reporting • Proactive equipment repair • Seismic image processing • Analyze public sentiment • Protect critical networks • Prevent fraud and waste • Crowdsource reporting for repairs to infrastructure • Fulfill open records requests
  • 11. 360° Customer View for Home Supply Retailer Problem Lack of a unified customer record across all channels • Global distribution online, in home and across 2000+ stores • No “golden record” for analytics on customer buying behavior across all channels • Data repositories on website traffic, POS transactions and in-home services existed in isolation of each other • Limited ability for targeted marketing to specific segments • Data storage costs increasing Solution HDP delivers targeted marketing & data storage savings • Golden record enables targeted, customized marketing • Data warehouse offload saved millions in recurring expense • Customer team continues to find unexpected, unplanned uses for their 360 degree view of customer buying behavior • New use case: price optimization versus competitors à several millions in top-line revenue growth Page 11 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Creating Opportunity Data: Clickstream, Unstructured, Structured Retail Major home improvement retailer >$74B in revenue >300K employees >2,200 stores RT2
  • 12. Hadoop Incrementally Delivers A ‘Data Lake’ A Modern Data Architecture/Data Lake SCALE SCOPE RDBMS MPP EDW New Analytic Apps New types of data LOB-driven Page 12 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Governance & Integration Security Operations Data Access Data Management Data Lake An architectural shift in the data center that uses Hadoop to deliver deeper insight across a large, broad, diverse set of data at efficient scale
  • 13. Hadoop: An Integrated Part Of The Modern Data Architecture Page 13 © Hortonworks Inc. 2011 – 2014. All Rights Reserved DEPTH Hortonworks engages in deep engineered relationships with the leaders in the data center, applications and operations BREADTH Hundreds of partners work with us to certify their applications to work with Hadoop so they can extend big data to their users DEV & DATA TOOLS Provision, Manage & Monitor DATA SYSTEM APPLICATIONS OPERATIONAL TOOLS INFRASTRUCTURE HDP 2.1 Governance & Integration Security Operations Data Access Data Management Business Analy4cs Custom Applica4ons Packaged Applica4ons REPOSITORIES Build & Test On Premise or in the Cloud SOURCES OLTP, ERP, CRM Systems Documents, Emails Web Logs, Click Streams Social Networks Machine Generated Sensor Data Geoloca>on Data
  • 14. Customer Analytics with HP Vertica + Hortonworks Chris Selland, VP Business Development HP Software, Big Data Group Page 14 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
  • 15. Completing Analytical Vision Structured Semi-Structured Unstructured CRM ERP Data Warehouse Web Social Log Files Machine Data Images Data Types Accuracy and Insight © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 15 without notice. Dark Data Traditional Big Data Enterprise Data Audio Video
  • 16. Customer Analytics in the Big Data Era Select Customers with < 2 Months Remaining on Contract with 5+ dropped calls per week and lifetime value > $500 From a database get me all matches from the CRM and Call Detail Records that match the query Customer expressed negative sentiment through social media, web log and/or support within the last 3 months From unstructured sources get me all matches for weblogs, calls, chat, email that were negative for the structured results Structured Data © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 16 without notice. Unstructured Data
  • 17. Introducing HP Vertica Dragline Faster answers from Big Data at a fraction of the cost of traditional data warehouses Store all your data in any format cost-effectively across Vertica + Hadoop Explore all your data directly in Hadoop without moving or changing it Serve all of your data consumers without compromise from individualized queries to large complex reports HP Vertica © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 17 without notice.
