IBM revealed the availability of its Netezza Customer Intelligence Appliance today. The appliance empowers retailers to analyze petabytes of data about customer interactions regarding their products across multiple segments and points of interaction. Retailers can use the Netezza Customer Intelligence Appliance to obtain a 360 degree picture of customer behavior spanning the internet, mobile and purchases in brick and mortar stores. Based on the premise that 70 percent of a customer’s initial interactions with a product take place online, IBM partnered with Aginity to develop actionable analytics that assist retailers to understand and predict customer behavior by aggregating data from multiple channels. Leslie Weber, CIO of Bass Pro Shops, testified that the appliance had enabled the retailer to analyze data from “retail stores, boat dealerships, Internet and catalog sales, wholesale and hospitality,” thereby enabling it to “deliver more targeted promotions, circulars and catalogs to create a better shopping experience.” The Netezza Customer Intelligence Appliance is a SQL based Big Data product designed to deliver analytics on structured data. IBM is still in the process of integrating Netezza with its BigInsights, Hadoop-based appliance for analyzing structured and unstructured data.
IBM announced its first acquisition of 2012 on Wednesday by purchasing Green Hat, the software quality and testing company based in Wilmington, Delaware and London, England. Green Hat delivers a cloud based testing environment that enables developers to test software applications without the hassle of setting up the hardware and software required for the testing simulation environment. Green Hat’s cloud testing solutions are particularly useful for rapid application development with ultra-short development timelines such smartphones and tablet applications. Green Hat shrinks the percentage of software development costs devoted to testing and simulates a wide variety of IT infrastructures used in development processes. Upon acquisition, Green Hat will join IBM’s Rational Solution for Collaborative Lifecycle Management to enable enterprise customers to optimize their testing processes and accelerate software delivery. The acquisition of Green Hat is expected to improve IBM’s application delivery lifecycle in addition to that of its enterprise customers. Green Hat was founded in 1996 by Peter Cole, the company’s CEO. The majority of its 45 employees are based in London. Terms of the acquisition were not disclosed.
If 2011 was the year of Cloud Computing, then 2012 will surely be the year of Big Data. Big Data has yet to arrive in the way cloud computing has, but the framework for its widespread deployment as a commodity emerged with style and unmistakable promise. For the first time, Hadoop and NoSQL gained currency not only within the developer community, but also amongst bloggers and analysts. More importantly, Big Data garnered for itself a certain status and meaning in the technology community even though few people asked about the meaning of big in “Big Data” in a landscape where the circle around the meaning of “big” with respect to “data” is constantly being redrawn. Even though yesterday’s “big” in Big Data morphed into today’s “small” as consumer personal storage transitions from gigabytes to terabytes, the term “Big Data” emerged as a term that everyone almost instantly understood. It was as if consumers and enterprises alike had been searching for years for a long lost term to describe the explosion of data as evinced by web searches, web content, Facebook and Twitter feeds, photographs, log files and miscellaneous structured and unstructured content. Having been speechless, lacking the vocabulary to find the term for the data explosion, the world suddenly embraced the term Big Data with passion.
Below are some of the highlights of 2011 with respect to big data:
•Teradata finalized a deal to acquire Big Data player Aster Data Systems for $263 million.
•Yahoo revealed plans to create Hortonworks, a spin-off dedicated to the commercialization of Apache Hadoop.
•Teradata announced the Teradata Aster MapReduce Platform that combines SQL with MapReduce. The Teradata Aster MapReduce Platform empowers business analysts who know SQL to leverage the power of MapReduce without having to write scripted queries in Java, Python, Perl or C.
•Oracle announced plans to launch a Big Data appliance featuring Apache Hadoop, Oracle NoSQL Database Enterprise Edition and an open source distribution of R. The company’s announcement of its plans to leverage a NoSQL database represented an abrupt about face of an earlier Oracle position that discredited the significance of NoSQL.
•Microsoft revealed plans for a Big Data appliance featuring Hadoop for Windows Server and Azure, and Hadoop connectors for SQL Server and SQL Parallel Data Warehouse. Microsoft revealed a strategic partnership with Yahoo spinoff Hortonworks to integrate Hadoop with Windows Server and Windows Azure. Microsoft’s decision not to leverage NoSQL and use instead a Windows based version of Hadoop for SQL Server 2012 constituted the key difference between Microsoft and Oracle’s Big Data platforms.
•IBM announced the release of IBM Infosphere BigInsights application for analyzing “Big Data.” The SmartCloud release of IBM’s BigInsights application means that IBM beat competitors Oracle and Microsoft in the race to deploy an enterprise grade, cloud based Big Data analytics platform.
•Christophe Bisciglia, founder of Cloudera, the commercial distributor of Apache Hadoop, launched a startup called Odiago that features a Big Data product named WibiData. WibiData manages investigative and operational analytics on “consumer internet data” such as website traffic on traditional and mobile computing devices.
•Cloudera announced a partnership with NetApp, the storage and data management vendor. The partnership revealed the release of the NetApp Open Solution for Hadoop, a preconfigured Hadoop cluster that combines Cloudera’s Apache Hadoop (CDH) and Cloudera Enterprise with NetApp’s RAID architecture.
