Hadoop is changing how businesses operate, learn about this emerging technology stack. View the webinar video recording and download this deck: http://www.senturus.com/resource-video/hadoop-future-sql/?rId=3410. Learn the role SQL queries play for big data, and how SQL-on-Hadoop technologies enable organizations to leverage their existing SQL skills and investments in business intelligence (BI) tools to dramatically improve: 1) Recommendation engines for online retail, 2) Transactional fraud prevention for financial services, 3) Customized advertising and 4) Predictive failure analytics for manufacturing. Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.

1. Using BI Tools with Big Data
HADOOPANDTHEFUTUREOFSQL

2. questions
here
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www.senturus.com/resources/hadoop-future-sql/
Hear the Recording

3. Resource Library
Senturus’ whole purpose is to make you successful with Business Analytics. Thus, we offer a series of technology-neutral webinars, training on specific software, demonstrations, and no-holds-barred reviews of new software releases. We host dozens of live webinars every year and we offer a comprehensive library of recorded webinars, demos, white papers, presentations and case studies on our website-- a wealth of learning resources. Most of our content is custom created and constantly updated, so visit us often to see what’s new in the industry.
www.senturus.com/resources/
3
Copyright 2014 Senturus, Inc. All Rights Reserved

4. •Welcome and Introduction
•Hadoopand the Future of SQL
•More Resources
•Q&A
AGENDA
Copyright 2014 Senturus, Inc. All Rights Reserved
4

5. John Peterson
CEO & Co-Founder
Senturus
Introduction: Today’s Presenters
Copyright 2014 Senturus, Inc. All Rights Reserved
5
Jack Norris
Chief Marketing Officer
MapR

6. Who we are
SENTURUSINTRODUCTION

7. Senturus: Business Analytics Consultants
7
Copyright 2014 Senturus, Inc. All Rights Reserved
BusinessIntelligence
Enterprise
Planning
Predictive
Analytics
Our Team:
Business depth combined with technical expertise. Former CFOs, CIOs, Controllers, Directors

8. 800+ Clients, 1400+ Projects, 14 Years
8
Copyright 2014 Senturus, Inc. All Rights Reserved

9. HADOOPANDTHEFUTUREOFSQL
9
Copyright 2014 Senturus, Inc. All Rights Reserved

10. questions
here
Copyright 2014Senturus,Inc.
AllRightsReserved
Hear the Recording
This slide deck is part of a recorded webinar. To view the FREE recording of the entire presentation and download the slide deck go to
www.senturus.com/resources/hadoop-future-sql/
Senturus’ comprehensive library of recorded webinars, demos, white papers, presentations and case studies is available on our website.
www.senturus.com

11. © 2014 MapR Technologies 11
MapR Overview
BIG
DATA
BEST
PRODUCT
BUSINESS
IMPACT
Hadoop
Top Ranked
Production
Success

12. © 2014 MapR Technologies 12
 YouTube users upload 48 hours of new video every minute of the day
 Twitter has 175 million tweets/day, with more than 465 million accounts
Big Data In Our World
Variety
Velocity
Volume
 Facebook stores, accesses, and analyzes 30+ petabytes of user generated data
 5 billion people calling, texting, tweeting & browsing on mobile phones worldwide
 2.7 zetabyes data exist in the digital universe today
 Data production will be 44 times greater in 2020 than it was in 2009
More Data
More Users
Interactive Apps

13. © 2014 MapR Technologies 13
Say
BIG DATA
one more
time...

14. © 2014 MapR Technologies 14
Difficult to Leverage Data with Traditional Systems
• Mission-critical reliability
• Transaction guarantees
• Deep security
• Real-time performance
• Backup and recovery
• Interactive SQL
• Rich analytics
• Workload management
• Data governance
• Backup and recovery
Enterprise
Data
Architecture
TREND 2
ENTERPRISE
USERS
OPERATIONAL
SYSTEMS
ANALYTICAL
SYSTEMS
PRODUCTION
REQUIREMENTS
PRODUCTION
REQUIREMENTS
OUTSIDE SOURCES

15. © 2014 MapR Technologies 15
Hadoop: The Disruptive Technology at the TREND 3 Core of Big Data
JOB TRENDS FROM INDEED.COM
Jan „06 Jan „07 Jan „08 Jan „09 Jan „10 Jan „11 Jan „12 Jan „13 Jan „14

16. © 2014 MapR Technologies 16
Hadoop: Distributed Compute on Data

17. questions
here
Copyright 2014Senturus,Inc.
AllRightsReservedHear the Recording
This slide deck is part of a recorded webinar. To view the FREE recording of the entire presentation and download the slide deck go to
www.senturus.com/resources/hadoop-future-sql/
Senturus’ comprehensive library of recorded webinars, demos, white papers, presentations and case studies is available on our website.
www.senturus.com

18. © 2014 MapR Technologies 18
The Hadoop Advantage
BIG DATA
HADOOP
Data on
compute
Simple
algorithms on
Big Data
unstructured
data

