1. Unlock the power of Hadoop
to enable interactive analytics
& real-time Business Intelligence July 10, 2013

2. Web Briefing:
Unlock the power of Hadoop
to enable interactive analytics
• Thank you for joining today’s session!
• The web briefing will start momentarily.
• We will use the WebEx Q & A feature
Today’s Slides are available at www.slideshare.net/kognitio
@Hortonworks
@Kognitio
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3. Unlock the power of Hadoop
to enable interactive analytics
July 10, 2013
Demonstration: SQL and Hadoop with in‐memory
MPP Acceleration ‐ Stuart Watt
Hadoop meets Mature BI: Interactive Analytics
‐ Michael Hiskey
Modern Data Architectures
‐ John Kriesa
Web Briefing Agenda

4. © Hortonworks Inc. 2013
Modern Data Architectures
Big data drivers and patterns
John Kreisa – VP Strategic Marketing, Hortonworks
@marked_man

5. © Hortonworks Inc. 2013
Existing Data ArchitectureAPPLICATIONSDATA SYSTEMS
TRADITIONAL REPOS
RDBMS EDW MP
P
DATA SOURCES
OLTP,
POS
SYSTEMS
OPERATIONAL
TOOLS
MANAGE &
MONITOR
Traditional Sources
(RDBMS, OLTP, OLAP)
DEV & DATA
TOOLS
BUILD &
TEST
Business
Analytics
Custom
Applications
Enterprise
Applications
Page 5

6. © Hortonworks Inc. 2013
6 Common Types of Hadoop Data
1. Sentiment
Understand how your customers feel about your brand and
products – right now
2. Clickstream
Capture and analyze website visitors’ data trails and
optimize your website
3. Sensor/Machine
Discover patterns in data streaming automatically from
remote sensors and machines
4. Geographic
Analyze location-based data to manage operations where
they occur
5. Server Logs
Research logs to diagnose process failures and prevent
security breaches
6. Unstructured (txt, video, pictures, etc..)
Understand patterns in text across millions of web pages,
emails, and documents
Value
Page 6

7. © Hortonworks Inc. 2013
Next-Generation Data Architecture
Page 7
APPLICATIONSDATA SYSTEMS
Microsoft Applications
DATA SOURCES
Traditional Sources
(RDBMS, OLTP, OLAP)
In‐memory MPP Accelerator
BI Tools & OLAP Clients
TRADITIONAL REPOS
RDBMS EDW MPP
OPERATIONAL
TOOLS
MANAGE &
MONITOR
DEV & DATA
TOOLS
BUILD &
TEST
New Sources
(web logs, email, sensors, social media)
HORTONWORKS
DATA PLATFORM

8. © Hortonworks Inc. 2013
Interoperating With Your Data Tools
Page 8
APPLICATIONSDATA SYSTEMS
Microsoft Applications
DATA SOURCES
Traditional Sources
(RDBMS, OLTP, OLAP)
In‐memory MPP Accelerator
HORTONWORKS
DATA PLATFORM
OPERATIONAL
TOOLS
Viewpoint
DEV & DATA
TOOLS
TRADITIONAL REPOS
New Sources
(web logs, email, sensors, social media)

9. © Hortonworks Inc. 2013
Big Data
Transactions, Interactions, Observations
Hadoop Common Patterns of Use
Business Cases
HORTONWORKS
DATA PLATFORM
Refine Explore Enrich
Batch Interactive Online
“Right-time” Access to Data
Page 9

10. © Hortonworks Inc. 2013
Data SystemsApplicationsSources
Infrastructure ‐ Data Lake
Modern Data Architecture
Hadoop as a Shared Data Lake
TRADITIONAL REPOS
RDBMS EDW MPP
Custom
Analytic App
New Sources
(logs, clicks, social media, sensors)
Packaged
Analytic App
Traditional Sources
(RDBMS, OLTP, OLAP)
• A more mature
organization will have
this as a goal for Hadoop
ENTERPRISE
HADOOP
PLATFORM
Page 10
• Store all data and
build/enable applications
on shared “data lake”
• Delivers broad value
across the enterprise
In‐memory MPP Accelerator
HORTONWORKS
DATA PLATFORM
• Seamless SQL access
with interactive analytics

