Business Intelligence

This demand for disruptive solutions challenges the long-held misconceptions about BI. Companies today must pay new attention to the overlooked unstructured sources of actionable enterprise data, which can dramatically simplify the demands of providing the right information to the right person at the right time.

Unstructured Data:
Separating Value from Hype Traditional BI systems typically rely on structured information (databases), which usually comprises only a small portion of all enterprise information. However, the vast majority of enterprise information is found in unstructured data sources; that is, information sources outside of databases. Much hype has been devoted to the concept of harvesting unstructured data, while technology writers still disagree about what unstructured data is and whether it has any value at all.

Experts have a wide range of definitions for unstructured data. Some include any sort of potentially informative document, even hand-written notes. Others dismiss unstructured data as an oxymoron and as a gibberish term that is not helping anyone solve their data problems. The debate reveals an important kernel of truth: For an unstructured data source to be of authentic value as an enterprise BI source, the process of transforming a certain unstructured data source into actionable structured data must be very simple and reliable, without exception.

This key criterion eliminates the distraction of more exotic unstructured data sources, such as freeform text, handwritten notes, etc., and enables us to recognize that the single most valuable supply of unstructured data in the enterprise is the existing reports and business documents already produced by every organization.

Organizations running enterprise resource planning (ERP) systems, for example, already own a library of existing canned reports. All of the work is already done for them  there is no coding to do, no security to work out, and all the information that they need is embedded within the delivered standard report.3 For example, SAP offers canned reports numbering in the several thousands.

Organizations maintaining a huge historical database of an ERP (or other core system) often face a frustrating reality: most of the effort and cost associated with their complex BI tool is intended to allow the organization to create and work with customized views of the very same enterprise data that already appears within various existing ERP report outputs.

Putting Existing Reports to Work as a BI Source
Clearly, the existing reports already produced within the organization comprise its greatest unstructured data asset and putting those reports to use should be a top priority. The problem many organizations face is that conventional wisdom still says that reports cannot be used as a source of BI because they are static they do not allow the end user to ask questions about the data and see different data views. Thanks to report mining technology, this is no longer true. Existing reports can now easily become live, actionable data for easy analysis, with no new programming required.

Report mining enables the intelligent recognition and parsing of data within existing reports and business documents - typically in plain text or PDF format - into a valid data table, complete with optional new calculated fields of data and database lookups that allow the inclusion of additional data located elsewhere. Report mining also facilitates sorting, filtering, combination with other data and summarization with subtotals and grand totals, as well as easy export to a data cube, Excel, PDF, online form and other applications that allow users to analyze the information. Reports, particularly when intelligently indexed and archived within a report mining-enabled enterprise report management system, can become a wellspring of easily accessed and manipulated data for programming-free BI.

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