19. © 2014 MapR Technologies 19
Economics: Hadoop Just Makes Sense
Data
IT Budgets
• Gartner, "Forecast Analysis: Enterprise IT Spending by Vertical Industry Market, Worldwide, 2010-2016, 3Q12 Update.“
• Wall Street Journal, “Financial Services Companies Firms See Results from Big Data Push”, Jan. 27, 2014
$9,000
$40,000
<$1,000
2013
ENTERPRISE
STORAGE
IT BUDGETS
GROWING AT 2.5%
2014 2015 2016 2017
DATABASE
WAREHOUSE
DATA GROWING
AT 40%
$ PER TERABYTE
IT budgets can’t keep up growing data

20. © 2014 MapR Technologies 20
Fortune 100 Retailer

21. © 2014 MapR Technologies 21

22. © 2014 MapR Technologies 22
Production Hadoop in Waste Management

23. © 2014 MapR Technologies 23
What is Driving the Need for SQL-on-Hadoop?
Organizations are looking to
• Reuse existing tools and skills to unlock Hadoop data to broader
audiences
• Analysis on new types of data
• More complete data analysis
• More up-to-date and real-time data analysis
(not just “after the fact”)

24. © 2014 MapR Technologies 24
Real-World Data Modeling and Transformations

25. © 2014 MapR Technologies 25
Distance to Data
Business
(analysts, developers)
“Plumbing”
development
MapReduce
Business
(analysts, developers)
Modeling and
transformations
Hive and other
SQL-on-Hadoop
Existing approaches
require a middleman (IT)
Data
Data

26. © 2014 MapR Technologies 27
Distance to Data
Business
(analysts, developers)
“Plumbing”
development
MapReduce
Hive and other
SQL-on-Hadoop
Business
Data Agility (analysts, developers)
Existing approaches
require a middleman (IT)
Data
Data
Data
Business
(analysts, developers)
Modeling and
transformations

27. © 2014 MapR Technologies 28
Why Improve Distance to Data?
• Enable rapid data exploration and
application development
• IT should provide a valuable
service without “getting in the way”
• Can‟t add DBAs to keep up with
the exponential data growth
• Minimize “unnecessary work” so IT
can focus on value-added
activities and become a partner to
the business users
Improve time to value Redu2ce the burden on IT

28. questions
here
Copyright 2014Senturus,Inc.
AllRightsReserved
Hear the Recording
This slide deck is part of a recorded webinar. To view the FREE recording of the entire presentation and download the slide deck go to
www.senturus.com/resources/hadoop-future-sql/
Senturus’ comprehensive library of recorded webinars, demos, white papers, presentations and case studies is available on our website.
www.senturus.com

29. © 2014 MapR Technologies 30
• Pioneering Data Agility for Hadoop
• Apache open source project
• Scale-out execution engine for low-latency queries
• Unified SQL-based API for analytics & operational applications
APACHE DRILL
40+ contributors
150+ years of experience building
databases and distributed systems

30. © 2014 MapR Technologies 31
Rethink SQL for Big Data
• ANSI SQL
– Ubiquitous
• Familiar
– No context switch BI/Analytics
• One technology
– Painful to manage different
technologies
• Enterprise ready
– System-of-record,
HA, DR, Security, multi-tenancy,
…
• Flexible data-model
– Allow schemas to evolve rapidly
– Support semi-structured data
types
• Agility
– Self-service possible when
developer and DBA is same
• Scalability
– In all dimensions: schemas,
processes, management
Preserve Invent

31. © 2014 MapR Technologies 32
YOU CAN’T HANDLE REAL SQL!

32. © 2014 MapR Technologies 33
SQL
select * from A
where A.a in (select B.b from B
where B.b = A.c);
Did you know Apache HIVE cannot compute this query?
– e.g. Hive, Impala, Spark SQL

33. © 2014 MapR Technologies 34
Semi-structured Data
select cf.month, cf.year
from hbase.table1;
• Of course you know an RDBMS cannot handle this query?
– Nor can HIVE and its variants like Impala, Spark SQL
• There‟s no meta-store definition available

34. © 2014 MapR Technologies 35
(1) Drill Supports Schema Discovery On-The-Fly
• Fixed schema
• Leverage schema in centralized
repository (Hive Metastore)
• Fixed schema, evolving schema or
schema-less
• Leverage schema in centralized
repository or self-describing data
Schema Declared In Advance Schema2 Discovered On-The-Fly
SCHEMA ON
WRITE
SCHEMA
BEFORE READ
SCHEMA ON THE
FLY

35. © 2014 MapR Technologies 36
Zero to Results in 2 Minutes (3 Commands)
$ tar xzf apache-drill.tar.gz
$ apache-drill/bin/sqlline -u jdbc:drill:zk=local
0: jdbc:drill:zk=local>
SELECT count(*) AS incidents, columns[1] AS category
FROM dfs.`/tmp/SFPD_Incidents_-_Previous_Three_Months.csv`
GROUP BY columns[1]
ORDER BY incidents DESC;
+------------+------------+
| incidents | category |
+------------+------------+
| 8372 | LARCENY/THEFT |
| 4247 | OTHER OFFENSES |
| 3765 | NON-CRIMINAL |
| 2502 | ASSAULT |
...
35 rows selected (0.847 seconds)
Install
Launch shell
(embedded
mode)
Query
Results

