Unified Business Intelligence:
Voices from the Next Frontier
It would be difficult to write anything about business intelligence this month without mentioning the IBM/Ascential deal. The deal illustrates customers' demand for more integration of the analytics and information management stack and the increasingly strategic role this infrastructure plays in the enterprise. The Ascential deal complements IBM's other recent acquisitions of Venetica, SRD and Alphablox, and represents clearly that end-to-end information management is at the heart of unified business intelligence.
Ascential's goal was to provide end-to-end data integration: from any source to any target, at any time, at any latency. Through a layer of complex meta data management Ascential was able to achieve this goal - arguably in spades (Informatica and Ab Initio might disagree). Ascential is now part of a company with an even broader vision of business intelligence and data integration. IBM, it seems, is determined to integrate the various layers of the business intelligence stack from database to data analysis and all the ETL, data quality and meta data translation layers in between. This most recent acquisition begs the question of what will customers demand next in terms of integration as they strive to better hear the voice of the customer and their market.
The Next Frontier
To understand how the information management stack will evolve, it is important to understand what pain is spurring businesses to improve their infrastructures. Just as poor customer relationship management and Y2K drove improved analytics and ETL integration respectively, currently the executive suite is suffering from a lack of early-warning visibility. High-profile episodes such as Enron, Vioxx, Firestone, SCO/Linux and Pierre, bring the more expensive but routine costs of customer churn, product failures, inefficient innovation, and poor market and operational insight into the boardroom.
Businesses require a more unified view of their structured data and unstructured content. Unified business intelligence seeks to bring data from unstructured sources (RSS feeds, e-mails, Word docs) for analysis alongside traditional, structured data from relational data sources. That landscape is packed with every type of application - from search engines such as Google, to text analysis tools, to custom-built portal solutions - all with the vision of leveraging information hidden in unstructured content to help solve issues around quality, innovation, loyalty, control and risk. The problem is, according to analysts at IDC, that the technologies for managing and accessing text and structured data have evolved separately and, consequently, they do not mix well together.
What is Needed
By high technology standards, the business intelligence space is mature. Such a well-evolved technology brings with it entrenched solution sets, methodologies and standards. Successfully bringing the value of text to business intelligence will require as little deviation from traditional processes and tools as possible. While several tools provide access to unstructured content, the winners in this race will be the companies that manage to provide a means of extracting relevant information from unstructured text and structure it for seamless analysis and query by traditional, structured data analysis tools. In short, unified business intelligence applications must provide the benefits of integrating unstructured content while leveraging existing BI investments and without adding complicated steps for the end user.
What Won't Work
Creating small islands of application specific extraction and analytic tools or larger islands of content-centric architectures impedes the unified view of business intelligence that IBM and other platform vendors are moving towards. Next generation search and content management systems only highlight the current limitations of integrating and analyzing unstructured content with structured data. Likewise, custom-built unified analytics solutions lack the scalability and integration capabilities that enterprises require.
What Will Work
To access the information hidden within unstructured data, business analysts will need sophisticated text analysis solutions that essentially "structure" data through a process that involves mining text and applying an intelligent mark-up system to key entities such as person, organization, location, as well as detailed facts or events embedded within free-form text such as news articles, Web surveys and HTML documents. Once structured, this information can be used to drive stand-alone analytics applications or be fed into a company's existing data marts and combined with structured data to provide more comprehensive business intelligence.
This discussion is not hypothetical. The next frontier of unified business intelligence is already being explored and settled by industry leaders anxious to gain a competitive advantage, manage risk and improve customer loyalty. Publishers, such as Elsevier Science and Thomson Financial have been using text analytics solutions for years to improve the intelligence value of their products. Automotive manufacturers are beginning to integrate unstructured technology into their business intelligence stack to help identify the root causes of warranty claims and improve their products. Similarly, consumer goods manufacturers are using text analytics to analyze customer comments and better understand consumer needs, preferences and suggestions. Whether it is insurance fraud, retention of cell phone customers, improved clinical trials, faster equity analysis or national defense, applications the integration of text into the existing business intelligence stack.
The IBM/Ascential deal is significant to the business intelligence sector for many reasons; primarily, it represents a coalescing of the "old guard." Through this acquisition IBM has shored up its solution set for structured business intelligence and is better prepared than ever to tackle the new frontier of unified business intelligence. The addition of Ascential provides an almost universal ability to integrate structured data. It will be interesting to watch how the company moves forward to integrate the unstructured half of the BI stack. The stakes are high, but so are the potential rewards. The successful unification of structured data and unstructured content means faster innovation, better CRM, improved financial insight, reduced costs and better performance.
For more information on related topics visit the following related portals...
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Dr. Ronen Feldman. PhD is one of the leading minds in the field of text mining and draws on years of experience in the development of knowledge discovery systems and text mining applications. Feldman is responsible for ClearForest's technical business development, rapid prototyping, and the research and development of new products. In particular, he is in charge of the wireless segment and development of language models for new vertical domains. Feldman serves as a consultant to leading Israeli companies and serves on the program committees of AAAI, KDD, PKDD and SIGIR. He is often an invited speaker in academic and industrial conferences, and he is a senior lecturer in the Mathematics and Computer Science Department of Bar-Ilan University in Israel.
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