SAS, Hadoop and big data

The term “big data” is all the rage right now, however the term “big” is relative. At SAS we have been called on to do “big data” projects and more importantly “big analytics” projects for many years now. In fact, we are the pioneers of analytics on “big data.”

There is nothing special about the volume of data, variety, or velocity of big data. To quote one of my colleagues, “It is the value.” We are finding that the tough part of big data is the same problem that faces any analytic project: First you have to formulate a problem that you expect to be solved with analytics, next the data needs to be filtered, aggregated and structured in a way to yield some value from analysis, and finally the effort required to harvest value from big data is worth the investment.

What is special about “big data” today is that storage has gotten cheap enough, and the parallel processing techniques have matured to a point where now we have options to extract value form data that previously were not manageable. Take various forms of machine generated data, like GPS system output, RFID tags or web logs. By itself, this data isn’t very valuable or even interesting. It isn’t until you put structure to the data through parsing, filtering, sorting, joining and aggregation that the data begins to provide some insights into how it might be leveraged.

As Rick Wicklin points out Obtaining the means and standard deviations of 100,000 variables is simple. Computing a complex regression model with 100,000 variables is much more challenging! … To truly appreciate the problem of big data one must consider not only the volume of data but also the computational complexity of the analysis.”

The many uses of Hadoop
Technologies like Hadoop have become all the rage recently. Hadoop is an open source Apache project that “is a framework that allows for the distributed processing of large data sets across clusters of computers using a simple programming mode.l”

For many, Hadoop is used as a sandbox to dump data of questionable value that is too big and unwieldy or simply too costly to be stored in a traditional RDBMS. Instead, many just load it into Hadoop then aggregate, filter, and structure the data to see IF there is value that can be harvested from the data. For others, Hadoop is used as an alternative to relational databases for data warehousing. The momentum and interest in Hadoop can’t be overlooked, check out the job-trends for Hadoop.

Hadoop Job Trends from

What is SAS doing with Hadoop?
At SAS, we have a number of initiatives around Hadoop to enable SAS users to access, load, process, visualize and analyze data stored in Hadoop. In the coming months we’ll have more to share but here is a sneak peak of what is to come:

  • SAS/Access interface to Hadoop – this will enable the SAS user to analyze data stored in Hadoop, it also opens up Hadoop data to processing from SAS client software like Data Integration Studio, Enterprise Guide,and Enterprise Miner. The access engine does more than just move data into and out of Hadoop; it also will enable processing to be “pushed-down” into Hadoop.
  •  SAS Data Integration Studio transformations – this is a new set of Hadoop transformations that will enable the DI Studio user to load and unload data to and from Hadoop, perform EL-T like processing with HiveQL and ET-L like processing with Pig Latin. Additionally, we are working on a Hadoop specific scoring transform that will enable models developed with Enterprise Miner to be deployed to Hadoop via DI Studio.

 Check back here for more updates on these and other projects, and definitely leave a comment if you have questions or ideas about SAS and Hadoop.


tags: big data, data integration, data storage, hadoop, sas/access


  1. Kenny
    Posted September 1, 2011 at 10:30 am | Permalink

    How do we contact the author?

    • Alison Bolen Alison Bolen
      Posted September 2, 2011 at 2:51 pm | Permalink

      I think Mike is currently out of the office, but I'll ask him to contact you after the Labor Day Holiday.

  2. Hugh Shinn
    Posted September 2, 2011 at 1:13 pm | Permalink

    When will the SAS/Access interface to Hadoop be available?

    • Bill Nguyen
      Posted September 16, 2011 at 6:19 pm | Permalink

      I have the same question!

  3. Syed Munir Hassan
    Posted September 14, 2011 at 6:32 pm | Permalink

    Will Hadoop be supported for comercial produicts like GreenPlum? Will SAS Access to GreenPlum be enhanced to support Hadoop? Are there any definite time lines yet?

    • Mike Ames Mike Ames
      Posted September 29, 2011 at 11:59 am | Permalink

      Hello Syed, you can take advantage of Greenplum's external table interface to HDFS today with SAS/Access

  4. Allison Anderson
    Posted September 21, 2011 at 12:59 pm | Permalink

    I'm also interested in when this will be available. Is there any more info?

    • Mike Ames Mike Ames
      Posted September 29, 2011 at 11:57 am | Permalink

      Hi Allison we expect to have more specific information to share with you in the coming months. Please watch this space and

  5. David Moors
    Posted December 23, 2011 at 8:38 am | Permalink

    Have we got an update on this topic? It's been months since the last post..

    • Rajeev Jain
      Posted February 6, 2012 at 11:26 am | Permalink

      SAS strategists/product managers - would you please post an update here asap or confirm that there is no reportable progress at SAS on the topic of accessing Hadoop from SAS.

    • Mark Troester Mark Troester
      Posted February 10, 2012 at 2:10 pm | Permalink

      Hello David - thanks for your interest, please see my comment. Thanks, Mark.

  6. James Anderson
    Posted January 23, 2012 at 2:49 pm | Permalink

    I am also eagerly waiting to hear an update on the status of using Hadoop with SAS/Access.

    • Mark Troester Mark Troester
      Posted February 10, 2012 at 2:10 pm | Permalink

      Hello James - thanks for your interest, please see my comment. Thanks, Mark.

  7. Mark Troester Mark Troester
    Posted February 10, 2012 at 2:07 pm | Permalink

    Sorry for the delay. We are heads down working on the Hadoop capabilities. These plans include the SAS/ACCESS Interface to Hadoop and the DI Studio transforms that Mike mentioned in his initial post. The overall roadmap goes well beyond this capability and will include elements of what we provide for other data sources – think in-database capability, pushing process into Hadoop, running SAS alongside or embedded with Hadoop, etc. These capabilities will be delivered in a phased approach with the SAS/ACCESS module leading the way. We will provide a more official announcement by the end of March.

    Mark Troester
    CIO/IT Thought Leader & Strategist

  8. Vijay
    Posted March 7, 2012 at 1:49 pm | Permalink

    Interesting and very exciting developments to include hadoop in the mix for data analytics. I think this will definitely reduce (if not eliminate) any limitations of SAS when it comes to handling very big data (peta bytes) and come up with useful information. I am sure all the marketing companies out there are thrilled.

  9. Posted December 18, 2014 at 1:12 am | Permalink

    Can SAS Enterprise Miner work with Hadoop?

4 Trackbacks

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  3. [...] Hadoop and emerging technologies are part of an overall big data analytics arsenal – Not only has Hadoop and similar technologies enabled organizations to more effectively capture and store massive amounts of data, these technologies have also served to broaden the appeal of analytics to the masses. Hadoop provides an efficient storage mechanism and processing framework for large volumes of data that may not have been captured previously. Hadoop can be used to complement existing data sources and processing approaches. tags: big data, data processing, hadoop, high performance analytics, high-performance computing, information management Bookmark on Delicious Digg this post Recommend on Facebook Share on FriendFeed share via Reddit Share with Stumblers Tweet about it Print for later Tell a friend « Worried about what might kill you? You should have attended Gartner Symposium Who’s right? Business or IT » [...]

  4. [...] Fern's complete post located here and note that there are many other blog posts on big data and Hadoop in the Information Architect blog. tags: big data, Big data analytics, hadoop, high performance [...]

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