Tag: Companies

PAWCON -This week in London

Watch out for the twitter hash news on PAWCON and the exciting agenda lined up. If your in the City- you may want to just drop in

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Disclaimer- PAWCON has been a blog partner with Decisionstats (since the first PAWCON ). It is vendor neutral and features open source as well proprietary software, as well case studies from academia and Industry for a balanced view.

 

Little birdie told me some exciting product enhancements may be in the works including a not yet announced R plugin 😉 and the latest SAS product using embedded analytics and Dr Elder’s full day data mining workshop.

Citation-

http://www.predictiveanalyticsworld.com/london/2010/agenda.php#day1-7

Monday November 15, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites

9:00am-9:50am

Keynote
Five Ways Predictive Analytics Cuts Enterprise Risk

All business is an exercise in risk management. All organizations would benefit from measuring, tracking and computing risk as a core process, much like insurance companies do.

Predictive analytics does the trick, one customer at a time. This technology is a data-driven means to compute the risk each customer will defect, not respond to an expensive mailer, consume a retention discount even if she were not going to leave in the first place, not be targeted for a telephone solicitation that would have landed a sale, commit fraud, or become a “loss customer” such as a bad debtor or an insurance policy-holder with high claims.

In this keynote session, Dr. Eric Siegel will reveal:

  • Five ways predictive analytics evolves your enterprise to reduce risk
  • Hidden sources of risk across operational functions
  • What every business should learn from insurance companies
  • How advancements have reversed the very meaning of fraud
  • Why “man + machine” teams are greater than the sum of their parts for

    • enterprise decision support

 

Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

[ Top of this page ] [ Agenda overview ]

IBM9:50am-10:10am

Platinum Sponsor Presentation
The Analytical Revolution

The algorithms at the heart of predictive analytics have been around for years – in some cases for decades. But now, as we see predictive analytics move to the mainstream and become a competitive necessity for organisations in all industries, the most crucial challenges are to ensure that results can be delivered to where they can make a direct impact on outcomes and business performance, and that the application of analytics can be scaled to the most demanding enterprise requirements.

This session will look at the obstacles to successfully applying analysis at the enterprise level, and how today’s approaches and technologies can enable the true “industrialisation” of predictive analytics.

Speaker: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

[ Top of this page ] [ Agenda overview ]

Deloitte10:10am-10:20am

Gold Sponsor Presentation
How Predictive Analytics is Driving Business Value

Organisations are increasingly relying on analytics to make key business decisions. Today, technology advances and the increasing need to realise competitive advantage in the market place are driving predictive analytics from the domain of marketers and tactical one-off exercises to the point where analytics are being embedded within core business processes.

During this session, Richard will share some of the focus areas where Deloitte is driving business transformation through predictive analytics, including Workforce, Brand Equity and Reputational Risk, Customer Insight and Network Analytics.

Speaker: Richard Fayers, Senior Manager, Deloitte Analytical Insight

[ Top of this page ] [ Agenda overview ]

10:20am-10:45am

Break / Exhibits
Room: Albert Suites

10:45am-11:35am
Healthcare
Case Study: Life Line Screening
Taking CRM Global Through Predictive Analytics

While Life Line is successfully executing a US CRM roadmap, they are also beginning this same evolution abroad. They are beginning in the UK where Merkle procured data and built a response model that is pulling responses over 30% higher than competitors. This presentation will give an overview of the US CRM roadmap, and then focus on the beginning of their strategy abroad, focusing on the data procurement they could not get anywhere else but through Merkle and the successful modeling and analytics for the UK.

Speaker: Ozgur Dogan, VP, Quantitative Solutions Group, Merkle Inc.

Speaker: Trish Mathe, Life Line Screening

[ Top of this page ] [ Agenda overview ]

11:35am-12:25pm
Open Source Analytics; Healthcare
Case Study: A large health care organization
The Rise of Open Source Analytics: Lowering Costs While Improving Patient Care

Rapidminer and R were the number 1 and 2 in this years annual KDNuggets data mining tool usage poll, followed by Knime on place 4 and Weka on place 6. So what’s going on here? Are these open source tools really that good or is their popularity strongly correlated with lower acquisition costs alone? This session answers these questions based on a real world case for a large health care organization and explains the risks & benefits of using open source technology. The final part of the session explains how these tools stack up against their traditional, proprietary counterparts.

