Big data is a hot topic. While the volume and variety within big data are a significant issues, Gartner, among others, notes that the real issue is making sense of big data and finding patterns in it that help organizations make better business decisions. I could not agree more and this is where BI tools come into play. Gartner also predicts that the global market for BI software will grow by 9.7% in 2011. The worldwide market will reach $10.8 billion by the end of the year, with further growth expected all the way through until 2014.
One of the issues I have with many BI tools is that you have to set up what you are looking for before you start and thus miss the opportunity to find relationships beyond the anticipated. Endeca is tackling this issue in several ways. First, it allows for a greater dialog between business analysts and IT as BI applications are set up so that a more iterative process can occur and unanticipated questions can emerge through this dialog. Second, the actual applications can supply suggestions to the user through unanticipated facets to further explore their topics of interest. I recently spoke with Endeca’s Chief Strategist, Paul Sonderegger, to understand what they are offering and will cover these issues and others in more detail here.
Endeca offers two main product lines, Endeca InFront™ for customer experience management and Endeca Latitude®, for enterprise BI use. Both are built on their MDEX Engine® technology, a patented hybrid search analytical database. InFront allows for more sophisticated customer explorations in Web sites. For example, if you are looking for a faucet at the Home Depot site, it will ask you key questions about what type you need going beyond your input. This can save you a lot of frustration when you later go to install the facet and reduce the number of returns that Home Depot has to contend with. The same technology powers Latitude and we spent most of our time discussing this enterprise BI platform.
Paul said that they refer to Latitude as agile BI using the traditional sense of the word. Although, as he describes the Latitude development process, it also seems to be in the spirit of agile software development. It enables rapid iterations and better collaboration between IT and the business user. Paul gave an example from a Fortune 100 aerospace manufacturer. They created an application that provides answers for aircraft technicians. The application pulls together content from a vast diversity of sources to answer questions that cannot be anticipated in advance.
This application was developed in eight weeks with business and IT working closely together. The process trigged many new ideas from the business side as they saw possibilities unfold. They estimated that the application ended up about 90% different from the original vision.
Endeca operates in three steps. First diverse data is brought together. Then it is made available to people with business expertise and not simply the technical experts. Finally, the tool is made to adapt to a constantly changing set of requirements. You can create comprehensive data visualizations such as the one shown below.
Latitude is based on a three-tier architecture as show below. The foundation for data retrieval is provided through the Latitude Information Integration Suite. It can make use of many third party tools to connect with both structured and unstructured data. The middle layer is the MDEX Engine. It is a patented hybrid search analytical database that can let the incoming data drive the identification of facets. This allows for the avoidance of pre-determined data fields as I mentioned up front. The top layer is the Latitude Studio that allows for drag and drop application creation.
Paul talked about how their client, Toyota Motor Sales (MTS), USA, was able to use Latitude to better respond to their crisis over the massive product recall. They could find where the pedal assemblies were installed, a data point they had not known in advance needed tracking, and tie together such critical data sources such as customer claims and government agency reports. They were better able to answer the many customer questions that continued to arise as the situation unfolded.
Paul said Endeca operates on three principles. First no data is left behind. Second guidance is offered to the user in turning data into decisions. Third, the agile development that brings IT and the business users closer.
Paul gave me an example of how the data-generated facets can provide useful guidance to the business user. A home goods manufacturer had been purchasing about 130,000 kinds of commodities for $8 billion a year. They felt they were buying too many different kinds of items as the engineers, and not purchasing, control the ordering process. So they added a new facet, preferred suppliers where they got better deals. The engineers were still in charge but now they were armed with ways to both save money and consolidate suppliers. The company saved $300 million in direct costs the first year and decreased suppliers by 30%. This allowed for more concentrated purchasing and the ability to negotiate better deals.
This makes a lot of sense to me and it is useful to see the tangible benefits from allowing for the unanticipated in business intelligence. Gartner also likes them and Toyota’s use of Endeca Latitude made the automaker a semifinalist in Gartner’s BI Excellence Awards.
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