SAS Data Mining 2009 Las Vegas

I am going to Las Vegas as a guest of SAS Institute for the Data Mining 2009 Conference. ( Note FCC regulations on bloggers come in effective December but my current policies are in ADVERTISE page unchanged since some months now)

With the big heavyweight of analytics, SAS Institute showcases events in both the SAS Global Forum and the Data Mining 2009

conference has a virtual who’s- who of partners there. This includes my friends at Aster Data and Shawn Rogers, Beye Network

in addition to Anne Milley, Senior Product Director. Anne is a frequent speaker for SAS Institute and has shrug off the beginning of the year NY Times spat with R /Open Source. True to their word they did go ahead and launch the SAS/IML with the interface to R – mindful of GPL as well as open source sentiments.

. While SPSS does have a data mining product there is considerable discussion on that help list today on what direction IBM will allow the data mining product to evolve.

Charlie Berger, from Oracle Data Mining , also announced at Oracle World that he is going to launch a GUI based data mining product for free ( or probably Software as a Service Model)- Thanks to Karl Rexer from Rexer Analytics for this tip.

While this is my first trip to Las Vegas ( a change from cold TN weather), I hope to read new stuff on data mining including sessions on blog and text mining and statistical usage of the same. Data Mining continues to be an enduring passion for me even though I need to get maybe a Divine Miracle for my Phd to get funded on that topic.

Also I may have some tweets at #M2009 for you and some video interviews/ photos. Ok- Watch this space.

ps _ We lost to Alabama #2 in the country by two points because 2 punts were blocked by hand which were as close as it gets.

Next week I hope to watch the South Carolina match in Orange Country.


Advanced Analytics on Multi-Terabyte Datasets- Conferences

Some news on Data Mining 2009 by Aster Data –

SAS and Aster Data to Present “Advanced Analytics on Multi-Terabyte Datasets” at M2009 in Las Vegas – Oct. 26-27
Learn how the tight coupling of SQL and MapReduce provided by Aster Data creates new ‘big data’ analytics opportunities when combined with SAS. Aster Data will exhibit throughout the event.

And also a nice  webcast by Curt Monash on the same Big Data topic-

Mastering MapReduce Webinar Series, Session 1
“Big Data Reality: The Role of MapReduce in Big Data Management and Analysis”- Oct. 15
Industry analyst Curt Monash explains the basics of MapReduce, key uses cases, and which industries and applications are heavily using MapReduce. Topics include recommendations for integrating MapReduce in an enterprise business intelligence and data warehousing environment.


Here is a brief synopsis on the Aster Data ( Sponsored Big Data Summit  ( )which I attended-

  • A Plan for Large Scale Data Analytics: How to Utilize Aster nCluster and Hadoop in a Symbiotic
    Relationship to Support Processing in Excess of 100 Billion Rows Per Month
    – Michael Brown and Will Duckworth
    (EVP, Software Engineering, comScore, Inc. and Director, Software Engineering, comScore, Inc.)

This talked of the special needs of Com Score in handling big data and why Map Reduce and Hadoop seem to be the cost effective solutions for big big data while RDBMS seems stuck in the middle of middle data. Broadly informative on the statistical challenges of the future given the explosion of data as well.

  • Making Sense of Hadoop – Its Fit With Data Warehouses – Colin White
    (President and Founder of BI Research)

Colin brought a nice perspective on the open source Hadoop vis a vis the Properietary packages and the traditional DBMS. His perspective on the solution is no software is perfect for all needs while all softwares that sell have their own good points while the converging solution could be a heterogeneous solution of the above.

  • MapReduce Inside a Database System – When and How Case Studies from ShareThis, Specific Media, and Other – Tasso Argyros (Chief Technology Officer and Co-Founder of Aster Data)

This was a more detailed look at the Big Product Launch ( the Hadoop Connector) by Tasso and an interesting look at time series analysis using nPath rather than SQL . Interesting given the ongoing convergence analytics and business intelligence.

Also Tasso lived up to his presenting charm with an excellent pitch on nPath (as his interview said ).

  • Large-Scale Analytics at LinkedIn – Jonathan Goldman
    (Former Principal Scientist at LinkedIn)

This was nice given Jonathan’s perscpective ( he has Phd In Physics) and now does consulting for LinkedIn while maintaining his interests in education- the special needs for social media websites, designing experiments on the fly with huge real time datasets as well as some interesting visualizations (like India and America have the second biggest cross country Li connections after USA- UK. Apparently Linkedin ( ) does not sound so good when translated in Chinese ( AT Dinner I learnt from a fellow Chinese student that China censors Facebook – sigh!).

