Your SlideShare is downloading. ×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Introducing the official SlideShare app

Stunning, full-screen experience for iPhone and Android

Text the download link to your phone

Standard text messaging rates apply

The Need for Speed - Conversational Analytics for Complex Challenges

378
views

Published on

The Briefing Room with Robin Bloor and Actian …

The Briefing Room with Robin Bloor and Actian
Slides from the Live Webcast on May 8, 2012

Getting into an analytical rhythm requires more than just data and time. One of the key ingredients is speed, specifically, the ability to ask questions of your data in a conversational fashion. This has traditionally been the domain of Operational Data Stores or OLAP cubes, but there are new options today that don't rely so heavily on the kind of maintenance necessary to keep those solutions humming. Today, there are specialized database technologies that can fuel conversational analytics.

Check out this episode of The Briefing Room to learn from 30-year IT Analyst Robin Bloor, Ph.D., who will chart the evolution of specialty database technology. He'll explain how vector-based processing in particular changes the game of analytics. Bloor will be briefed by Fred Gallagher of Actian, who will discuss the technical advantages of the Actian Vectorwise database, including vector-based processing, on-chip memory optimization, parallel execution, column-based storage and self-optimizing compression.

For more information visit: http://www.insideanalysis.com

Watch us on YouTube: http://www.youtube.com/playlist?list=PL5EE76E2EEEC8CF9E

Published in: Technology

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
378
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Tuesday, May 8, 12
  • 2. Eric.kavanagh@bloorgroup.com Twitter Tag: #briefrTuesday, May 8, 12
  • 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! Twitter Tag: #briefrTuesday, May 8, 12
  • 4. May: Analytics June: Intelligence July: Governance August: Analytics September: Integration October: Database Twitter Tag: #briefrTuesday, May 8, 12
  • 5. Ultimately analytics is about businesses making optimal decisions, although the range of technologies that inhabit this area is wide: statistical analysis, data mining, process mining, predictive analytics, predictive modeling, business process modeling and additionally complex event processing. With the advent of big data, analytics has become “big analytics” with organizations diving into large heaps of data that previously was not available or usable. When you combine analytics with Big Data response times can become barriers to meeting business goals in the needed time frame. Database performance become a key determining factor. Twitter Tag: #briefrTuesday, May 8, 12
  • 6. Robin Bloor is Chief Analyst at The Bloor Group. Robin.Bloor@Bloorgroup.com Twitter Tag: #briefrTuesday, May 8, 12
  • 7. Actian Corporation (formerly Ingres Corp.) is a database and software development company. Its premier database platform is Vectorwise a new, innovative and highly performant database. Vectorwise is the only database platform we are aware of that implements parallelism at every level from the processor core to data storage and is thus both scalable and highly performant. Actian also boasts a cloud-based app development platform tailored for building mobile applications (actian Apps) which are lightweight consumer-style applications that automate business actions triggered by real-time changes in data. Twitter Tag: #briefrTuesday, May 8, 12
