The Briefing Room with Rick Sherman and Actian
Slides from the Live Webcast on Aug. 28, 2012
The appetite for high-powered analytics is greater than ever these days, with increasing numbers of business users clamoring for insights. At the same time, source systems are proliferating, and the nature of questions being asked is getting more complex. Indeed, the entire landscape of analytics is changing in fundamental ways. How can your organization stay ahead of the curve?
Register for this episode of The Briefing Room to learn from veteran Analyst Rick Sherman how a variety of technologies can change the manner in which analytics are done. He'll be briefed by Fred Gallagher of Actian, who will explain how his company's Vectorwise technology leverages vector processing to expedite even the most complex queries when compared to traditional columnar or relational databases.
For more information visit: http://www.insideanalysis.com
3. ! 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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5. ! Analytics has always been about discovering
insights that lead to better business decisions.
! More organizations are demanding faster time-to-
insight, while at the same time expecting
connectivity to and analytics on a wide variety of
data and data sources.
! Clever vendors look for ways to provide solutions
that not only scale at lightening speeds, but
deliver actionable insights.
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6. Robin Bloor is
Chief Analyst at
The Bloor Group.
Robin.Bloor@Bloorgroup.com
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8. Rick Sherman is the founder of Athena IT
Solutions, a Massachussetts-based firm that
provides business intelligence, data
integration & data warehouse consulting,
training and vendor services.
In addition to having more than 20 years of
experience in BI solutions, Rick writes on IT
topics and is a frequent speaker at industry
events.
He blogs at The Data Doghouse and can be
reached at:
rsherman@athena-solutions.com
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9. ! Actian Corporation is a database and software
development company.
! Its premier database platform is Vectorwise, a highly
performant analytic engine that implements
parallelism at every level, from the processor core to
data storage.
! Actian offers a cloud development platform for
building Action Apps, lightweight applications that
automate business actions triggered by real-time
changes in data.
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10. Fred Gallagher is GM, Vectorwise at Actian
Corporation and is responsible for managing the
business activities for this breakthrough product. He
joined Actian in 2006 as vice president of business
development.
Before joining Actian, Fred worked for Qlusters,
where he was responsible for worldwide sales,
marketing, and business development. At Qluster, he
successfully launched the industry's first open source
systems management project. Prior to that, he
worked at VMWare, where he was responsible for
worldwide software alliances, and where he
established 15 successful strategic alliances during a
high-growth period of two years. Previously he was
at Seagate Technology, where he was vice president
of worldwide channels and business development for
Seagate's XIOtech subsidiary. Fred holds Bachelor of
Arts and an MBA from Stanford University.
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11. Briefing Room
August 28
Speakers:
Rick Sherman
Fred Gallagher, General Manager Vectorwise, Actian Corporation
12. Actian Today
• Global
Reach,
Growing
with
Strong
Balance
sheet
• Highly
Profitable
with
strong
Cash
Balances
• 200
employees
across
11
Offices
• World’s
Fastest
Big
Data
Analy5cal
Engine
Vectorwise
• Experiencing
RAPID
GROWTH
• Affordable,
Leverages
Standard
Hardware
and
SoHware
• 10,000+
mission
cri5cal
applica5ons
–
inc
Data
Warehouses
Ingres
• Very
high
client
sa5sfac5on
• S5ll
Innova5ng:
GeoSpa5al
features
• Next
Genera5on
of
Ac5onable
BI
–
Connect
Insight
to
Ac5on
Ac5on
Apps
• Analyzing
Events
and
Data
12
13. But
most
enterprises
s5ll
only
use
1-‐5%
of
their
data
What
if
that
number
doubled,
tripled,
quadrupled…
?
Source:
Forrester
14. Enormous Opportunities for Big Data
$300bn
value
per
year
€250
bn
value
per
$600
bn
value
year
per
year
SOURCE:
McKinsey
Global
InsNtute
analysis
14
15. “Big” Data Management Challenge
Local Data
Data silos, distributed and disparate
!
Existing solutions are not real-time
!
Data in the Cloud
Expensive, inefficient or inflexible
!
Scalability not there
!