Speaker: Jos van Dongen, Associate & Principal, DeltIQ Group

[ Top of this page ] [ Agenda overview ]

12:25pm-1:25pm

Lunch / Exhibits
Room: Albert Suites

1:25pm-2:15pm
Keynote
Thought Leader:
Case Study: Yahoo! and other large on-line e-businesses
Search Marketing and Predictive Analytics: SEM, SEO and On-line Marketing Case Studies

Search Engine Marketing is a $15B industry in the U.S. growing to double that number over the next 3 years. Worldwide the SEM market was over $50B in 2010. Not only is this a fast growing area of marketing, but it is one that has significant implications for brand and direct marketing and is undergoing rapid change with emerging channels such as mobile and social. What is unique about this area of marketing is a singularly heavy dependence on analytics:

 

  • Large numbers of variables and options
  • Real-time auctions/bids and a need to adjust strategies in real-time
  • Difficult optimization problems on allocating spend across a huge number of keywords
  • Fast-changing competitive terrain and heavy competition on the obvious channels
  • Complicated interactions between various channels and a large choice of search keyword expansion possibilities
  • Profitability and ROI analysis that are complex and often challenging

 

The size of the industry, its growing importance in marketing, its upcoming role in Mobile Advertising, and its uniquely heavy reliance on analytics makes it particularly interesting as an area for predictive analytics applications. In this session, not only will hear about some of the latest strategies and techniques to optimize search, you will hear case studies that illustrate the important role of analytics from industry practitioners.

Speaker: Usama Fayyad, , Ph.D., CEO, Open Insights

[ Top of this page ] [ Agenda overview ]

SAS2:15pm-2:35pm

Platinum Sponsor Presentation
Creating a Model Factory Using in-Database Analytics

With the ever-increasing number of analytical models required to make fact-based decisions, as well as increasing audit compliance regulations, it is more important than ever that these models can be created, monitored, retuned and deployed as quickly and automatically as possible. This paper, using a case study from a major financial organisation, will show how organisations can build a model factory efficiently using the latest SAS technology that utilizes the power of in-database processing.

Speaker: John Spooner, Analytics Specialist, SAS (UK)

[ Top of this page ] [ Agenda overview ]

2:35pm-2:45pm

Session Break
Room: Albert Suites

2:45pm-3:35pm

Retail
Case Study: SABMiller
Predictive Analytics & Global Marketing Strategy

Over the last few years SABMiller plc, the second largest brewing company in the world operating in 70 countries, has been systematically segmenting its markets in different countries globally in order optimize their portfolio strategy & align it to their long term country specific growth strategy. This presentation talks about the overall methodology followed and the challenges that had to be overcome both from a technical as well as from a change management stand point in order to successfully implement a standard analytics approach to diverse markets and diverse business positions in a highly global setting.

The session explains how country specific growth strategies were converted to objective variables and consumption occasion segments were created that differentiated the market effectively by their growth potential. In addition to this the presentation will also provide a discussion on issues like:

  • The dilemmas of static vs. dynamic solutions and standardization vs. adaptable solutions
  • Challenges in acceptability, local capability development, overcoming implementation inertia, cost effectiveness, etc
  • The role that business partners at SAB and analytics service partners at AbsolutData together play in providing impactful and actionable solutions

 

Speaker: Anne Stephens, SABMiller plc

Speaker: Titir Pal, AbsolutData

[ Top of this page ] [ Agenda overview ]

3:35pm-4:25pm

Retail
Case Study: Overtoom Belgium
Increasing Marketing Relevance Through Personalized Targeting

 

Since many years, Overtoom Belgium – a leading B2B retailer and division of the French Manutan group – focuses on an extensive use of CRM. In this presentation, we demonstrate how Overtoom has integrated Predictive Analytics to optimize customer relationships. In this process, they employ analytics to develop answers to the key question: “which product should we offer to which customer via which channel”. We show how Overtoom gained a 10% revenue increase by replacing the existing segmentation scheme with accurate predictive response models. Additionally, we illustrate how Overtoom succeeds to deliver more relevant communications by offering personalized promotional content to every single customer, and how these personalized offers positively impact Overtoom’s conversion rates.

Speaker: Dr. Geert Verstraeten, Python Predictions

[ Top of this page ] [ Agenda overview ]

4:25pm-4:50pm

Break / Exhibits
Room: Albert Suites

4:50pm-5:40pm
Uplift Modelling:
Case Study: Lloyds TSB General Insurance & US Bank
Uplift Modelling: You Should Not Only Measure But Model Incremental Response

Most marketing analysts understand that measuring the impact of a marketing campaign requires a valid control group so that uplift (incremental response) can be reported. However, it is much less widely understood that the targeting models used almost everywhere do not attempt to optimize that incremental measure. That requires an uplift model.

This session will explain why a switch to uplift modelling is needed, illustrate what can and does go wrong when they are not used and the hugely positive impact they can have when used effectively. It will also discuss a range of approaches to building and assessing uplift models, from simple basic adjustments to existing modelling processes through to full-blown uplift modelling.

The talk will use Lloyds TSB General Insurance & US Bank as a case study and also illustrate real-world results from other companies and sectors.

