The Briefing Room with Dr. Robin Bloor and Cirro Live Webcast on February 11, 2014 Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=0ec1fa381886313cc06d841015c65898 As information ecosystems continue to expand, businesses are searching for ways to combine traditional analytics with a new source of insight: Big Data. But with data flooding in from all kinds of sources, fast access and performance at scale can easily become an issue. One effective approach for solving this challenge is data federation, a method that involves taking the analytical processing to the data, allowing streamlined access to multiple data sources without the expensive ETL overhead or building of semantic layers. Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains how the prevalence of distributed data calls for a new approach to Big Data. He will be briefed by Mark Theissen of Cirro, who will tout his company’s Data Hub, a data federation solution that provides a single point of access to all enterprise data assets without excessive data movements, preprocessing or staging. He will discuss how data federation differs from virtualization and ETL approaches, and demonstrate how a Cirro deployment solves the analytics challenge of integrating data silos across the data center – and the cloud – using the BI tools you already have on your desktop for real-time distributed analytics. Visit InsideAnlaysis.com for more information.

1. Grab some coffee and enjoy
the pre-show banter before
the top of the hour!

2. The New Frontier: Optimizing Big Data Exploration
The Briefing Room

3. Twitter Tag: #briefr
The Briefing Room
Welcome
Host:
Eric Kavanagh
eric.kavanagh@bloorgroup.com
@eric_kavanagh

4. ! Reveal the essential characteristics of enterprise software,
good and bad
! Provide a forum for detailed analysis of today’s innovative
technologies
! Give vendors a chance to explain their product to savvy
analysts
! Allow audience members to pose serious questions... and get
answers!
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Mission

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Topics
This Month: BIG DATA
March: CLOUD
April: BIG DATA
2014 Editorial Calendar at
www.insideanalysis.com/webcasts/the-briefing-room

6. The Age of
Exploration
The Age of
DATA

7. Twitter Tag: #briefr
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Analyst: Robin Bloor
Robin Bloor is
Chief Analyst at
The Bloor Group
robin.bloor@bloorgroup.com
@robinbloor

8. Twitter Tag: #briefr
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Cirro
! Cirro provides a single method to access any type of data,
on any platform, in any environment
! Its product suite consists of Cirro Data Hub, Analyst for
Excel and Multi Store – all designed to remove complexity
from Big Data analytics
! Cirro’s products are cloud based and can run in public,
private and on-premise environments

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The Briefing Room
Guest: Mark Theissen
Mark is CEO at Cirro. He is a respected analytics and data
warehousing expert with more than 22 years in the industry.
Most recently Mark was the worldwide data warehousing
technical lead at Microsoft following the acquisition of
DATAllegro. At DATAllegro Mark was the COO and a member
of the board of directors. Prior to joining DATAllegro, Mark
was Vice President and Research Lead at META Group
(Gartner Group) for Enterprise Analytics Strategies, covering data warehousing,
business intelligence and data integration markets. Before META, Mark was VP
of Professional Services at Accruent where he was responsible for domestic and
overseas services and operations. Mark has a BS in Computer Information
Systems from Chapman University and a MBA from the University of California,
Irvine.

10. Briefing Room 2/11/14
Next
Genera*on
Data
Federa*on

11. On Demand Distributed Analysis
Cirro is the ONLY Solution that can:
• Access any data
• On any platform
• Without ETL or the cost and complexity of a
semantic layer
“
What
used
to
take
2-­‐4
weeks
is
now
done
in
a
ma;er
of
minutes.
Cirro
is
a
‘game-­‐
changing’
approach
to
visualizing
mul*-­‐
structured
big
data
and
integra*ng
it
with
other
data
sources.”
Director
of
Business
Intelligence
©2014 Cirro Inc. All rights reserved.

