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Posted on April 13th, 2010 by Steve Wooledge

It looks like Aster Data isn’t the only company hoping to demystify advanced analytics as a growing number of organizations try to decide whether to dip their toe in the water or dive in completely. There was an interesting article from Doug Henschen of Intelligent Enterprise last week on their launch of the “Advantage in Analytics” TechCenter.

The main impediments to growth for the analytics market have been “lack of awareness, skills and a demand for fact-based decision-making within organizations,” Doug writes. This preceded our announcement of the Aster Analytics Center and MapReduce.org earlier this week to support those very goals.

The Aster Analytics Center provides best practices, and ready-to-use analytics solutions to jump-start development of advanced in-database analytics. Further, www.mapreduce.org provides valuable information to companies interested in understanding MapReduce-based analytics and learning how other companies have built rich data-driven applications using MapReduce and SQL-MapReduce. We expect these resources, along with Intelligent Enterprise’s “Advantage in Analytics” TechCenter, to be integral in increasing awareness and skills. And as more organizations learn the benefits, demand will become nearly universal. Hats off to Intelligent Enterprise for supporting these goals.

Today Aster took a significant step and made it easier for developers building fraud detection, financial risk management, telco network optimization, customer targeting and personalization, and other advanced, interactive analytic applications.

Along with the release of Aster Data nCluster 4.5, we added a new Solution Partner level for systems integrators and developers.

Why is this relevant?

Recession or no-recession, IT executives are constantly challenged. They are asked to execute strategies based on better analytics and information to improve effectiveness of business processes (customer loyalty, inventory management, revenue optimization, ..), while staying on top of technology-based disruptions and managing (shrinking or flat) IT budgets.

IT organizations have taken on the challenge by building analytics-based offerings  leveraging existing data management skills and increasingly taking advantage of MapReduce, a disruptive technology introduced by Google and now being rapidly adopted by mainstream enterprise IT shops in Finance, Telco, LifeSciences, Govt. and other verticals.

As MapReduce and big data analytics goes mainstream, our customers and ecosystem partners have asked us to make it easier for their teams to leverage MapReduce across enterprise application lifecycles, while harvesting existing IT skills in SQL, Java and other programming languages.  The Aster development team that brought us the SQL/MapReduce innovation, has now delivered the market’s first integrated visual development environment for developing, deploying and managing MapReduce and SQL-based analytic applications.

Enterprise MapReduce developers and system integrators can now leverage the integrated Aster platform and deliver compelling business results in record time (read how ComScore delivers 360 degree view of digital world to enterprise customers, Full Tilt Poker gains the upper hand tackling online fraud using Aster).

We are also teaming up with leaders in our ecosystem like MicroStrategy to deliver an end-to-end analytics solution to our customers that includes SQL/MapReduce enabled reporting and rich visualization. Aster is proud to be driving innovation in the Analytics and BI market and was recently honored at  MicroStrategy’s annual customer conference.

I am delighted with the rapid adoption of Aster Data’s platform by our partners and the strong continued interest from enterprise developers and system integrators in building big data applications using Aster. New partners are endorsing our vision and technical innovation as the future of advanced analytics for large data volumes.

Sign up today to be an Aster solution partner and join the revolution to deliver compelling information and analytics-driven solutions.

Closing the Gap for Big Data and Fast Insights within Banking
Posted on November 11th, 2009 by rpai


Last week I attended Bank of America’s Technology Innovation Summit in Silicon Valley. In attendance were leading technology executives from Bank of America who outlined needs and challenges for the global banking giant. BofA’s annual IT spend is greater than $5 Billion, serving  almost 59 million, or one out of every two U.S. households and distribution strength of about six thousand branches, 18,000 ATMs and 24 million online banking customers, and more than 3,000 customer touches every second. Key themes discussed involved Cloud computing, Information Management, Security, Mobility and Green IT. And as I sat through the panel discussions and spoke to some of the IT leaders, it became evident that underpinning all the major business and IT initiatives for the global bank was a central theme – Lots of data, need for better and faster insights.

A senior BofA IT executive stated “Broad BI and data mining remain objectives, not realized goals”. There was a high level of interest in analytics and a big drive to be information-driven across business units.

Clearly, for a large bank like BofA, the business drivers exist. For example, the consumer channels executive was interested in understanding consumer behavior across different channels. In a saturated marketplace for retail customers and facing stiff competition from Chase (now owns WaMu), Wells Fargo (now owns Wachovia), BofA is keenly interested in strengthening its bond with its existing customer base.  With thousands of interactions per second, every interaction with the customer is an opportunity to learn more about customer behavior and customer preferences.

 In the credit card division, early detection of fraud patterns can translate into big savings for a market that is undergoing dramatic transformation due to reforms mandated by Congress. 

On the IT front, BofA has lots of existing investments in BI tools and data management software.

So where is the gap? Why are BI/data mining unrealized goals?

The answer lies in re-thinking and challenging the status quo in data management and analytic application development in today’s big data IT environments. Google, Amazon, and other innovators are leading this and it is only a matter of time before leaders in the financial services industry follow suit. A new mandate and architecture for big data applications  is emerging.