 

Speaker: Nicholas Radcliffe, Founder and Director, Stochastic Solutions

[ Top of this page ] [ Agenda overview ]

5:40pm-6:30pm

Consumer services
Case Study: Canadian Automobile Association and other B2C examples
The Diminishing Marginal Returns of Variable Creation in Predictive Analytics Solutions

 

Variable Creation is the key to success in any predictive analytics exercise. Many different approaches are adopted during this process, yet there are diminishing marginal returns as the number of variables increase. Our organization conducted a case study on four existing clients to explore this so-called diminishing impact of variable creation on predictive analytics solutions. Existing predictive analytics solutions were built using our traditional variable creation process. Yet, presuming that we could exponentially increase the number of variables, we wanted to determine if this added significant benefit to the existing solution.

Speaker: Richard Boire, BoireFillerGroup

[ Top of this page ] [ Agenda overview ]

6:30pm-7:30pm

Reception / Exhibits
Room: Albert Suites

Tuesday November 16, 2010
All conference sessions take place in Edward 5-7

8:00am-9:00am

Registration, Coffee and Danish
Room: Albert Suites

9:00am-9:55am
Keynote
Multiple Case Studies: Anheuser-Busch, Disney, HP, HSBC, Pfizer, and others
The High ROI of Data Mining for Innovative Organizations

Data mining and advanced analytics can enhance your bottom line in three basic ways, by 1) streamlining a process, 2) eliminating the bad, or 3) highlighting the good. In rare situations, a fourth way – creating something new – is possible. But modern organizations are so effective at their core tasks that data mining usually results in an iterative, rather than transformative, improvement. Still, the impact can be dramatic.

Dr. Elder will share the story (problem, solution, and effect) of nine projects conducted over the last decade for some of America’s most innovative agencies and corporations:

    Streamline:

  • Cross-selling for HSBC
  • Image recognition for Anheuser-Busch
  • Biometric identification for Lumidigm (for Disney)
  • Optimal decisioning for Peregrine Systems (now part of Hewlett-Packard)
  • Quick decisions for the Social Security Administration
    Eliminate Bad:

  • Tax fraud detection for the IRS
  • Warranty Fraud detection for Hewlett-Packard
    Highlight Good:

  • Sector trading for WestWind Foundation
  • Drug efficacy discovery for Pharmacia & UpJohn (now Pfizer)

Moderator: Eric Siegel, Program Chair, Predictive Analytics World

Speaker: John Elder, Ph.D., Elder Research, Inc.

Also see Dr. Elder’s full-day workshop

 

[ Top of this page ] [ Agenda overview ]

9:55am-10:30am

Break / Exhibits
Room: Albert Suites

10:30am-11:20am
Telecommunications
Case Study: Leading Telecommunications Operator
Predictive Analytics and Efficient Fact-based Marketing

The presentation describes what are the major topics and issues when you introduce predictive analytics and how to build a Fact-Based marketing environment. The introduced tools and methodologies proved to be highly efficient in terms of improving the overall direct marketing activity and customer contact operations for the involved companies. Generally, the introduced approaches have great potential for organizations with large customer bases like Mobile Operators, Internet Giants, Media Companies, or Retail Chains.

Main Introduced Solutions:-Automated Serial Production of Predictive Models for Campaign Targeting-Automated Campaign Measurements and Tracking Solutions-Precise Product Added Value Evaluation.

Speaker: Tamer Keshi, Ph.D., Long-term contractor, T-Mobile

Speaker: Beata Kovacs, International Head of CRM Solutions, Deutsche Telekom

[ Top of this page ] [ Agenda overview ]

11:20am-11:25am

Session Changeover

11:25am-12:15pm
Thought Leader
Nine Laws of Data Mining

Data mining is the predictive core of predictive analytics, a business process that finds useful patterns in data through the use of business knowledge. The industry standard CRISP-DM methodology describes the process, but does not explain why the process takes the form that it does. I present nine “laws of data mining”, useful maxims for data miners, with explanations that reveal the reasons behind the surface properties of the data mining process. The nine laws have implications for predictive analytics applications: how and why it works so well, which ambitions could succeed, and which must fail.

 

Speaker: Tom Khabaza, khabaza.com

 

[ Top of this page ] [ Agenda overview ]

12:15pm-1:30pm

Lunch / Exhibits
Room: Albert Suites

1:30pm-2:25pm
Expert Panel: Kaboom! Predictive Analytics Hits the Mainstream

Predictive analytics has taken off, across industry sectors and across applications in marketing, fraud detection, credit scoring and beyond. Where exactly are we in the process of crossing the chasm toward pervasive deployment, and how can we ensure progress keeps up the pace and stays on target?

This expert panel will address:

  • How much of predictive analytics’ potential has been fully realized?
  • Where are the outstanding opportunities with greatest potential?
  • What are the greatest challenges faced by the industry in achieving wide scale adoption?
  • How are these challenges best overcome?

 

Panelist: John Elder, Ph.D., Elder Research, Inc.