  • Networking Mixer: Beer, wine, hot hors d’oeuvres

I got interviewed ( AFTER) I had mixed some Beer and Wine for myself. The Video interview which was the first video interview I have given ( You know- I have taken SOME interviews by Email and plan to do some more while in Vegas for the Data Mining 2009  with SAS

They are still editing that interview 😉

—That was all – you need to send me a Facebook invite to see the rest of the NY trip or better still just join the Facebook page of Decision Stats at

After two weeks I hope to have some more coverage on Data Mining 2009 while at the same time enjoying my much needed Fall Break-  Life at University at Tennessee is looking up ( since we beat Georgia 45-19 🙂 )


The Big Data Event- Why am I here?

I am here braving New York’s cold weather, as I prepare for this evening’s events. If you follow this blog closely ( including the poems) ,it is a welcome change— New York is a nice city people are friendly if you ask them nicely and the bus is a great way to watch the city – best of all I like the crowds which I have grown used while living in India.

Why Am I here?

Because the topics that are discussed here are cutting edge to the point that I cannot find anyone willing to teach me Hadoop and Map-Reduce while in University and at the same time teach me statistics on them as well ( as in how do we do a K Means clustering on a 1 terabyte dataset).

I asked the organizers on what makes the event special ( every event promises special Mojo after all).

This is what they said-

What is the unique value proposition of the event that will help developers and both current and potential customers-

The essence of the event is to explore new innovations in massively-parallel processing data warehousing technology and how it can help companies gain more insight from their data.  Applications include fraud detection, behavioral targeting, social network analysis, better predictions/forecasting, bioinformatics, etc.  We are exploring how MapReduce and Hadoop can be integrated into the enterprise IT system to help evolve data warehousing/BI/data mining

and to put it even more nicely’

The industry’s first big data event, Big Data Summit ‘09, being held this evening in New York City, will showcase Hadoop’s fit with MPP data warehouses. Aster Data will be presenting alongside Colin White, President and Founder of BI Research, Mike Brown of comScore Inc., and Jonathan Goldman, who represents LinkedIn.”

That’s good enough for me to drop into Roosevelt Hotel on East 45th Street at around 6 pm for some reluctant networking ( read: beers). 5 years ago whie working for GE , I used to run queries using SAS on a 147 million row database (the size of the DB) and wait 3 hours for it to come back. Today that much data fits very snugly in my laptop. How soon will we have Terabyte level personal computing, and Petabyte level business computing and the challenges it poses to standard statistical assumptions and synching of hardware and software- Big Big Data is an interesting area to watch.

Interview Shawn Kung Sr Director Aster Data

Here is an interview with Shawn Kung, Senior Director of Product Management at Aster Data. Shawn explains the difference between the various database technologies, Aster’s rising appeal to its unique technological approach and touches upon topics of various other interests as well to people in the BI and technology space.


Ajay -Describe your career journey from a high school student of science till today .Do you think science is a more lucrative career?

Shawn: My career journey has spanned over a decade in several Silicon Valley technology companies.  In both high school and my college studies at Princeton, I had a fervent interest in math and quantitative economics.  Silicon Valley drew me to companies like upstart procurement software maker Ariba and database giant Oracle.  I continued my studies by returning to get a Master’s in Management Science at Stanford before going on to lead core storage systems for nearly 5 years at NetApp and subsequently Aster.

Science (whether it is math, physics, economics, or the hard engineering sciences) provides a solid foundation.  It teaches you to think and test your assumptions – those are valuable skills that can lead to a both a financially lucrative and personally inspiring career.

Ajay- How would you describe the difference between Map Reduce and Hadoop and Oracle and SAS, DBMS and Teradata and Aster Data products to a class of undergraduate engineers ?

Shawn: Let’s start with the database guys – Oracle and Teradata.  They focus on structured data – data that has a logical schema and is manipulated via a standards-based structured query language (SQL).  Oracle tries to be everything to everyone – it does OLTP (low-latency transactions like credit card or stock trade execution apps) and some data warehousing (typically summary reporting).  Oracle’s data warehouse is not known for large-scale data warehousing and is more often used for back-office reporting.

Teradata is focused on data warehousing and scales very well, but is extremely expensive – it runs on high-end custom hardware and takes a mainframe approach to data processing.  This approach makes less sense as commodity hardware becomes more compute-rich and better software comes along to support large-scale MPP data warehousing.