11. © Hortonworks Inc. 2013
Data SystemsApplicationsSources
Hadoop for New Targeted Applications
TRADITIONAL REPOS
RDBMS EDW MPP
New Sources
(logs, clicks, social media, sensors)
Packaged
Analytic App
Traditional Sources
(RDBMS, OLTP, OLAP)
ENTERPRISE
HADOOP
PLATFORM
Business Application
Catalyst: Type of Data
Custom
Analytic App
In‐memory MPP Accelerator
HORTONWORKS
DATA PLATFORM
• Many organizations start
here & expand usage
• Driven by a type of data
that was not capable of
analysis before Hadoop
• Delivers explicit value for
a business case or an
individual LOB
• Complementary to
existing applications that
use SQL
• Interactive analytics with
MPP in-memory
execution of R, Python,
Perl, etc.

12. © Hortonworks Inc. 2013
OS Cloud VM Appliance
HDP: Enterprise Hadoop Distribution
Page 12
PLATFORM
SERVICES
HADOOP
CORE
Enterprise Readiness
High Availability, Disaster Recovery,
Security and Snapshots
HORTONWORKS
DATA PLATFORM (HDP)
OPERATIONAL
SERVICES
DATA
SERVICES
HIVE &
HCATALOG
PIG HBASE
OOZIE
AMBARI
HDFS
MAP REDUCE
Hortonworks
Data Platform (HDP)
Enterprise Hadoop
• The ONLY 100% open source
and complete distribution
• Enterprise grade, proven and
tested at scale
• Ecosystem endorsed to
ensure interoperability
SQOOP
FLUME
NFS
LOAD &
EXTRACT
WebHDFS

13. Hadoop meets Mature
BI: Interactive Analytics
Michael Hiskey
VP of Marketing & Business Development
@mphnyc

14. Mature Business Intelligence and Reporting
Numbers, tables, charts, indicators
…accessed with ease and simplicity
Historical information, latency
BI tools have plateaued
Decision Support
Advanced analytics and data science
More math…a lot more math

15. Drive for a deeper level of understanding
Dynamic
Simulation
Statistical
Analysis
Behavior
modellingReporting
Fraud
detection
create external script LM_PRODUCT_FORECAST environment rsint
receives ( SALEDATE DATE, DOW INTEGER, ROW_ID INTEGER, PRODNO INTEGER, DA
partition by PRODNO order by PRODNO, ROW_ID
sends ( R_OUTPUT varchar )
isolate partitions
script S'endofr( # Simple R script to run a linear fit on daily sales
prod1<-read.csv(file=file("stdin"), header
colnames(prod1)<-c("DOW","ID","PRODNO","DA
dim1<-dim(prod1)
daily1<-aggregate(prod1$DAILYSALES, list(D
daily1[,2]<-daily1[,2]/sum(daily1[,2])
basesales<-array(0,c(dim1[1],2))
basesales[,1]<-prod1$ID
basesales[,2]<-(prod1$DAILYSALES/daily1[pr
colnames(basesales)<-c("ID","BASESALES")
fit1=lm(BASESALES ~ ID,as.data.frame(bases
forecast<-array(0,c(dim1[1]+28,4))
colnames(forecast)<-c("ID","ACTUAL","PREDI
select Trans_Year, Num_Trans,
count(distinct Account_ID) Num_Accts,
sum(count( distinct Account_ID)) over (partition by Trans_Year order by Num_Tran
cast(sum(total_spend)/1000 as int) Total_Spend,
cast(sum(total_spend)/1000 as int) / count(distinct Account_ID) Avg_Yearly_Spend
rank() over (partition by Trans_Year order by count(distinct Account_ID) desc) R
rank() over (partition by Trans_Year order by sum(total_spend) desc) Rank_by_Tot
from( select Account_ID,
Extract(Year from Effective_Date) Trans_Year,
count(Transaction_ID) Num_Trans,
sum(Transaction_Amount) Total_Spend,
avg(Transaction_Amount) Avg_Spend
from Transaction_fact
where extract(year from Effective_Date)<2009
and Trans_Type='D'
and Account_ID<>9025011
and actionid in (select actionid from DEMO_FS.V_FIN_actions
where actionoriginid =1)
group by Account_ID, Extract(Year from Effective_Date)
) Acc_Summary
group by Trans_Year, Num_Trans
order by Trans_Year desc, Num_Trans;
select dept, sum(sales)
from sales_fact
Where period between date ‘01-05-2006’ a
group by dept
having sum(sales) > 50000;
select sum(sales)
from sales_history
where year = 2006 and month = 5 and regi
select total_sales
from summary
where year = 2006 and month = 5 and regi