Panelist: Colin Shearer, WW Industry Solutions Leader, IBM UK Ltd

Panelist: Udo Sglavo, Global Analytic Solutions Manager, SAS

Panel moderator: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

2:25pm-2:30pm

Session Changeover

2:30pm-3:20pm
Crowdsourcing Data Mining
Case Study: University of Melbourne, Chessmetrics
Prediction Competitions: Far More Than Just a Bit of Fun

Data modelling competitions allow companies and researchers to post a problem and have it scrutinised by the world’s best data scientists. There are an infinite number of techniques that can be applied to any modelling task but it is impossible to know at the outset which will be most effective. By exposing the problem to a wide audience, competitions are a cost effective way to reach the frontier of what is possible from a given dataset. The power of competitions is neatly illustrated by the results of a recent bioinformatics competition hosted by Kaggle. It required participants to pick markers in HIV’s genetic sequence that coincide with changes in the severity of infection. Within a week and a half, the best entry had already outdone the best methods in the scientific literature. This presentation will cover how competitions typically work, some case studies and the types of business modelling challenges that the Kaggle platform can address.

Speaker: Anthony Goldbloom, Kaggle Pty Ltd

[ Top of this page ] [ Agenda overview ]

3:20pm-3:50pm

Breaks /Exhibits
Room: Albert Suites

3:50pm-4:40pm
Human Resources; e-Commerce
Case Study: Naukri.com, Jeevansathi.com
Increasing Marketing ROI and Efficiency of Candidate-Search with Predictive Analytics
InfoEdge, India’s largest and most profitable online firm with a bouquet of internet properties has been Google’s biggest customer in India. Our team used predictive modeling to double our profits across multiple fronts. For Naukri.com, India’s number 1 job portal, predictive models target jobseekers most relevant to the recruiter. Analytical insights provided a deeper understanding of recruiter behaviour and informed a redesign of this product’s recruiter search functionality. This session will describe how we did it, and also reveal how Jeevansathi.com, India’s 2nd-largest matrimony portal, targets the acquisition of consumers in the market for marriage.

 

Speaker: Suvomoy Sarkar, Chief Analytics Officer, HT Media & Info Edge India (parent company of the two companies above)

 

[ Top of this page ] [ Agenda overview ]

4:40pm-5:00pm
Closing Remarks

Speaker: Eric Siegel, Ph.D., Program Chair, Predictive Analytics World

[ Top of this page ] [ Agenda overview ]

Wednesday November 17, 2010

Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes
Click here for the detailed workshop description

  • Workshop starts at 9:00am
  • First AM Break from 10:00 – 10:15
  • Second AM Break from 11:15 – 11:30
  • Lunch from 12:30 – 1:15pm
  • First PM Break: 2:00 – 2:15
  • Second PM Break: 3:15 – 3:30
  • Workshop ends at 4:30pm

Speaker: John Elder, Ph.D., CEO and Founder, Elder Research, Inc.

 

Interview James Dixon Pentaho

Here is an interview with James Dixon the founder of Pentaho, self confessed Chief Geek and CTO. Pentaho has been growing very rapidly and it makes open source Business Intelligence solutions- basically the biggest chunk of enterprise software market currently.

Ajay-  How would you describe Pentaho as a BI product for someone who is completely used to traditional BI vendors (read non open source). Do the Oracle lawsuits over Java bother you from a business perspective?

James-

Pentaho has a full suite of BI software:

* ETL: Pentaho Data Integration

* Reporting: Pentaho Reporting for desktop and web-based reporting

* OLAP: Mondrian ROLAP engine, and Analyzer or Jpivot for web-based OLAP client

* Dashboards: CDF and Dashboard Designer

* Predictive Analytics: Weka

* Server: Pentaho BI Server, handles web-access, security, scheduling, sharing, report bursting etc

We have all of the standard BI functionality.

The Oracle/Java issue does not bother me much. There are a lot of software companies dependent on Java. If Oracle abandons Java a lot resources will suddenly focus on OpenJDK. It would be good for OpenJDK and might be the best thing for Java in the long term.

Ajay-  What parts of Pentaho’s technology do you personally like the best as having an advantage over other similar proprietary packages.

Describe the latest Pentaho for Hadoop offering and Hadoop/HIVE ‘s advantage over say Map Reduce and SQL.

James- The coolest thing is that everything is pluggable:

* ETL: New data transformation steps can be added. New orchestration controls (job entries) can be added. New perspectives can be added to the design UI. New data sources and destinations can be added.

* Reporting: New content types and report objects can be added. New data sources can be added.

* BI Server: Every factory, engine, and layer can be extended or swapped out via configuration. BI components can be added. New visualizations can be added.

This means it is very easy for Pentaho, partners, customers, and community member to extend our software to do new things.

In addition every engine and component can be fully embedded into a desktop or web-based application. I made a youtube video about our philosophy: http://www.youtube.com/watch?v=uMyR-In5nKE

Our Hadoop offerings allow ETL developers to work in a familiar graphical design environment, instead of having to code MapReduce jobs in Java or Python.

90% of the Hadoop use cases we hear about are transformation/reporting/analysis of structured/semi-structured data, so an ETL tool is perfect for these situations.