•Big Data player Karmasphere announced plans to join the Hortonworks Technology Partner Program today. The partnership enables Karmasphere to offer its Big Data intelligence product Karmasphere Analytics on the Apache Hadoop software infrastructure that undergirds the Hortonworks Data Platform.
•Informatica released the world’s first Hadoop parser. Informatica HParser operates on virtually all versions of Apache Hadoop and specializes in transforming unstructured data into a structured format within a Hadoop installation.
•MarkLogic announced support for Hadoop, the Apache open source software framework for analyzing Big Data with the release of MarkLogic 5.
•HP provided details of Autonomy IDOL (Integrated Data Operating Layer) 10, a Next Generation Information Platform that integrates two of its 2011 acquisitions, Vertica and Autonomy. Autonomy IDOL 10 features Autonomy’s capabilities for processing unstructured data, Vertica’s ability to rapidly process large-scale structured data sets, a NoSQL interface for loading and analyzing structured and unstructured data and solutions dedicated to the Data, Social Media, Risk Management, Cloud and Mobility verticals.
•EMC announced the release of its Greenplum Unified Analytics Platform (UAP). The EMC Greenplum UAP contains the The EMC Greenplum platform for the analysis of structured data, enterprise-grade Hadoop for analyzing structured and unstructured data and EMC Greenplum Chorus, a collaboration and productivity software tool that enables social networking amongst constituents in an organization that are leveraging Big Data.
The widespread adoption of Hadoop punctuated the Big Data story of the year so far. Hadoop featured in almost every Big Data story of the year, from Oracle to Microsoft to HP and EMC, while NoSQL came in a close second. Going into 2012, one of the key questions for the Big Data space concerns the ability of OpenStack to support Hadoop, NoSQL, MapReduce and other Big Data technologies. The other key question for Big Data hinges on the user friendliness of Big Data applications for business analysts in addition to programmers. EMC’s Greenplum Chorus, for example, democratizes access to its platform via a user interface that promotes collaboration amongst multiple constituents in an organization by transforming questions into structured queries. Similarly, the Teradata Aster MapReduce Platform allows business analysts to make use of its MapReduce technology by using SQL. That said, as Hadoop becomes more and more mainstream, the tech startup and data intensive spaces are likely to witness a greater number of data analysts trained in Apache Hadoop in conjunction with efforts by vendors to render Hadoop more accessible to programmers and non-programmers alike.
On Monday, IBM announced the release of the Infosphere BigInsights application for analyzing massive volumes of structured and unstructured data on its SmartCloud environment. The SmartCloud release of IBM’s BigInsights application means that IBM beat competitors Oracle and Microsoft in the race to deploy an enterprise grade, cloud based Big Data analytics platform. Over the past month, Oracle and Microsoft have revealed plans to release cloud based Big Data applications that leverage Apache Hadoop, although in the case of both companies, plans for a live release are scheduled for 2012. BigInsights was previously accessed via the IBM Smart Business Development and Test Cloud environment that served as the testing ground for IBM’s SmartCloud which was deployed in April 2011.
IBM developed its Big Data analytics platform because organizations across a number of verticals are drowning in the sea of unstructured data such as Facebook and Twitter feeds, internet searches, log files and emails. IBM’s press release quantified the size of the emerging big data space as follows:
Organizations of all sizes are struggling to keep up with the rate and pace of big data and use it in a meaningful way to improve products, services, or the customer experience. Every day, people create the equivalent of 2.5 quintillion bytes of data from sensors, mobile devices, online transactions, and social networks; so much that 90 percent of the world’s data has been generated in the past two years. Every month people send one billion Tweets and post 30 billion messages on Facebook. Meanwhile, more than 1 trillion mobile devices are in use today and mobile commerce is expected to reach $31 billion by 2016.
IBM customers in the banking, insurance and communications verticals are currently using BigInsights to more effectively understand trends from web analytics, social media feeds, text messages and other forms of unstructured data. The availability of BigInsights via IBM’s SmartCloud is likely to accelerate enterprise adoption of the product given enterprise familiarity with the SmartCloud offering and recent publicity about its October 12 upgrade. The deployment of BigInsights on SmartCloud also gives IBM early traction in the Big Data space, with competition from Amazon Elastic MapReduce from Amazon Web Services, EMC, Teradata and HP. Granted, Oracle and Microsoft are set to join the Big Data party soon, but IBM should have at least six months to consolidate its market positioning ahead of its West coast based competitors. The enterprise version of BigInsights is priced at 60 cents per cluster per hour whereas the basic version is free.
Key features of enterprise level IBM Infosphere BigInsights include the following:
• Advanced text analytics to mine massive amounts of textual data
• A spreadsheet-like interface called BigSheets that allows users to create and deploy analytics without writing code
• Web-based management console
• Jaql, a query language for querying structured and unstructured data through an interface that resembles SQL
In tandem with the release of BigInsights on the SmartCloud, IBM announced the availability of IBM Cognos Mobile on the iPad and iPhone. iPad users can now leverage Cognos to run analytics on data and obtain access to a suite of visually rich dashboards. The combination of Cognos on the iPad and BigInsights clearly indicates that portability of access to data analytics constitutes a key component of IBM’s big data strategy. The big question now concerns how Oracle and Microsoft will differentiate themselves from BigInsights in their respective, forthcoming Big Data offerings.