15
16. The Need for Speed and Agility
! Business users require interactivity
! Desktop users tolerate 10 to 20 seconds
! Mobile users tolerate 2 to 5 seconds
! Increases in user concurrency
! Take action in “business time”
! Be faster than your competition
! Optimize your business
16
17. Reduce Latency Between Events and Action
Event
Latency
Capture
Value
Latency
Analyze
Informed
decision
ready
Latency
to
be
made
A*ribu/on:
Ac5on
Jean-‐Michel
Franco
of
Business
&
Decision
Time
latencies
17
18. Vectorwise:
Affordable Performance – Proven!
QphH 0
100,000
200,000
300,000
400,000
June
‘12
Vectorwise
445,529
May
‘11
Vectorwise
436,788
Aug
‘11
SQL
Server
219,888
June
‘11
Oracle
209,534
Sept
‘11
Oracle
201,487
Apr
‘11
SQL
Server
173,962
Dec
‘10
Sybase
IQ
164,747
Apr
‘10
Oracle
140,181
Dec
‘11
SQL
Server
134,117
Fastest TPC-H QphH@1TB Benchmark (non-clustered)
Source:
www.tpc.org
/
June
15,
2012
18
19. Vectorwise:
Affordable Performance – Proven!
QphH 0
100,000
200,000
300,000
400,000
Hardware
Cost
(excluding
discounts)
June
‘12
Vectorwise
445,529
$57,146
May
‘11
Vectorwise
436,788
$85,621
Aug
‘11
SQL
Server
219,888
$460,869
June
‘11
Oracle
209,534
$2,402,706
Sept
‘11
Oracle
201,487
$753,392
Apr
‘11
SQL
Server
173,962
$278,527
Dec
‘10
Sybase
IQ
164,747
$1,229,968
Apr
‘10
Oracle
140,181
$1,249,967
Dec
‘11
SQL
Server
134,117
$258,880
Fastest TPC-H QphH@1TB Benchmark (non-clustered)
Source:
www.tpc.org
/
June
15,
2012
19
21. Customer Stories: Sheetz and Zoho
! Leader in Convenience Stores ! SaaS Company with 6 million Users
! Problem ! Problem and Requirements
! Customer data growing rapidly
! Multiple data sources
! Ease of use for self-service BI
! Need to control costs
! Affordability
! Huge data growth
! 200,000 users of Zoho Reports
! Vectorwise results Vectorwise results
! Expand data to analyze two years ! Exceptional performance
! Manage growth for three years ! Affordability for a SaaS offering
21
23. Customer Stories: Badoo
! Fastest Growing Social Network
! Problem
! Limited slice and dice analytics
! Better target ad campaigns
! Huge data growth
! Vectorwise results
! Detailed answers in seconds
! Immediate actions
23
24. Summary
! Successful businesses require speed and agility
! BI solutions must address these requirements
! Recommendations for how to get started and succeed:
! Align IT goals and organization with user needs and business goals
! Include operational processes in requirements (business and IT)
! POC with Vectorwise for affordable performance and scalability
24
34. • The query patterns for BI business analytics are much different than
transactional processing. What are the key differences? How do you address
them?
• Traditionally BI implementations required a sophisticated data architecture
including a DW, data marts (dimensional), OLAP, “flattened” datasets,
aggregated/summarized tables and other reporting data stores. Also maybe
an ODS (operational data store), staging tables and various data shadow
systems. Do you reduce the complexity of the traditional data architecture?
• A key component of developing the business analytics is to define what data
the business needs, how they plan to analyze on it, design the queries, tune
the database, etc. And then do it again for each query. How do you change
that?
• Business analytics typically involves a variety of BI tools such as reports,
dashboards, scorecards, ad-hoc analytics, data visualization, data discovery
and predictive analytics. How do you interact with these tools?
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35. • Business analytics/BI, data integration and DW requires a lot of varied skills.
What type of skills are needed to successfully implement your solutions? Do
you raise the increase on skills needed for implementation?
• The limiting factor on many enterprise-wide BI and DW programs has been
cost, but emerging technology is perceived as more expensive. How do you
lower the TCO?
• Assume that most enterprises have a DW (maybe even MDM) in order to
enable consistent and conformed data. How does your solution leverage the
DW? Does you solution lessen the need for a DW?
• There was a lot of hype regarding BI Appliances a while ago and many
vendors used that term to label various hardware & software combinations.
From the hype, what has emerged to impact BI & how? What are the
“pretender” technologies that have not fulfilled on hype (no vendor names!)?
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