Using Pentaho Data Integration reduces implementation and maintenance costs significantly. The fact that our ETL engine is Java and is embeddable means that we can deploy the engine to the Hadoop data nodes and transform the data within the nodes.

Ajay-  Do you think the combination of recession, outsourcing,cost cutting, and unemployment are a suitable environment for companies to cut technology costs by going out of their usual vendor lists and try open source for a change /test projects.

Jamie- Absolutely. Pentaho grew (downloads, installations, revenue) throughout the recession. We are on target to do 250% of what we did last year, while the established vendors are flat in terms of new license revenue.

Ajay-  How would you compare the user interface of reports using Pentaho versus other reporting software. Please feel free to be as specific.

James- We have all of the everyday, standard reporting features covered.

Over the years the old tools, like Crystal Reports, have become bloated and complicated.

We don’t aim to have 100% of their features, because we’d end us just as complicated.

The 80:20 rule applies here. 80% of the time people only use 20% of their features.

We aim for 80% feature parity, which should cover 95-99% of typical use cases.

Ajay-  Could you describe the Pentaho integration with R as well as your relationship with Weka. Jaspersoft already has a partnership with Revolution Analytics for RevoDeployR (R on a web server)-

Any  R plans for Pentaho as well?

James- The feature set of R and Weka overlap to a small extent – both of them include basic statistical functions. Weka is focused on predictive models and machine learning, whereas R is focused on a full suite of statistical models. The creator and main Weka developer is a Pentaho employee. We have integrated R into our ETL tool. (makes me happy 🙂 )

(probably not a good time to ask if SAS integration is done as well for a big chunk of legacy base SAS/ WPS users)

About-

As “Chief Geek” (CTO) at Pentaho, James Dixon is responsible for Pentaho’s architecture and technology roadmap. James has over 15 years of professional experience in software architecture, development and systems consulting. Prior to Pentaho, James held key technical roles at AppSource Corporation (acquired by Arbor Software which later merged into Hyperion Solutions) and Keyola (acquired by Lawson Software). Earlier in his career, James was a technology consultant working with large and small firms to deliver the benefits of innovative technology in real-world environments.

Related Articles

Open Source's worst enemy is itself not Microsoft/SAS/SAP/Oracle

The decision of quality open source makers to offer their software at bargain basement prices even to enterprise customers who are used to pay prices many times more-pricing is the reason open source software is taking a long time to command respect in enterprise software.

I hate to be the messenger who brings the bad news to my open source brethren-

but their worst nightmare is not the actions of their proprietary competitors like Oracle, SAP, SAS, Microsoft ( they hate each other even more than open source )

nor the collective marketing tactics which are textbook like (but referred as Fear Uncertainty Doubt by those outside that golden quartet)- it is their own communities and their own cheap pricing.

It is community action which prevents them from offering their software by ridiculously low bargain basement prices. James Dixon, head geek and founder at Pentaho has a point when he says traditional metrics like revenue need o be adjusted for this impact in his article at http://jamesdixon.wordpress.com/2010/11/02/comparing-open-source-and-proprietary-software-markets/

But James, why offer software to enterprise customers at one tenth the next competitor- one reason is open source companies more often than not compete more with their free community version software than with big proprietary packages.

Communities including academics are used to free- hey how about paying say 1$ for each download.

There are two million R users- if say even 50 % of them  paid 1 $ as a lifetime license fee- you could sponsor enough new packages than twenty years of Google Summer of Code does right now.

Secondly, this pricing can easily be adjusted by shifting the licensing to say free for businesses less than 2 people (even for the enhanced corporate software version not just the plain vanilla community software thus further increasing the spread of the plain vanilla versions)- for businesses from 10 to 20 people offer a six month trial rather than one month trial.

– but adjust the pricing to much more realistic levels compared to competing software. Make enterprise software pay a real value.

That’s the only way to earn respect. as well as a few dollars more.

As for SAS, it is time it started ridiculing Python now that it has accepted R.

Python is even MORE powerful than R in some use cases for stat computing

Dixon’s Pentaho and the Jaspersoft/ Revolution combo are nice _ I tested both Jasper and Pentaho thanks to these remarks this week 🙂  (see slides at http://www.jaspersoft.com/sites/default/files/downloads/events/Analytics%20-Jaspersoft-SEP2010.pdf or http://www.revolutionanalytics.com/news-events/free-webinars/2010/deploying-r/index.php )

Pentaho and Jasper do give good great graphics in BI (Graphical display in BI is not a SAS forte though probably I dont know how much they cross sell JMP to BI customers- probably too much JMP is another division syndrome there)

Related Articles

Jim Goodnight on Open Source- and why he is right -sigh

Logo Open Source Initiative
Image via Wikipedia

Jim Goodnight – grand old man and Godfather of the Cosa Nostra of the BI/Database Analytics software industry said recently on open source in BI (btw R is generally termed in business analytics and NOT business intelligence software so these remarks were more apt to Pentaho and Jaspersoft )