SAS is very different – it’s not a relational database. It really offers an application platform for data analysis, specifically data mining.  Unlike Oracle and Teradata which is used by SQL developers and managed by DBAs, SAS is typically run in business units by data analysts – for example a quantitative marketing analyst, a statistician/mathematician, or a savvy engineer with a data mining/math background.  SAS is used to try to find patterns, understand behaviors, and offer predictive analytics that enable businesses to identify trends and make smarter decisions than their competitors.

Hadoop offers an open-source framework for large-scale data processing.  MapReduce is a component of Hadoop, which also contains multiple other modules including a distributed filesystem (HDFS).  MapReduce offers a programming paradigm for distributed computing (a parallel data flow processing framework).

Both Hadoop and MapReduce are catered toward the application developer or programmer.  It’s not catered for enterprise data centers or IT.  If you have a finite project in a line of business and want to get it done, Hadoop offers a low-cost way to do this.  For example, if you want to do large-scale data munging like aggregations, transformations, manipulations of unstructured data – Hadoop offers a solution for this without compromising on the performance of your main data warehouse.  Once the data munging is finished, the post-processed data set can be loaded into a database for interactive analysis or analytics. It is a great combination of big data technologies for certain use-cases.

Aster takes a very unique approach.  Our Aster nCluster software offers the best of all worlds – we offer the potential for deep analytics of SAS, the low-cost scalability and parallel processing of Hadoop/MapReduce, and the structured data advantages (schema, SQL, ACID compliance and transactional integrity, indexes, etc) of a relational database like Teradata and Oracle.  Often, we find complementary approaches and therefore view SAS and Hadoop/MapReduce as synergistic to a complete solution.  Data warehouses like Teradata and Oracle tend to be more competitive.

Ajay- What exciting products have you launched so far and what makes them unique both from a technical developer perspective and a business owner perspective

Shawn: Aster was the first-to-market to offer In-Database MapReduce, which provides the standards and familiarity of SQL and databases with the analytic power of MapReduce.  This is very unique as it offers technical developers and application programmers to write embedded procedural algorithms once, upload it, and allow business analysts or IT folks (SQL developers, DBAs, etc) to invoke these SQL-MapReduce functions forever.

It is highly polymorphic (re-usable), highly fault-tolerant, highly flexible (any language – Java, Python, Ruby, Perl, R statistical language, C# in the .NET world, etc) and natively massively parallel – all of which differentiate these SQL extensions from traditional dumb user-defined functions (UDFs).

Ajay- “I am happy with my databases and I don’t need too much diversity or experimentation in my systems”, says a CEO to you.

How do you convince him using quantitative numbers and not marketing adjectives?

Shawn: Aster has dozens of production customers including big-names like MySpace, LinkedIn, Akamai, Full Tilt Poker, comScore, and several yet-to-be-named retail and financial service accounts.  We have quantified proof points that show orders of magnitude improvements in scalability, performance, and analytic insights compared to incumbent or competitor solutions.  Our highly referenceable customers would be happy to discuss their positive experiences with the CEO.

But taking a step back, there’s a fundamental concept that this CEO needs to first understand.  The world is changing – data growth is proliferating due to the digitization of so many applications and the emergence of unstructured data and new data types.  Like the book “Competing on Analytics”, the world is shifting to a paradigm where companies that don’t take risks and push the limits on analytics will die like the dinosaurs.

IDC is projecting 10x+ growth in data over the next few years to zetabytes of aggregate data driven by digitization (Internet, digital television, RFID, etc).  The data is there and in order to compete effectively and understand your customers more intimately, you need a large-scale analytics solution like the one Aster nCluster offers.  If you hold off on experimentation and innovation, it will be too late by the time you realize you have a problem at hand.

Ajay- How important is work life balance for you?

Shawn: Very important.  I hang out with my wife most weekends – we do a lot of outdoors activities like hiking and gardening.  In Silicon Valley, it’s all too easy to get caught up in the rush of things.  Taking breaks, especially during the weekend, is important to recharge and re-energize to be as productive as possible.

Ajay- Are you looking for college interns and new hires what makes aster exciting for you so you are pumped up every day to go to work?

Shawn: We’re always looking for smart, innovative, and entrepreneurial new college grads and interns, especially on the technical side.  So if you are a computer science major or recent grad or graduate student, feel free to contact us for opportunities.

What makes Aster exciting is 2 things –

first, the people.  Everyone is very smart and innovative so you learn a tremendous amount, which is personally gratifying and professionally useful long-term.

Second, Aster is changing the world!

Distributed systems computing focused on big data processing and analytics – these are massive game-changers that will fundamentally change the landscape in data warehousing and analytics.  Traditional databases have been a oligopoly for over a generation – they haven’t been challenged and so the 1970’s based technology has stuck around.  The emergence of big data and low-cost commodity hardware has created a unique opportunity to carve out a brand new market…

what gets me pumped every day is I have the ability to contribute to a pioneer that is quickly becoming Silicon Valley’s next great success story!


