With the combined Business Objects/Inxight technology offering, users will have streamlined access to information inside and outside the organization, both unstructured (such as e-mails, attachments, electronic documents, notes fields and Web content) and structured (databases and data warehouses).
John Schwarz, CEO of Business Objects, says, “Business intelligence (BI) solutions have traditionally focused on structured data discovery, however 80 percent of corporate information is stored in an unstructured format. With the acquisition of Inxight, Business Objects will be the first to provide customers with a BI platform that can streamline all of their internal and external information assets—both structured and unstructured data. This will dramatically accelerate our customers’ ability to locate hidden intelligence in search results that might otherwise be overlooked.”
Ian Bonner, president and CEO of Inxight, supports Schwarz’s claim with a focus on the user, saying, “I’m a firm believer that technology for technology’s sake is nothing. I believe that you must add value to the user—the customer—and improve their work lives by giving them better and more complete information. The merging of business intelligence capabilities from Business Objects with our search and text analytics capabilities is absolutely the right thing ultimately for the customer. The good news is that we are going to be able to satisfy the emerging needs of users so they may be more productive and make better decisions.”
Inxight software allows customers to access, cluster and be alerted to relevant information contained in the open Web, deep Web (patent databases, SEC filings), subscription and internal sources. Its understanding of all major languages, including English, Arabic, German, French, Farsi, Spanish and Simplified Chinese, powers the ability to automatically identify and tag named entities in a document, such as people, companies, places, weapons, addresses and dates. It also identifies events—such as M&A and travel activities—as well as relationships between entities.
Capable of identifying out of the box more than 35 types of information within a document, entity extraction can also be customized to recognize pattern- or list-based, industry- or customer-specific entities, events and relationships, such as SKUs, drug compounds, terrorists, etc.
A key Inxight competitor, TEMIS, issued a statement soon after the Business Objects/Inxight deal was announced. In it, Eric Brégand, TEMIS CEO, responds, “With this recent market change, TEMIS becomes the largest pure text analytics independent software vendor.” TEMIS also announced a special migration program for customers and partners potentially impacted by the acquisition of Inxight by Business Objects.
Bonner of Inxight, however, says, “We still hold the largest installed base and have the most satisfied customers in the text analytics market segment and, combined with the financial muscle and resources of Business Objects, we will only be able to service our
The pure-play text analytics software market is fast being absorbed into other software infrastructure and vertical market provider segments. A few months earlier, Reuters announced its acquisition of text analytics provider ClearForest.
“There definitely is a rollup of the text analytics market segment,” says Barak Pridor, ClearForest CEO and new executive VP of text analytics at Reuters. “The acquisition of ClearForest by Reuters is mostly a vertical integration in the financial segment, as we not only service information providers, but have a great many financial industry segment users, and that is the key market segment Reuters services. The Business Objects acquisition of Inxight is more of a horizontal integration—it gives Business Objects new technology capabilities they can deliver across market segments.”
Gerry Campbell, president/global head of search & content technologies at Reuters, says, “Reuters’ history is all about using technology to improve customer value and create competitive advantage. Text analytics, for Reuters, is about extending our competency in content by creating a coherent knowledge set—bringing structured (fielded data, including metadata such as ticker symbols, etc.) and unstructured content (free text) together into complete picture for
“For instance, financial news stories have a direct impact on related securities. By connecting companies and events in news stories quickly and accurately with the underlying instruments, we can provide a direct link between news and other financial information. This saves time and cost for our customers, while eliminating any guesswork. Our goal is to unlock Reuters’ content to make markets more efficient and people more knowledgeable.”