Asked whether open source BI and data integration software from the likes of Jaspersoft, Pentaho and Talend is a growing threat, [Goodnight] said: “We haven’t noticed that a lot. Most of our companies need industrial strength software that has been tested, put through every possible scenario or failure to make sure everything works correctly.”

quotes from Jim Goodnight are courtesy Jason’s  story here:
http://www.cbronline.com/news/sas-ceo-says-cep-open-source-and-cloud-bi-have-limited-appeal

and the Pentaho follow-up reaction is here

http://bi.cbronline.com/news/pentaho-fires-back-across-sas-bows-over-limited-open-source-appeal

 

 

While you can rage and screech- here is the reality in terms of market share-

From Merv Adrian-‘s excellent article on market shares in BI

http://www.enterpriseirregulars.com/22444/decoding-bi-market-share-numbers-%E2%80%93-play-sudoku-with-analysts/

The first, labeled BI Platforms, is drawn fromGartner Market Share Analysis: Business Intelligence, Analytics and Performance Management Software, Worldwide, 2009, published May 2010 , and Gartner Dataquest Market Share: Business Intelligence, Analytics and Performance Management Software, Worldwide, 2009.

and

Advanced Analytics category.

and 

so whats the performance of Talend, Pentaho and Jaspersoft

From http://www.dbms2.com/category/products-and-vendors/talend/

It seems that Talend’s revenue was somewhat shy of $10 million in 2008.

and Talend itself says

http://www.talend.com/press/Talend-Announces-Record-2009-and-Continues-Growth-in-the-New-Year.php

Additional 2009 highlights include:

  • Achieved record revenue, more then doubling from 2008. The fourth quarter of 2009 was Talend’s tenth consecutive quarter of growth.
  • Grew customer base by 140% to over 1,000 customers, up from 420 at the end of 2008. Of these new customers, over 50% are Fortune 1000 companies.
  • Total downloads reached seven million, with over 300,000 users of the open source products.
  • Talend doubled its staff, increasing to 200 global employees. Continuing this trend, Talend has already hired 15 people in 2010 to support its rapid growth.

now for Jaspersoft numbers

http://www.dbms2.com/2008/09/14/jaspersoft-numbers/

Highlights include:

  • Revenue run rate in the double-digit millions.
  • 40% sequential growth most recent quarter. (I didn’t ask whether there was any reason to suspect seasonality.)
  • 130% annual revenue growth run rate.
  • “Not quite” profitable.
  • Several hundred commercial subscribers, at an average of $25K annually per, including >100 in Europe.
  • 9,000 paying customers of some kind.
  • 100,000+ total deployments, “very conservatively,” counting OEMs as one deployment each and not double-counting for OEMs’ customers. (Nick said Business Objects quotes 45,000 deployments by the same standards.)
  • 70% of revenue from the mid-market, defined as $100 million – $1 billion revenue. 30% from bigger enterprises. (Hmm. That begs a couple of questions, such as where OEM revenue comes in, and whether <$100 million enterprises were truly a negligible part of revenue.)

and for Pentaho numbers-

http://www.dbms2.com/2009/01/27/introduction-to-pentaho/

and http://www.monash.com/uploads/Pentaho-January-2009.pdf

suggests there are far far away from the top 5-6 vendors in BI

and a special mention  for postgreSQL– which is a non Profit but is seriously denting Oracle/MySQL

http://www.postgresql.org/about/

Limit Value
Maximum Database Size Unlimited
Maximum Table Size 32 TB
Maximum Row Size 1.6 TB
Maximum Field Size 1 GB
Maximum Rows per Table Unlimited
Maximum Columns per Table 250 – 1600 depending on column types
Maximum Indexes per Table Unlimited

and leading vendor is EnterpriseDB which is again IBM-partnering as well as IBM funded

http://www.sramanamitra.com/2009/05/18/enterprise-db/

and

http://www.enterprisedb.com/company/news_events/press_releases/2010_21.do

suggest it is still in early stages.

————————————————————–

So what do we conclude-

1) There is a complete lack of transparency in open source BI market shares as almost all these companies are privately held and do not disclose revenues.

2) What may be a pure play open source company may actually be a company funded by a big BI vendor (like Revolution Analytics is funded among others by Intel-Microsoft) and EnterpriseDB has IBM as an investor.MySQL and Sun of course are bought by Oracle

The degree of control by proprietary vendors on open source vendors is still not disclosed- whether they are holding a stake for strategic reasons or otherwise.

3) None of the Open Source Vendors are even close to a 1 Billion dollar revenue number.

Jim Goodnight is pointing out market reality when he says he has not seen much impact (in terms of market share). As for the rest of his remarks, well he’s got a job to do as CEO and thats talk up his company and trash the competition- which he as been doing for 3 decades and unlikely to change now unless there is severe market share impact. Unless you expect him to notice companies less than 5% of his size in revenue.