This new class of analytic applications will require a strategic investment in infrastructure that embraces assimilating advanced analytics processing right next to the terabytes to petabytes of enterprise data for key business initiatives including

  • Customer service effectiveness to predict customer requirements as well as fully understand customer relationships across branch office, ATM, online, and mobile channels
  • Ability to respond faster to regulators or to management and driving decisions based on insights driven from accurate, timely data

Broader, more pervasive BI and richer Analytics is on the threshold of becoming a reality!

Posted on June 9th, 2009 by Peter Pawlowski

The Aster SQL/MapReduce framework allows developers to push analytics code for applications closer to the data in the database, without dealing with the headaches of extracting and analyzing data outside of the database. We’ve supported a variety of language from day one, including Java, Python, and Perl. Today we’re pleased to announce official support for the .NET family of languages via Mono, an excellent open source .NET implementation. This will allow developers who use .NET languages like C# and VB (and, of course, F#) to more easily leverage nCluster for massively parallel analytics.

Our .NET support is enabled through our Stream SQL/MR function, which allows users to process data via a simple streaming interface: provide a program that reads rows from the console (stdin) and writes rows back to the console (stdout). Let’s consider a simple C# program called Tokenize, which splits incoming rows into tokens, and then output each token (one per line):

To run this program over data stored in nCluster, a developer just needs to compile the above Tokenize.cs into Tokenize.exe with a C# compiler (in our case, the Mono C# compiler gmcs). With the compiled executable in hand, one command in our terminal client will install it in nCluster. The program can be then invoked from SQL. The below example will run the program over all the rows in the documents table, outputting a table with a single column (token). Each row in the result of the query will correspond to a single token in the input documents.

It’s as simple as that. We hope our new .NET support will enable an ever-broader group of developers take advantage of SQL/MR, our in-database analytics technology!If you’re interested in learning more, please check out a host of new resources around our implementation of MapReduce within Aster nCluster including example applications and code.

A big congratulations to our CTO and Co-Founder, Tasso Argyros, who has been recognized as one of BusinessWeek’s Best Young Tech Entrepreneurs for 2009. I’d have given him a run for his spot, but I am over-the-hill and probably too old to run the distance - I wish they’d start a list for Best Entrepreneurs under the age of 40 :-)

Tasso’s hard work, dedication, confidence and vision have been a huge part of our success to date, and we know they will be a big part of great things ahead for Aster. Congratulations to you, and to all the other great companies that made the list as well; it’s an honor for them to be recognized alongside you.

Posted on February 11th, 2009 by Steve Wooledge

As a follow-on to the introductory nPath post, I wanted to share a little more depth on the nPath SQL syntax and a more sophisticated example which can be applied in click-stream or Web analytics. I’ll try to keep it concise for my colleagues who don’t want the pretty marketing bow . ;-)

SEO and SEM are critical traffic drivers for just about any consumer-facing website. Third party analytics offerings such as Google Analytics or Omniture can provide great turn-key package of canned reports. However, certain deep analytics on sequential events are simply out of the reach of not only these outsourced analytics services, but also in-house Web analytics data warehouses implemented on traditional solutions such as Oracle or SQL Server.

For example, suppose we are interested in the optimization of our website flow in order to retain and engage visitors driven to us by SEO/SEM. We want to answer the question: for SEO/SEM-driven traffic that stay on our site only for 5 or less pageviews and then leave our site and never return in the same session, what are the top referring search queries and what are the top path of navigated pages on our site? In traditional data warehouse solutions, this problem would require a five-way self-join of granular weblog data, which is simply unfeasible for large sites such as Myspace.

With the Aster nPath SQL/MR function, this problem can be expressed in a straightforward query that is executed in a very efficient manner in just a single pass over the granular data. The query below returns the top combinations of referral query string (of the entry page of the visit to our site) and on-site navigation path of up to 5 pages before leaving the site:

SELECT entry_refquerystring, entry_page || “,” || onsite_pagepath as onsite_pagepath, count(*) as session_count FROM nPath(
ON ( select * from clicks where year = 2009 )
PARTITION BY customerid, sessionid
ORDER BY timestamp
PATTERN ( ‘Entry.Onsite+.OffSite+$’ )
SYMBOLS (
domain ilike “mysite.com” and refdomain ~* “yahoo.com|google.com|msn.com|live.com” as Entry,
domain ilike “mysite.com” as OnSite,
domain not ilike “mysite.com” as OffSite
)
MODE( NONOVERLAPPING )
RESULT(
first(page of Entry) as entry_page,
first(refquerystring of Entry) as entry_refquerystring,
accumulate(page of Onsite) as onsite_pagepath,
count(* of Onsite) as onsitecount_minus1
)
)
WHERE onsitecount_minus1 < 4
GROUP BY 1,2
ORDER BY 3 DESC
LIMIT 1000;

Posted on January 22nd, 2009 by Mayank Bawa


We are very excited that OnMedia has just announced Aster as one of the winners of the AlwaysOn OnMedia 100, a listing of the top 100 private, emerging technology companies in the advertising, publishing, marketing, branding and PR spaces. As a technology enabler for many media clients like MySpace, Invite Media, aCerno, Aggregate Knowledge (and others soon to be announced), we understand the pressures that media faces today. Our customers are a great testament to the fact that Aster has the best solution to meet the rapidly changing needs of media, to keep up with the huge amounts of data they are managing for themselves and their end clients. More info on Aster’s win here.

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