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IBM Netezza Analytics 2.0 and Big Data

May 8, 2012

If this was a start-up, that would be good for at least $100M...

Analytics. Big Data. At a recent conference I attended, one of the keynote speakers stated that start-ups with “Analytics” in their business description are getting about two times the average valuation by the venture capital community, but those that combine “Analytics” and “Big Data” are getting about ten times the valuation. Netezza is no longer a start-up - we at Netezza have been helping customers with analytics and big data since our beginnings over ten years ago. And then there was that little matter of our acquisition by IBM, itself at a pretty healthy valuation. There isn’t really anything new about big data but the name. Companies have had to deal with larger amounts of data, more types of data, and faster generated or changing data since data has existed. Now because the term has gone viral, all the data management vendors are trying to wedge it into every press release and all their social media posts to catch the search engines. (Vendors in other segments seem to be looking for ways to get in on that game. Maybe we’ll see Kellogg’s “Big Data Crunch” on our supermarket shelves soon.)

We believe in choice in analytics. There is a lot of press about Hadoop as the tool for big data. Hadoop can be a very useful tool for analyzing data, but it certainly is not the only tool and it is sometimes not the best tool. With our IBM Netezza Analytics software, we enable our customers to use MapReduce within our analytics appliance and we have connectors (BigInsights, Cloudera) that allow interfacing to full-blown Hadoop outside of the appliance. We also support the use of R (through our partnership with Revolution Analytics) and SAS (through our partnership with SAS) and SPSS and matrix and pre-built in-database analytic and the embedding of custom algorithms written in a wide variety of languages (including Perl, Python, Lua, Java, C, C++, and even FORTRAN).

Our customers who are using IBM Netezza Analytics experience three main benefits:

  • Predict with more accuracy
  • Deliver predictions faster
  • Respond rapidly to changes

We will explore each of those in upcoming blog postings.

I’m happy to announce the availability of IBM Netezza Analytics 2.0.  We’ve added some new pre-built in-database analytics and features in this version and we continue to expand our analytics ecosystems further and deeper with partners like Revolution Analytics, SAS, SPSS, Fuzzy Logix, and our newest analytics partner, Zementis.

Version 2.0 highlights include:

  • Logistic Regression, GLM and Time Series analysis
  • Enhanced model and metadata management
  • New and enhanced Statistics
  • New language support for Lua and Perl
  • Enhanced Hadoop MapReduce functionality
  • New algorithm integration (push-back) with SPSS

Again, we believe in choice. We want to empower our customers to run the advanced analytics that they want to run on the data they have in their IBM Netezza appliances and that means providing a robust set of parallelized, scalable pre-built analytics in addition to working with those vendors who offer the best-in-breed analytics solutions. IBM Netezza Analytics is included with every IBM Netezza data warehouse appliance we ship or, if you already have your IBM Netezza appliance, you can download it from IBM’s Passport Advantage.

Take a look at the new data sheet and contact your friendly neighborhood IBM sales representative to explore how IBM Netezza Analytics can help you make more sense out of your big data. And for those of you at start-ups, maybe we can help you with your valuation.


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