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http://www.cbronline.com/news/sas-ceo-says-cep-open-source-and-cloud-bi-have-limited-appeal

http://bi.cbronline.com/news/pentaho-fires-back-across-sas-bows-over-limited-open-source-appeal

 

Scoring SAS and SPSS Models in the cloud

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An announcement from Zementis and Predixion Software– about using cloud computing for scoring models using PMML. Note R has a PMML package as well which is used by Rattle, data mining GUI for exporting models.

Source- http://www.marketwatch.com/story/predixion-software-introduces-new-product-to-run-sas-and-spss-predictive-models-in-the-cloud-2010-10-19?reflink=MW_news_stmp

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ALISO VIEJO, Calif., Oct 19, 2010 (BUSINESS WIRE) — Predixion Software today introduced Predixion PMML Connexion(TM), an interface that provides Predixion Insight(TM), the company’s low-cost, self-service in the cloud predictive analytics solution, direct and seamless access to SAS, SPSS (IBM) and other predictive models for use by Predixion Insight customers. Predixion PMML Connexion enables companies to leverage their significant investments in legacy predictive analytics solutions at a fraction of the cost of conventional licensing and maintenance fees.

The announcement was made at the Predictive Analytics World conference in Washington, D.C. where Predixion also announced a strategic partnership with Zementis, Inc., a market leader in PMML-based solutions. Zementis is exhibiting in Booth #P2.

The Predictive Model Markup Language (PMML) standard allows for true interoperability, offering a mature standard for moving predictive models seamlessly between platforms. Predixion has fully integrated this PMML functionality into Predixion Insight, meaning Predixion Insight users can now effortlessly import PMML-based predictive models, enabling information workers to score the models in the cloud from anywhere and publish reports using Microsoft Excel(R) and SharePoint(R). In addition, models can also be written back into SAS, SPSS and other platforms for a truly collaborative, interoperable solution.

“Predixion’s investment in this PMML interface makes perfect business sense as the lion’s share of the models in existence today are created by the SAS and SPSS platforms, creating compelling opportunity to leverage existing investments in predictive and statistical models on a low-cost cloud predictive analytics platform that can be fed with enterprise, line of business and cloud-based data,” said Mike Ferguson, CEO of Intelligent Business Strategies, a leading analyst and consulting firm specializing in the areas of business intelligence and enterprise business integration. “In this economy, Predixion’s low-cost, self-service predictive analytics solutions might be welcome relief to IT organizations chartered with quickly adding additional applications while at the same time cutting costs and staffing.”

“We are pleased to be partnering with Zementis, truly a PMML market leader and innovator,” said Predixion CEO Simon Arkell. “To allow any SAS or SPSS customer to immediately score any of their predictive models in the cloud from within Predixion Insight, compare those models to those created by Predixion Insight, and share the results within Excel and Sharepoint is an exciting step forward for the industry. SAS and SPSS customers are fed up with the high prices they must pay for their business users just to access reports generated by highly skilled PhDs who are burdened by performing routine tasks and thus have become a massive bottleneck. That frustration is now a thing of the past because any information worker can now unlock the power of predictive analytics without relying on experts — for a fraction of the cost and from anywhere they can connect to the cloud,” Arkell said.

Dr. Michael Zeller, Zementis CEO, added, “Our mission is to significantly shorten the time-to-market for predictive models in any industry. We are excited to be contributing to Predixion’s self-service, cloud-based predictive analytics solution set.”

About Predixion Software

Predixion Software develops and markets collaborative predictive analytics solutions in the public and private cloud. Predixion enables self-service predictive analytics, allowing customers to use and analyze large amounts of data to make actionable decisions, all within the familiar environment of Excel and PowerPivot. Predixion customers are achieving immediate results across a multitude of industries including: retail, finance, healthcare, marketing, telecommunications and insurance/risk management.

Predixion Software is headquartered in Aliso Viejo, California with development offices in Redmond, Washington. The company has venture capital backing from established investors including DFJ Frontier, Miramar Venture Partners and Palomar Ventures. For more information please contact us at 949-330-6540, or visit us atwww.predixionsoftware.com.

About Zementis

Zementis, Inc. is a leading software company focused on the operational deployment and integration of predictive analytics and data mining solutions. Its ADAPA(R) decision engine successfully bridges the gap between science and engineering. ADAPA(R) was designed from the ground up to benefit from open standards and to significantly shorten the time-to-market for predictive models in any industry. For more information, please visit www.zementis.com.

 

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LibreOffice News and Google Musings

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Official Bloggers on LibreOffice- http://planet.documentfoundation.org/

Note- for some strange reason I continue to be on top ranked LibreOffice blogs- maybe because I write more on the software itself than on Oracle politics or coffee spillovers.