12. Cirro
Data Hub
©2014 Cirro Inc. All rights reserved.
Cirro Enterprise Data Hub
Visualization
Tools
Real-time
Federation
Data
Language
Translation
Data
Movement &
Management
RDBMS
HDFS
NoSql
Legacy
BI
Tools
CLI
Excel
SaaS

13. ©2014 Cirro Inc. All rights reserved.
How Federation Works
I
have
a
table
on
SQL
Server
that
needs
to
join
to
tables
on
Oracle
and
Hadoop

14. ©2014 Cirro Inc. All rights reserved.
How Federation Works
I
have
a
table
on
SQL
Server
that
needs
to
join
to
tables
on
Oracle
and
Hadoop
Oracle
Hadoop
SQL
Server
SQL
predicates,
local
joins
SQL
predicates
Standard
SQL
Row
processing
pushed
into
data
systems
MapReduce

15. ©2014 Cirro Inc. All rights reserved.
How Federation Works
I
have
a
table
on
SQL
Server
that
needs
to
join
to
tables
on
Oracle
and
Hadoop
Oracle
Hadoop
SQL
Server
SQL
predicates,
local
joins
SQL
predicates
Standard
SQL
Row
processing
pushed
into
data
systems
MapReduce
50k
Rows
50m
Rows
5k
Rows

16. ©2014 Cirro Inc. All rights reserved.
How Federation Works
I
have
a
table
on
SQL
Server
that
needs
to
join
to
tables
on
Oracle
and
Hadoop
Oracle
Hadoop
SQL
Server
SQL
predicates,
local
joins
SQL
predicates
Standard
SQL
Row
processing
pushed
into
data
systems
MapReduce
50k
Rows
50m
Rows
5k
Rows
Limited
movement
Limited
movement

17. ©2014 Cirro Inc. All rights reserved.
How Federation Works
I
have
a
table
on
SQL
Server
that
needs
to
join
to
tables
on
Oracle
and
Hadoop
Oracle
Hadoop
SQL
Server
SQL
join,
aggregaEon
Standard
SQL
Row
processing
pushed
into
data
systems

18. ©2014 Cirro Inc. All rights reserved.
How Federation Works
I
have
a
table
on
SQL
Server
that
needs
to
join
to
tables
on
Oracle
and
Hadoop
Results
Des)na)on
Op)ons
Oracle
Hadoop
SQL
Server
Results
Standard
SQL
Row
processing
pushed
into
data
systems
UI
Tools
Data
Marts;
in
the
Cloud
or
Data
Center
BI
Server

19. ©2014 Cirro Inc. All rights reserved.
Completing The Solution…
• Cirro Data Hub – Federated query
processing
• Use any tool
• The fastest distributed
processing possible
• Cirro Analyst
• Data discovery
• Mash up data like never before
• Go beyond SQL
• Publish
• Cirro Multi Store
• Stage, Store, Process
• Highly scalable

20. Next Generation Data Federation
Ask Questions You Couldn’t Ask Before
• Designed & Built for Big Data
• Compatible with structured, semi-structured & unstructured data
• Works in the cloud, in the data center, or both
©2014 Cirro Inc. All rights reserved.
• Real-Time Federation
• Queries are dynamically optimized and executed, taking the
processing to the data
• Enables ad-hoc query and exploration of all data
• No Semantic Layer Required

21. Cirro Federation vs. Data Virtualization
Cirro
Data
Virtualiza)on
©2014 Cirro Inc. All rights reserved.
• Excellent
for
data
exploraEon
and
discovery
• Excellent
for
ad-­‐hoc
queries
• True
federated
processing
–
minimal
data
movement,
no
server
boPlenecks
–
‘pushes
processing
to
the
data’
• Easy
setup,
maintenance
&
administraEon
• Hadoop
–
can
execute,
Hive
&
Impala
queries
along
with
MapReduce
programs
• Pathway
to
NoSQL
• Not
appropriate
for
data
exploraEon
or
discovery
–
requires
you
to
know
the
quesEons
you
want
to
ask
in
advance
of
accessing
the
data
• Not
true
federated
processing
–
final
joins
and
aggregaEons
done
on
VirtualizaEon
Server
• Good
for
structured
data
processing
workloads
• Labor
intensive
setup,
maintenance
&
administraEon
for
modeling
and
semanEc
layer
• Hadoop
–
limited
to
Hive
access

22. Data Federation Use Cases
• On Demand Distributed Data Analysis
• Data warehouse offloading
• Business intelligence federation
• Self-service data exploration and discovery
• Entry point for private cloud analytics
• SaaS, Hadoop and/or NoSQL integration with
enterprise data sources
• Simplify application development
©2014 Cirro Inc. All rights reserved.