Over the past decade, Shawn has led product management for some of Silicon Valley’s most successful and innovative technology companies.  Most recently, he spent nearly 5 years at Network Appliance leading Core Systems storage product management, where he oversaw the development of high availability software and Storage Systems hardware products that grew in annual revenue from $200M to nearly $800M.  Prior to NetApp, Shawn held senior product management and corporate strategy roles at Oracle Corporation and Ariba Inc.

Shawn holds an M.S. in Management Science and engineering from Stanford University, where he was awarded the Valentine Fellowship (endowed by Don Valentine of Sequoia Capital).  He also received a B.A. with high honors from Princeton University.

About Aster

Aster Data Systems is a proven leader in high-performance database systems for data warehousing and analytics – the first DBMS to tightly integrate SQL with MapReduce – providing deep insights on data analyzed on clusters of low-cost commodity hardware. The AsternCluster database cost-effectively powers frontline analytic applications for companies such as MySpace, aCerno (an Akamai company), and ShareThis.

Running on low-cost off-the-shelf hardware, and providing ‘hands-free’ administration, Aster enables enterprises to meet their data warehousing needs within their budget. Aster is headquartered in San Carlos, California and is backed by Sequoia Capital, JAFCO Ventures, IVP, Cambrian Ventures, and First-Round Capital, as well as industry visionaries including David Cheriton and Ron Conway.

Big Data in the Big Apple


I am all set to go to the Big Data summit on OCTOBER    1 in  New York

It talks  on Aster Data and their  passion in success in crunching data faster than the speed of thought. Interesting stuff includes Map/Reduce , Hadoop, Big Data and people who have experience in them.

As  a graduate student who is about  to  start his thesis in

statistical ( Regression , Em Algorithm, K Means Clustering) computation (Chunking , and aggregation) of :

MIXED data

  • (structured row and column numbers) and

in a  computing  environment that

  • uses HPC nodes and a MIXED GRID of desktops AND IDLE WEB SERVERS on  THE INTERNET

seminars like these are the only way to learn cutting edge stuff.

I would also be present in SAS Data Mining 2009 Conference in Las Vegas in October. Hope to see you there.

At both the conferences I would be interviewing people ( preferably using Video and someone to ask the questions- my spoken accent is very bad). Also rather sheepishly- I will be giving an interview at the Big Data Summit. I have given only two interviews till now-

One for my mentor Vincent Granville, founder Analyticbridge here in April 2008 and the other was on my poetry .

So I guess the interview is on the other side 🙂

Understanding Map/Reduce

if you think Map/Reduce was another buzz word that some boys cooked up while in their cheerless lab in Stanford, you need to take another deeper, hard look at the technology that will promise to overthrow current industry dynamics in the Big Data category.

Here is a white paper by Aster Data alumni- Aster has the same pedigree as Google and is on it’s way to make other Big Data companies into Kilo Data and Mega Data.

One of the best things of this paper is it actually helps answer the question – which all other databases are there and how does M/R compare with them.



VLDB ’09 2009, Lyon, France. Copyright 2009 VLDB Endowment, ACM 0000000000000/00/00.


View more documents from ajayohri.

A special thanks to Tasso CTO, Aster Data for pointing this paper to me. SQL/ MR turned 1 year old on August 25 this year.

Interview Tasso Argyros CTO Aster Data Systems

Here is an interview with Tasso Argyros,the CTO and co-founder of Aster Data Systems ( ) .Aster Data Systems is one of the first DBMS to tightly integrate SQL with MapReduce.


Ajay- Maths and Science students the world over are facing a major decline. What would you recommend to young students to get careers in science.

[TA]My father is a professor of Mathematics and I spent a lot of my college time studying advanced math. What I would say to new students is that Math is not a way to get  a job, it’s a way to learn how to think. As such, a Math education can lead to success in any discipline that requires intellectual abilities. As long as they take the time to specialize at some point – via  postgraduate education or a job where they can learn a new discipline from smart people – they won’t regret the investment.

Ajay- Describe your career in Science particularly your time at Stanford. What made you think of starting up Asterdata. How important is it for a team rather than an individual to begin startups. Could you describe the startup moment when your team came together.