LibreOffice Beta 2  is ready and I just installed it on Windows 7 – works nice- and I somehow think open Office and Google needs an  example to stop being so scary on cautioning—— hey,hey it’s a  beta – (do you see Oracle saying this release is a beta or Windows saying hey this Windows Vista is a beta for Windows 7- No right?)-

see screenshot of solver in  LibreOffice spreadsheet -works just fine.

We cant wait for Chromium OS and LibreOffice integration (or Google Docs-LibreOffice integration)  so Google starts thinking on those lines (of course

Google also needs to ramp up Google Storage and Google Predict API– but dude are you sure you wanna take on Amazon, Oracle and MS and Yahoo and Apple at the same time. Dear Herr Schmidt- Last German Guy who did that ,  ended up in a bunker in Berlin. (Ever since I had to pay 50 euros as Airline Transit fee -yes Indian passport holders have to do that in Germany- I am kind of non objective on that issue)

Google Management is busy nowadays thinking of trying to beat Facebook -hint -hint-

-buy out the biggest app makers of Facebook apps and create an api for Facebook info download and upload into Orkut –maybe invest like an angel in that startup called Diaspora http://www.joindiaspora.com/) see-

Back to the topic (and there are enough people blogging on Google should or shouldnt do)

-LibreOffice aesthetically rocks! It has a cool feel.

More news- The Wiki is up and awaits you at http://wiki.documentfoundation.org/Documentation

And there is a general pow-wow scheduled at http://www.oookwv.de/ for the Open Office Congress (Kongress)

As you can see I used the Chrome Extension for Google Translate for an instant translation from German into English (though it still needs some work,  Herr Translator)

Back to actually working on LibreOffice- if Word and Powerpoint is all you do- save some money for Christmas and download it today from
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China biggest threat to Indian Software in 5 years: Indian Tech CEO

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An interview with a noted Indian Software CEO, mentions China the possible biggest threat in next 5 years at  http://www.thehindubusinessline.com/2010/10/13/stories/2010101353180700.htm

 

China could be the biggest threat to India in next five years, positioning itself as the lowest-cost manpower supplier in the IT sector by 2015, according to Mr Vineet Nayar, CEO, HCL Technologies.

“I believe it (China) is the biggest threat in the next five years that we are going to face…So India will have to up its game,” he told reporters on sidelines of ‘Directions’, the company’s annual town hall.

Terming China, as both “threat and opportunity”, Mr Nayar said that India will have to find alternate “differentiators” than the ones it currently has. Despite issues of language and the purported inability to scale-up, China has sharpened its technological and innovation edge, he added.

“Look at the technology companies from China…how does that fit in with the assumption that they (China) do not understand English or technology. They are producing cutting edge technology at a price which is lower than everyone else,” he said.

Manpower

By 2015, Mr Nayar said, China will be the lowest cost manpower supplier in IT sector to the world

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I wonder how he did his forecast. Did he do a time series analysis using a software, did he peer into his crystal ball, or did he spend a lot of time brainstorming with his strategic macro economic team on Chinese threat.

China has various advantages over India (and in fact the US)-

1) Big pool of reliable scientific manpower

2) State funded education in higher studies and STEM

3) Increasing exposure with the West-English speaking is no longer an issue. Almost 50 % of Grad Students in the US in STEM and certain sectors are Chinese and they not only retain fraternal ties with the motherland- they often remain un-assimilated with American Culture mainstream. or they have a separate interaction with fellow American Chinese and seperate with American Americans.

Chinese suffer from some disadvantages in software-

1) Communism Perception- Just because the Govt is communist and likes to confront US once a year (and India twice a month)- is no excuse for the hapless Chinese startup guy to lose out on software outsourcing contracts. unfortunately there have been reported cases where sneak codes have been inserted in code deliverables for American partners, just like American companies are forced to work with DoD (especially in software, embedded chips and telecom)

If you have 10000 lines of code delivered by your Chinese partner, how sure are you of going through each line of code for each sub routine or call procedure.

2) English- Chinese accent is like Chinese cooking. Unique- many Chinese are unable to master the different style of English even after years (derived from Latin and Indo European class of languages)

Sales jobs tend to go to American trained Chinese or to Westerners.

In Indian software companies, accent is a lesser problem.

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The biggest threat to Indian software in 5 years is actually Indian software itself- Can it evolve and mature to a product based model from a service only model.

Can Indian software partner with Chinese companies and maybe teach the Indian government why friendship is more profitable than envy and suspicion. If the US and China can trade enormously despite annual tensions, why cant Indian services do the same- if they lose this opportunity, US companies will likely bypass them and create the same GE/McKinsey style backoffices that started the Indian offshoring phenomenon.

3) Lastly- what did the poor American grad student do to deserve that even if devotes years to study STEM (and being called a Geek and Nerd) his job will get outsourced to India or China (if not now- in his 30s or worse in his 40s). Talk to any middle aged IT chap in the US who is middle class- and India and China would figure in why he still worries about his overpriced mortgage.

Unless the US wants only Twitter and Facebook as dominant technologies in the 21 st century.

Amen.

 

 

 

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