23. On Demand Intra-Day Analytics
Solution
• Cirro Data Hub; Cirro Analyst
Results
• On demand analytics supports faster
trend analysis and the ability to identify
data anomalies
• Cross-platform data access reduced
from weeks to minutes
• Flexible/iterative using in-house BI tools
• Enables self-service data mash-ups by
analysts across all data sources
©2014 Cirro Inc. All rights reserved.
Business Challenge
• Data that drives trading analytics &
decisions in data silos
• Inability to analyze data ‘fast enough’ to
make informed trading decisions
• ETL tools and manual data consolidation is
too slow and inflexible for hourly or daily
iterative analysis
• Inability to join traditional data with cloud
sources
Financial
&
Energy
/
UElity
Markets

24. Ask Questions You Couldn’t Ask Before
Last Market Price
©2014 Cirro Inc. All rights reserved.
Oracle - Pricing DW
Transaction Data
Tableau
Actionable Visualizations
Subscrip)on
Market
Data

25. Ask Questions You Couldn’t Ask Before
©2014 Cirro Inc. All rights reserved.
A
Anonymous Behavior
Transactional Data
Ads viewed/clicked
Actionable
Visualizations

26. ©2014 Cirro Inc. All rights reserved.
The Business Impact
• Agility;
conducEng
analysis
previously
unavailable
• CompeEEve
advantage
• Supports
ad-­‐hoc
analysis
,
Fastest
Eme
to
value
• Leverage
in-­‐house
BI
tools
–
no
new
tools
to
learn
Improved
Business
OperaEons
• TradiEonal
architectures
not
designed
for
Big
Data
• Easily
add
new
data
sources
–
RDBMS,
Hadoop,
NoSQL
• Easy
to
install,
use
&
manage
• Future
proof
analyEcs
developed
Streamline
IT
Processes
• ReducEon
in
license
costs
on
EDW
and
RDBMS
• Time
&
cost
savings
associated
with
data
staging,
modeling,
ETL
work,
etc.
• No
new
BI
applicaEons
to
buy
-­‐
use
exisEng
BI
tools
• No
new
skills
to
develop
Cost
Savings

27. Twitter Tag: #briefr
The Briefing Room
Perceptions & Questions
Analyst:
Robin Bloor

29. The Visible “Big Data” Trend
u Corporate data volumes
grow at about 55% per
annum - exponentially
u Data has been growing at
this rate for, maybe, 40
years
u There is nothing new
about big data; it clings to
an established exponential
trend

30. The Invisible Trend: Moore’s Law Cubed
u The biggest databases are new
databases
u They grow at the cube of Moore’s
Law
u Moore’s Law = 10x every 6 years
u VLDB: 1000x every 6 years
• 1991/2 megabytes
• 1997/8 gigabytes
• 2003/4 terabytes
• 2009/10 petabytes
• 2015/16 exabytes

31. Whys and Wherefores?
u Why do we assemble such gargantuan heaps of
data?
u While the data volume has grown like bamboo
in spring, the size of executables has not?
u Why not just move the processing to the data?
u This is surely an option worth exploring – maybe
it is even one of the foundations for Big Data
Architecture…

32. No Country for Old DBMS (Thinking)

33. Questions are Easy, Answers Difficult
The
WORKLOAD
Conundrum
The
DISTRIBUTION
Conundrum
The DATA
FLOW
Conundrum
The REAL-TIME
Conundrum

34. u What are the primary applications where Cirro
makes a big impact?
u What is (roughly) the largest number of data
sources Cirro federates in any implementation?
u What’s the most resource deployed for the
largest Cirro implementation? How much
memory?
u How does “fault tolerance” work?

35. u How difficult is it to develop applications
employing Cirro? Is it significantly different to a
DBMS?
u Are any companies adopting this technology
strategically?
u Which technologies/companies do you regard as
competition?

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37. This Month: BIG DATA
March: CLOUD
April: BIG DATA
www.insideanalysis.com/webcasts/the-briefing-room
Twitter Tag: #briefr
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Upcoming Topics
2014 Editorial Calendar at
www.insideanalysis.com

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THANK YOU
for your
ATTENTION!
The Briefing Room

39. Photo credit for Slide 28:
Lenny’s Alice in Wonderland site: http://www.alice-in-wonderland.net/
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