Bill Inmon

This White Paper outlines the latest thinking from the World's pre-eminent expert on Data Warehousing & Business Intelligence - Bill Inmon. The paper looks at ways to integrate structured and unstructured data to optimise your business intelligence resources and capabilities.

CLICK HERE to download the paper in PDF format


Analytics have been around from the time the first computer program was written. Once the corporation began to generate data, there were financial analysts, sales analysts, marketing analysts and others anxiously awaiting to use that data in novel and creative ways. In the early days, data from applications was hard to come by, and the tools the analysts used to access and analyse the data were crude. As time passed and the volume of data grew, so grew the opportunity to use analytics to compete in the business arena.

And over time the world discovered the data warehouse as a foundation for analytic processing. The data warehouse contained data that was integrated, historical, and granular that was gathered from a host of legacy systems. The data warehouse proved to be an ideal foundation for the analysis of data. Data from the data warehouse was predictable and easy to access. And because data in the data warehouse was granular, it could be reshaped for many different purposes.


But over time it was recognised that business analysis – analytics – had a very fundamental limitation. That limitation was that analytics operated only on numerical data. While analysis of numerical data was quite useful, in fact, the corporation has massive amounts of data that are not in the form of numerical data. In the corporation there exists massive amounts of unstructured textual data – from emails, medical records, contracts, warranties, reports, call centers, and so forth. In fact, most estimates shows that 80% of the data in the corporation is in the form of text, not numbers.

And in that textual data that is owned by the corporation, there is a wealth of information. But there is a problem with unstructured, textual data. The problem with textual data is that it is not as neatly organized and as accessible as numerical data. Textual data just doesn’t lend itself to easy and facile analysis because the software and technology used for business analytics is almost 100% dedicated to handling well structured numeric data. The very disorder of the textual data defeats (or at least greatly hampers!) any attempt at accessing and analysing textual data in any sort of meaningful manner.

However there is technology that now is available that indeed is designed for textual analysis. That technology is FOREST RIM TECHNOLOGY Textual Foundation software. IDS is designed to allow the organisation to do textual analytics, for the first time.


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