  • 18. HP Vertica Dragline: The Richest, Most Open SQL on Hadoop Page 18 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Challenge Extracting Data from Hadoop requires complex and brittle ETL processes Solution: Hadoop Navigation and Analytics Benefits: • Navigate Hadoop data using its native catalog • Quickly & easily load native data types from Hadoop to Vertica • Avoid creating and maintaining time-consuming schemas • Use the full power of HP Vertica SQL and Analytics DEV & DATA TOOLS Provision, Manage & Monitor DATA SYSTEM APPLICATIONS OPERATIONAL TOOLS INFRASTRUCTURE HDP 2.1 Governance & Integration Security Operations Data Access Data Management Business Analy4cs Custom Applica4ons Packaged Applica4ons REPOSITORIES Build & Test On Premise or in the Cloud SOURCES OLTP, ERP, CRM Systems Documents, Emails Web Logs, Click Streams Social Networks Machine Generated Sensor Data Geoloca>on Data
  • 19. Flexible Vertica Hadoop Connectivity Leverage existing tools in shared Vertica and Hadoop storage environment HDP 2.1 Hortonworks Data Platform HCatalog Connector Hadoop Connector webHCAT webHDFS ANSI SQL webHDFS Page 19 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Provision, Manage & Monitor Ambari Zookeeper Scheduling Oozie Data Workflow, Lifecycle & Governance Falcon Sqoop Flume NFS WebHDFS BATCH, INTERACTIVE & REAL-TIME SECURITY DATA ACCESS YARN: Data Operating System DATA MANAGEMENT GOVERNANCE & INTEGRATION Authentication Authorization Accounting Data Protection Storage: HDFS Resources: YARN Access: Hive, … Pipeline: Falcon Cluster: Knox OPERATIONS Script Pig Search Solr SQL Hive HCatalog NoSQL HBase Accumulo Stream Storm 1 ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° ° N HDFS (Hadoop Distributed File System) In-Memory Spark TezTez Batch Map Reduce Storage Tiering HDFS Connector External Tables and Copy
  • 20. Data Tiering and Cost Optimization Tier-off older data Cool Cold Hot Dark Data © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 20 without notice. Value Discovery Interactive Data Frequently queried Vertica data cache Batch Data Archive Data Serve Convert data to Vertica storage format Explore Any format Store Location Format Any format
  • 21. More than 140 Characters JSON Record-Unstructured Data {"filter_level":"medium","contributors":null,"text":“Listening to Meg Whitman talk about the New Style of IT at #HPDiscover","geo":null,"retweeted":false,"in_reply_to_screen_name":null,"truncated":false, "lang":"en","entities":{"symbols":[],"urls":[],"hashtags":[{"text":"nope","indices":[51,56]}], "user_mentions": []},"in_reply_to_status_id_str":null,"id":346104750565097474,"source":"! <a href="http://twitter.com/download/iphone" rel="nofollow">Twitter for iPhone</a>", "in_reply_to_user_id_str":null,"favorited":false,"in_reply_to_status_id":null,"retweet_count": 0,"created_at":“Tue Jun 11 03:19:37 +0000 2013","in_reply_to_user_id":null, "favorite_count":0,"id_str": "346104750565097474","place":null,"user": {"location":"","default_profile":false,"profile_background_tile":true,"statuses_count": 2354,"lang":"en","profile_link_color":"FF0000","profile_banner_url":"https://pbs.twimg.com/profile_banners/ 271588683/1370571522","id":271588683,"following":null,"protected":false,"favourites_count": 121,"profile_text_color":"3D1957","description":"Dance It is a part of me A part of who I am It has entered my life Taken over my body It is in my walk In my movements In my thoughts I have become a DANCER","verified":false,"contributors_enabled": false,"profile_sidebar_border_color":"65B0DA","name":"ashley tousignant", "profile_background_color":"642D8B","created_at": "Thu Mar 24 20:25:59 +0000 2011","default_profile_image":false,"followers_count":434,"profile_image_url_https":"https://si0.twimg.com/ profile_images/3765534455/ eee814d484d70b8eb9ca5db08a122cbb_normal.jpeg","geo_enabled":true,"profile_background_image_url":"http:// a0.twimg.com/images/themes/theme10/bg.gif","profile_background_image_url_https":"https://si0.twimg.com/images/ themes/theme10/ bg.gif","follow_request_sent":null,"url":null,"utc_offset":null,"time_zone":null,"notifications":null,"profile_u se_background_image":true,"friends_count": 844,"profile_sidebar_fill_color":"7AC3EE","screen_name":"01ashleymt","id_str":"271588683","profile_image_url":"h ttp://a0.twimg.com/profile_images/3765534455/eee814d484d70b8eb9ca5db08a122cbb_normal.jpeg","listed_count": 0,"is_translator":false},"coordinates":null}! ! © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change 21 without notice.
  • 22. HP Vertica Flex Zone Avoid creating and maintaining time-consuming schemas Faster SQL querying Auto-schematization Flexible parsers © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 22 on semi-structured data semi-structured data loading for JSON and delimited data One-step schema for blazing-fast performance Load, manage, and explore semi-structured data
  • 23. Major Computer Products Manufacturer © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 23 Analyzing Billions of Clicks Challenge online • Millions of website visitors generate billions of clicks per month • Must store 5 years worth of data to get full value of year-over- year clickstream analysis • Legacy database had sluggish performance – queries took 48 hours after each day’s transactions • Extremely complex website – many pages are generated dynamically creating complex clickstream trails HP Vertica Solution • Queries run in hours or even minutes; 48x – 100x faster • Industry-standard SQL accelerated acceptance and proficiency • Speed of HP Vertica allows iterative and recursive analysis for deeper dives • Functionality tailored to individual interactions based on nuanced understanding of user behavior at an individual level
  • 24. Next steps… More about HP Vertica & Hortonworks http://hortonworks.com/partner/HP/ Download the Hortonworks Sandbox Learn Hadoop Build Your Analytic App Try Hadoop 2 Don’t miss our next webinar! HP Converged Systems and Hortonworks Planning for the Impacts of Big Data in the Data Center http://info.hortonworks.com/hpconvergedandhortonworks.html Page 24 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
  • 25. End Page 25 © Hortonworks Inc. 2011 – 2014. All Rights Reserved