  • 8. Fred Gallagher GM, Vectorwise at Actian Corporation is responsible for managing the business activities for Actian’s breakthrough product. He joined Actian in 2006 as vice president of business development. Prior to joining Actian, Fred worked for Qlusters, where he was responsible for worldwide sales, marketing, and business development. Previously, he was at Seagate Technology. Fred holds Bachelor of Arts and an MBA from Stanford University. Twitter Tag: #briefrTuesday, May 8, 12
  • 9. Vectorwise Enabling Conversational Analytics Fred Gallagher General Manager of Vectorwise, Actian CorporationTuesday, May 8, 12
  • 10. Actian Overview !"#$%#& ($%)*+ ,&-.$ ()*+%(//0 !"#$%&()*+%+%,$&-"." 2 10Tuesday, May 8, 12
  • 11. Vectorwise Enabling Conversational Analytics 11Tuesday, May 8, 12
  • 12. Conversational Analytics: What is it? The ability to interact with your data in real-time and ask follow up questions in the moment 12Tuesday, May 8, 12
  • 13. Conversational Analytics: The Need for Speed Empower your employees to get insight quickly Be faster than your competition Optimize your business Discover new opportunities first 13Tuesday, May 8, 12
  • 14. Vectorwise Optimizes the Modern Technology Stack 456 ,12(34444444444444444444444444444444444444444444444444444444425!(6(784 2(3 -$0# !"/1 49:;%4<4=:;%4444444444444444444444444444444444444444444444444444444444444444444444444444444>.?4@4ABB"C 6 /0Tuesday, May 8, 12
  • 15. Vectorwise Optimizes the Modern Technology Stack !7"8$*+%"9-".":"010;/*<$=1 >+7-$0#"%82(3 456 ,12(34444444444444444444444444444444444444444444444444444444425!(6(784 2(3 -$0# !"/1 49:;%4<4=:;%4444444444444444444444444444444444444444444444444444444444444444444444444444444>.?4@4ABB"C 6 /0Tuesday, May 8, 12
  • 16. Vectorwise Optimizes the Modern Technology Stack !7"8$*+%"9-".":"010;/*<$=1 >+7-$0#"%82(3 456?$.@AB4")@1 456 ,12(34444444444444444444444444444444444444444444444444444444425!(6(784 2(3 2(3 -$0# -$0# !"/1 49:;%4<4=:;%4444444444444444444444444444444444444444444444444444444444444444444444444444444>.?4@4ABB"C 6 /0Tuesday, May 8, 12
  • 17. Vectorwise Optimizes the Modern Technology Stack !7"8$*+%"9-".":"010;/*<$=1 >+7-$0#"%82(3 456?$.@AB4")@1 456 ,12(34444444444444444444444444444444444444444444444444444444425!(6(784 2(3 2(3 -$0# -$0# C1).+7?$01;/*<$=10 !"/1 >+7456"%8AB4")@1 49:;%4<4=:;%4444444444444444444444444444444444444444444444444444444444444444444444444444444>.?4@4ABB"C 6 /0Tuesday, May 8, 12
  • 18. Vectorwise: What Makes it So Fast? F U ;%4@$/4+</L*%& C1).+757+)100$%& 3(EI 4+7191D19/"7"9919/7+)100$%&E 6)HH).$% FGGH Time / Cycles to Process J,6 CD*D4E(63F4EBGC"%&#H"7 /Q:@OQ: KL(5 B U%8X1%4+9L<%W.+71 O@O: 0:@0::6N O@PMN /:MN A$<$.IJ;.+0/1)$K))+9L<%0M Data Processed NO)$1%.71"9*<1L/8".10M SFGGHT"0.17.+/7+)1008"."+%)@$/ )")@1.@"%$%2(3M V W<"7.174+</7100$+% (L.+<"*)+/*<$="*+%+>>L99 0.+7"&1@$17"7)@Q 3"P$<$=10.@7+L&@/L.D$" "L.+<"*)"99Q+/*<$=18+%R)@$/ compression 16Tuesday, May 8, 12
  • 19. Vectorwise: Affordable Performance – Proven! 17Tuesday, May 8, 12
  • 20. Vectorwise: Affordable Performance – Proven! 517>+7<"%)1 !+/_`+%R49L0.1718-".":"01WQ0.1< ]Z/@[F!,^ Q::F::: !54R[F!,W)"91T").+7 C1).+7?$01 B3"QUGFF 0::F::: P::F::: ;7")91 3$)7+0+e BfL%1UGFF BG(L&L0.UGFF O::F::: WQ:"01IZ 3$)7+0+e F_-1)UGFG _(/7UGFF dG)+710 BU)+710 aV)+710 dG)+710 /::F::: U!,2(3 F!,2(3 _FUX, U!, 2(3 2(3 /0:F/9/ /V0FW0W /WPF=V/ VBabcdd O:=FQPP O/=F999 : 57$)1J517>+7<"%)1 6WYJZ/@[F!, XVD9Q4YE X/DPW4YE X:D994YE X=DQP4YE X/D9V4YE E.B"&CR4???DG&D."*4S4ECGCTUC"4/=F4O:// Vectorwise is FASTER on LESS Hardware for Unbeatable Price Performance /99Tuesday, May 8, 12
  • 21. What Makes Data Useful?A;gC(A6N[IX[C(A6N Ability for business users to analyze granular data quickly! hF01)+%8_.+FG01) F<$% FG<$% BG<$% ZL17Q517>+7<"%)1 19Tuesday, May 8, 12