16. The Analytical Enterprise
Business
Analyst
Systems
Admin
Data
Scientist
Sexiest job of the 21st Century?
Key: “Graduation”
• Projects will need to easily Graduate
from the Data Science Lab and
become part of Business as Usual

17. Your goal:
PRESS HERE
…and really cool Big Data stuff happens!

18. Big Data: Bring the Analytics TO the Data
Kognitio Hadoop Integration
• Kognitio Map/Reduce Agent uploads itself to
Hadoop nodes
• Query passes selections, relevant predicates
• Data filtering & projection locally on each node
• Data filtered as it is read from file(s)
• Only data of interest is transferred and loaded
into memory via parallel load streams

19. Demonstration:
SQL &Hadoop with in‐memory
MPP Acceleration
Stuart Watt
Senior Systems Engineer
@Kognitio

20. © Hortonworks Inc. 2013
Hortonworks Snapshot
• We distribute the only 100%
Open Source Enterprise
Hadoop Distribution:
Hortonworks Data
Platform
• We engineer, test & certify
HDP for enterprise usage
• We employ the core
architects, builders and
operators of Apache Hadoop
• We drive innovation within
Apache Software
Foundation projects
• We are uniquely positioned
to deliver the highest quality
of Hadoop support
• We enable the ecosystem to
work better with Hadoop
Develop Distribute Support
We develop, distribute and support
the ONLY 100% open source
Enterprise Hadoop distribution
Endorsed by Strategic Partners
Headquarters: Palo Alto, CA
Employees: 200+ and growing
Investors: Benchmark, Index, Yahoo,
Tenaya, Dragoneer

21. Kognitio Snapshot: Mature SQL atop Hadoop
Kognitio is an in‐memory
analytical platform that is tightly
integrated with Hadoop for high‐
performance advanced analytics
that make Big Data more
consumable for enterprises,
especially those with mature BI
environments or engrained
tools.
• Privately held
• Invented the in‐memory analytical platform
• Labs in the UK ‐ HQ in New York, NY
• Powering advanced analytics at
organizations worldwide, such as:

22. © Hortonworks Inc. 2013
Interactive analytics with Hadoop:
Getting Started
• Assess your environment and use case for Hortonworks Data Platform
+ Kognitio Analytical Platform www.kognitio.com/hadoop
Download Hortonworks Sandbox
www.hortonworks.com/sandbox
Sign up for Training for in-depth learning
hortonworks.com/hadoop-training/
ZERO to big data in 15 minutes:
Request a Meeting
Download the Kognitio Analytical Platform
• No registration required
• Perpetual license - No time limits
www.kognitio.com/free

23. Question & Answer session will be conducted electronically,
using the panel to the right of your screen
Today’s Slides available at: www.slideshare.net/kognitio
Download Hortonworks Sandbox
www.hortonworks.com/sandbox
Download the Kognitio Analytical Platform
• No registration required
• Perpetual license - No time limits
www.kognitio.com/free
Unlock the power of Hadoop to
enable interactive analytics
Request a Meeting
www.kognitio.com/hadoop

24. connect
www.kognitio.com
twitter.com/kognitiolinkedin.com/companies/kognitio
tinyurl.com/kognitio youtube.com/kognitio
+1 855 KOGNITIO

25. © Hortonworks Inc. 2013
Hortonworks Sandbox
Fastest onramp to Apache Hadoop
• What is it?
– Free, virtualized single-node version of Hortonworks Data Platform
– A personal Hadoop environment
– An integrated learning environment with hands-on step-by-step tutorials
• What it does?
– Dramatically accelerates the process of learning Apache Hadoop
– Accelerates & validates the use of Hadoop within your unique data
architecture
– Use your data to explore and investigate your use cases
• ZERO to big data in 15 minutes
• Get Started!
Page 25
Download Hortonworks Sandbox
www.hortonworks.com/sandbox
Sign up for Training for in-depth learning
hortonworks.com/hadoop-training/