hadoop

In the 9 months or so since I last wrote about Revolution Analytics they have released a new version of Revolution R Enterprise 7. This is focused on delivering “Write once deploy anywhere.” R, of course, continues to expand in popularity with the recent Rexer Data Mining survey (reviewed here) putting the percentage of data [...]

i4C Analytics is focused on delivering advanced analytic applications for specific industries and business decisions. These packaged analytic applications apply predictive analytics in real-time in a highly automated environment. The applications use automated analytic model creation as well as allowing data scientists and predictive analytic professionals to integrate their own models to solve the business problems [...]

Attending the Teradata Partners conference and getting a briefing on the Teradata UDA – Unified Data Architecture.  The UDA brings together Teradata’s traditional Enterprise Data Warehouse (EDW) products, its Teradata Aster discovery platform and a variety of partner technologies. UDA was announced in 2012 and they have been adding integrations and partnerships since then. Specifically [...]

It’s been a while since I got an update from Cloudera (last time was in 2010, here). Since then, obviously, much has changed. Back in 2010 Cloudera was focused on storage and batch processing against this data with little focus on advanced analytics. Today, Cloudera has added support for real-time SQL queries through improvements in [...]

FICO has just released Model Builder 7.4, the first “Big Data” release of their analytic modeling tool (I reviewed 7.2 here and the 7.4 press release is here). Four things make this release: Text analytics and semantic scorecards High Volume Processing with Hadoop – including algorithms moved to MapReduce R Integration And drifting away from Big [...]

As part of an ongoing expansion of our ecosystem mapping to include more Hadoop-based products I recently got an update from Datameer. Datameer was founded back in 2009 by Stefan Groschupf, who was one of the original contributors to Nutch, the open source project that spun off Hadoop. Prior to starting Datameer, he and the [...]

I got an update from SAP on their Predictive Analytics products. Back in December I got a briefing on the Windows client (that went GA in November 2012) and the SAP HANA (SAP’s in-memory database) libraries related to it. SAP, like me, is seeing a lot of demand for predictive analytics with existing clients needing [...]

As part of some ongoing research on support for PMML I recently spoke with Concurrent. Concurrent is an enterprise software company focused on simplifying Big Data development on Hadoop. The company’s core product is called Cascading. This is a free, open-source, development framework for Apache Hadoop designed to let developers build sophisticated data processing applications [...]

The second in my series on the impact of Big Data on Decision Management Systems: The impact of Variety. Big Data involves adding more types of data, from more sources inside and outside of the organization, to your analytic toolkit. Social, mobile, local and cloud data sources are exploding and organization must find ways to [...]

Well that’s a wrap for the IBM Big Data Analytics Analyst Insight 2013 event. I’ve blogged 13 sessions and attended a couple of others plus had dinner at the Hockey Hall of Fame and seen the Stanley Cup. A few closing thoughts: Like IBM I believe that the power of Big Data lies in its [...]

Next up is a session on the new infrastructure and platforms for analytics. IBM’s view (and I would agree) is that use cases for analytics are evolving to increasingly combine traditional structured data and newer unstructured, more dynamic, “Big Data” sources. As customers change the time frames in which they need to make decisions (more [...]

Jason Verlen and Bernard Spang took one of the breakout sessions on analytic innovations. IBM, as noted yesterday, sees a progression of analytics from descriptive to predictive, prescriptive and ultimately cognitive. The purpose, of course, of big data and analytics is to drive better decisions. Managing big data is a necessary step but acts only [...]

Bob Picciano and Les Rechan came up next to discuss Big Data and Analytics: Fueling Competitive Advantage in the New Era of Smart. Five years ago IBM launched the Smarter Planet initiative. On a smarter planet, they say, everything is connected and instrumented and this is reflected in the explosion of Big Data. To drive value [...]

It’s been over a year since I last got updated on Zementis (their 3.5 release of ADAPA and PMML Universal Plug-in). Since then they have been busy adding support for new platforms and signing new partnerships. Most recently they have announced a strategic alliance between Zementis and FICO, something Zementis sees as a big win for [...]

Stuart Wells, the CTO of FICO, came up to give the keynote and talk about FICO’s big cloud announcements: FICO Cloud-based Decision Management Platform (announcement here) FICO Analytic Cloud (announcement here and sign up here) Customer engagement applications  on this cloud platform announcement here (discussed also in this blog post). Stuart began with a couple of stories. [...]

Josh Prismon and Matt Beck came up next to walk through a 5 step plan for Big Marketing – Marketing in the era of Big Data. Admit you have a problem Stop interrupting and start understanding Create a personal dialogue guided by analytics Continuously improve your decisions Push out by building network effects The context for this [...]

Phil Francisco came up to talk about the new PureData System for Hadoop. He began by pointing out that just because something is open source does not mean there are not real costs involved. To make Hadoop adoptable and usable for enterprises, easier consumption is needed. Hence the PureData Hadoop appliance designed to simplify building, [...]

Next up is Inhi Suh focusing on the Big Data platform announcements. She began by reiterating the various use cases Bob mentioned earlier: Enrich your information base by analyzing more data faster Improve customer interaction with richer view of customer Reduce risk and prevent fraud in security/intelligence Optimize infrastructure and monetize data Gain IT efficiency [...]

I am attending the IBM Big Data Management launch today and will do my best to blog it as it happens. Steve Mills, on video, kicked things off. Steve began by pointing out that the price performance boost of recent years has made a whole new class of use cases reasonable. In particular more data [...]