  • 22. Tuesday, May 8, 12
  • 23. From Insight to Action The Next FrontierTuesday, May 8, 12
  • 24. Taking Action on Big Data Action Apps are lightweight consumer style applications that automate business actions. 22Tuesday, May 8, 12
  • 25. Tuesday, May 8, 12
  • 26. Actian Overview ,&-.$ 21/+7*%&"%8 -"0@:+"780 ()*+%(//0 (%"9Q*)0 49+L8()*+%59"i+7< !"#$%#& ($%)*+ 15 24Tuesday, May 8, 12
  • 27. Summary Most DBMS’s designed for 1980’s hardware Vectorwise exploits 30 years of hardware advances Processors, cache and memory Solves the problem instead of throwing money at the problem Several proof-points with customers and benchmarks Vectorwise speed creates value from data Brings data to solve business problems and take action in real-time Optimize data infrastructure and your business Competitive advantage OQTuesday, May 8, 12
  • 28. A1"7%<+71"%88+?%9+"8"C1).+7?$01.7$"9".j???M")*"%M)+<JD1).+7?$01Tuesday, May 8, 12
  • 29. Twitter Tag: #briefrTuesday, May 8, 12
  • 30. Tuesday, May 8, 12
  • 31. Tuesday, May 8, 12
  • 32. Most of the Big Data opportunity is really a Big Analytics opportunity. Companies rarely think in terms of “better dashboards” when they embark on Big Data projects Big Analytics can be thought of as involving 2 distinctly different latencies: Acceptable latency Truly actionable latency The second of these is an imperative in some business areas e.g. credit card fraud, telco customer churn, risk analysis, etc.Tuesday, May 8, 12
  • 33. Analytics needs to be a precursor to action. There are very few new analytical techniques. Indeed most analytical techniques are old and well understood and well established. The challenge with analytics is whether analytical activity is well integrated within a business process, so that when a trend changes, a business can respond quickly (if it is a contextual trend) and quickly enough (if it is a competitive trend). Sometimes businesses perform the analytics but fail to act. It’s more common than it should be.Tuesday, May 8, 12
  • 34. Tuesday, May 8, 12
  • 35. Big Analytics is here to stay In some analytical application areas speed is desirable, in others speed is critical Analytic speed depends upon the database engine, but also data flow architecture Business effectiveness depends upon integration with the business process Twitter Tag: #briefrTuesday, May 8, 12
  • 36. Questions What specific application areas do you regard as sweet spots for VectorWise Benchmarks may be impressive, but in the end they are synthetic. So the question is how well does Vectorwise perform: With mixed query workloads (short and long queries) on large volume data? With heavy duty analytic workloads? (what difference does vector processing make in this area? Can it handle fast ingest with simultaneous query workloads. Twitter Tag: #briefrTuesday, May 8, 12
  • 37. Questions In what way is Vectrowise available as a cloud service. Is there anythign other than speed which differentiates you? Which vendors do you tend to meet in competition? Who have been the early adopters of this kind of capability and what kind of business problems are they trying to solve? Which vertical business sectors have shown most interest in Vectorwise and which have shown the least How important is Vectorwise as a complement to your mobile App platform? Twitter Tag: #briefrTuesday, May 8, 12
  • 38. Tuesday, May 8, 12
  • 39. May: Analytics June: Intelligence July: Governance August: Analytics September: Integration October: Database Twitter Tag: #briefrTuesday, May 8, 12
  • 40. Tuesday, May 8, 12