[TA] – While at Stanford I became very familiar with the world of startups through my advisor, David Cheriton (who was an angel investor in VMWare, Google and founder of two successful companies). My research was about processing large amounts of data on large, low-cost computer farms. A year into my research it became obvious that this approach had huge processingpower advantages and it was superior to anything else I could see in the marketplace. I then happened to meet my other two co-founders, Mayank Bawa & George Candea who were looking at a similar technical problem from the database and reliability perspective, respectively.

I distinctly remember George walking into my office one day (I barely knew him back then) and saying “I want talk to you about startups and the future” – the rest has become history.

Ajay- How would you describe your product Aster nCluster Cloud Edition to omebody who does not anything beyond the Traditional Server/ Datawarehouse technologies. Could you rate it against some known vendors and give a price point specific to what level of usage does the Total Cost of Ownership in Asterdata becomes cheaper than a say Oracle or a SAP or a Microsoft Datawarehosuing solution.

[TA]- Aster allows businesses  to reduce the data analytics TCO in two interesting ways. First, it has a much lower hardware cost than any traditional DW technology because of its use of commodity servers or cloud infrastructure like Amazon EC2. Secondly, Aster has implemented a lot of  innovations that simplify the (previously tedious and expensive) management of the system, which includes scaling the system elastically up/down as needed – so they are not paying for capacity they don’t need at a given point in time.

But cutting costs is one side of the equation; what makes me even more excited is the ability to make a business more profitable, competitive and efficient through analyzing more data at greaterdepth. We have customers that have cut their costs and increased their customers and revenue by using Aster to analyze their valuable (and usually underutilized) data. If you have data – and you think you’re not taking full advantage of it – Aster can help.

Ajay- I have always have this one favourite question.When can I analyze 100 giga bytes of data using just a browser and some statistical software like R or advanced forecasting softwares that are available.Describe some of Asterdata ‘s work in enhancing the analytical capabilities of big data.

Can I run R ( free -open source) on an on demand basis for an Asterdata solution. How much would it cost me to crunch 100 gb of data and make segmentations and models with say 50 hours of processing time per month

[TA]- One of the big innovations that Aster does it to allow analytical applications like R to be embedded in the database via our SQL/MapReduce framework. We actually have customers right now that are using R to do advanced analytics over terabytes of data.  100GB is actually on the lower end of what our software can enable and as such the cost would not be significant.

Ajay- What do people at Asterdata do when not making complex software.

[TA]- A lot of Asterites love to travel around the world – we are, after all, a very diverse company. We also love coffee, Indian food as well as international and US sports like soccer, cricket, cycling,and football!

Ajay- Name some competing products to Asterdata and where Asterdata products are more suitable for a TCO viewpoint. Name specific areas where you would not recommend your own products.

[TA]- We go against products like Orace database, Teradata and IBM DB2. If you need to do analytics over 100s of GBs or terabytes of data, our price/performance ratio would be orders of magnitude better.

Ajay- How do you convince named and experienced VC’s Sequia Capital to invest in a start-up ( eg I could do with some server costs coming financing)

[TA]- You need to convince Sequoia of three things. (a) that the market you’re going after is very large (in the billions of dollars, if you’re successful). (b) that your team is the best set of people that could ever come together to solve the particular problem you’re trying to solve. And (c) that the technology you’ve developed gives you an “unfair advantage” over incumbents or new market entrants.  Most importantly, you have to smile a lot! J


About Tasso:

Tasso (Tassos) Argyros is the CTO and co-founder of Aster Data Systems, where he is responsible for all product and engineering operations of the company. Tasso was recently recognized as one ofBusinessWeek’s Best Young Tech Entrepreneurs for 2009 and was an SAP fellow at the Stanford Computer Science department. Prior to Aster, Tasso was pursuing a Ph.D. in the Stanford Distributed Systems Group with a focus on designing cluster architectures for fast, parallel data processing using large farms of commodity servers. He holds an MsC in Computer Science from Stanford University and a Diploma in Computer and Electrical Engineering from Technical University of Athens.

About Aster:

Aster Data Systems is a proven leader in high-performance database systems for data warehousing and analytics – the first DBMS to tightly integrate SQL with MapReduce – providing deep insights on data analyzed on clusters of low-cost commodity hardware.

The Aster nCluster database cost-effectively powers frontline analytic applications for companies such as MySpace, aCerno (an Akamai company), and ShareThis. Running on low-cost off-the-shelf hardware, and providing ‘hands-free’ administration, Aster enables enterprises to meet their data warehousing needs within their budget.

Aster is headquartered in San Carlos, California and is backed by Sequoia Capital, JAFCO Ventures, IVP, Cambrian Ventures, and First-Round Capital, as well as industry visionaries including David Cheriton, Rajeev Motwani and Ron Conway.


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