36. questionshereCopyright 2014Senturus,Inc.AllRightsReserved
Hear the Recording
This slide deck is part of a recorded webinar. To view the FREE recording of the entire presentation and download the slide deck go to
www.senturus.com/resources/hadoop-future-sql/
Senturus’ comprehensive library of recorded webinars, demos, white papers, presentations and case studies is available on our website.
www.senturus.com

37. © 2014 MapR Technologies 39
(2) Drill‟s Data Model is Flexible

38. © 2014 MapR Technologies 40
(3) Drill Has ANSI SQL as the Design Center
• Users want “standard” SQL rather than SQL-like (HiveQL)
– Leverage existing expertise
– Better support for BI/DI tools
• Drill will support ANSI SQL
– Extensions to handle complex data
• Current status:
– Drill 0.5 runs 15 of 22 TPC-H queries unmodified
– Impala 1.4 runs 2 of 22 TPC-H queries unmodified

39. © 2014 MapR Technologies 41
The Data-to-Value Pipeline in Organizations
Refining, analyzing, and operationalizing data for competitive advantage
Ad-hoc
Query & Analysis
Why did it happen?
Operational Analytics
Data-driven, automated
business processes
Reporting
What happened?
Data Discovery
What data do we have?
What questions should I ask?
“Modeled”
data
Machine
Generated
Data
Operational
Apps
Relational
Data
Relational
Data

40. © 2014 MapR Technologies 42
The Data-to-Value Pipeline in Organizations
Refining, analyzing, and operationalizing data for competitive advantage
Traditional
SQL & DW Focus
Ad-hoc
Query & Analysis
Why did it happen?
Operational Analytics
Data-driven, automated
business processes
Reporting
What happened?
Data Discovery
What data do we have?
What questions should I ask?
“Modeled”
data
Operational
Data Store
Operational
Apps
Relational
Data
Relational
Data

41. © 2014 MapR Technologies 43
The Data-to-Value Pipeline in Organizations
Refining, analyzing, and operationalizing data for competitive advantage
Current Hadoop SQL Focus
Ad-hoc
Query & Analysis
Why did it happen?
Operational Analytics
Data-driven, automated
business processes
Reporting
What happened?
Data Discovery
What data do we have?
What questions should I ask?
“Modeled”
data
Machine
Generated
Data
Operational
Apps
Relational
Data
Relational
Data

42. © 2014 MapR Technologies 44
The Data-to-Value Pipeline in Organizations
Refining, analyzing, and operationalizing data for competitive advantage
Apache Drill: Enabling SQL Analysis Across Entire Spectrum
Ad-hoc
Query & Analysis
Why did it happen?
Operational Analytics
Data-driven, automated
business processes
Reporting
What happened?
Data Discovery
What data do we have?
What questions should I ask?
“Modeled”
data
Machine
Generated
Data
Operational
Apps
Relational
Data
Relational
Data

43. questionshere
Copyright 2014Senturus,Inc.
AllRightsReserved
Hear the Recording
This slide deck is part of a recorded webinar. To view the FREE recording of the entire presentation and download the slide deck go to
www.senturus.com/resources/hadoop-future-sql/
Senturus’ comprehensive library of recorded webinars, demos, white papers, presentations and case studies is available on our website.
www.senturus.com

44. © 2014 MapR Technologies 46
Advertising
Automation
Cloud
Sellers
Cloud
Buyers
Cloud
100B
AD AUCTIONS
per day

45. © 2014 MapR Technologies 47
Largest Biometric Database in the World
PEOPLE
1.2B
PEOPLE

46. © 2014 MapR Technologies 48
50M
SET-TOP BOXES

47. © 2014 MapR Technologies 49
104M
CARD MEMBERS
Fortune 100 Financial Services Company

48. © 2014 MapR Technologies 50
Summary
• Volume, Variety and Velocity of data requires a new SQL
approach
• The new approach delivers value through operational analytics –
“impacting business as it happens”
• Apache Drill supports the development and implementation of
these operational analytic applications

49. © 2014 MapR Technologies 51
@mapr maprtech
jnorris@mapr.com
Engage with us!
MapR
maprtech
mapr-technologies

50. ADDITIONALRESOURCES
52

51. www.senturus.com
Upcoming Events
53
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52. questions
here
Copyright 2014Senturus,Inc.
AllRightsReserved
Hear the Recording
This slide deck is part of a recorded webinar. To view the FREE recording of the entire presentation and download the slide deck go to
www.senturus.com/resources/hadoop-future-sql/
Senturus’ comprehensive library of recorded webinars, demos, white papers, presentations and case studies is available on our website.
www.senturus.com

53. Thank
You!!
www.senturus.com
888-601-6010
info@senturus.com
Copyright2014bySenturus,
Inc.
ThisentirepresentationiscopyrightedandmaynotbereusedordistributedwithoutthewrittenconsentofSenturus,Inc.