CMOD – The Bridge to Big Data Analytics

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Production-level, transaction records – generally printed reports, statements, invoices and other documents lack the traditional “field and record” layout as well as the parameters needed to specifically identify and classify them.

The data within these documents can be described as semi-structured or loosely-structured and experts estimate that it represents more than 80% of the data within enterprises. It is also the most trusted source of data within the organization. Generally produced from “line-of-business” systems, it is the true record of business activity, customer billing and collections as well as goods and services ordered and paid for. The production of these documents and therefore the data contained within them is validated, vetted and proven over time.

IBM® Content Manager OnDemand (CMOD) is a security-rich, efficient system in which to store these and a variety of other documents. Designed, from the start, to be a high-performance repository for transactional documents because its scalability is practically limitless, it maintains a highly accurate, easy to use index methodology for finding documents and it’s a long-standing, proven performer in enterprise, critical business applications.

Over the last several years, many enterprises that use CMOD have extended the utility of the installation by using CMOD as the “back-end” of customer facing portals that allow end user customers the ability to provide access to invoices, statement and correspondence. This repository of internal and customer facing documents has been able to “jump start” any number of customer self-service initiatives by enabling the delivery of current as well as historical documents.

Because of the aforementioned attributes of robustness and scalability, the typical long-standing CMOD installation has many billions of documents stored within it. These invoice statement and billing documents have a wealth of information contained within them.

In today’s world of analytic and big data projects, a case can be made that the original big data repository is, in fact, Content Manager OnDemand. Although information contained in CMOD is not in the traditional structured format of field and record, all organizations collect and retain data from semi-structured resources in the normal course of daily business.

Much effort has been expended to maintain and categorize these various semi-structured digital assets. Extracting insight from the records contained within those platforms has been difficult and time-consuming. Because records consist of so much diverse information, in an unstructured format, it can be difficult to acquire and narrow in on the information required to deliver the insight needed to augment strategic decision making.

By extracting appropriate data elements from reports, invoices and statements, a big data picture of business functions can be derived – allowing the business to gain insight into customer behavior, purchasing patterns, and more. In other words, CMOD archival and retrieval system is a Big Data content source itself, and it provides accurate, trusted information that can be used either by itself or in conjunction with a larger “Big Data Analytics” program. While Big Data Analytics is important, Good Data is critical. Some things never change – garbage in, garbage out.

Next time we’ll take a look at what a major financial institution accomplished in answering a compliance audit by using the valuable data stored within hundreds of millions of customer facing documents stored in CMOD. In the meantime, we invite you to join us at one of the CMOD workshops happening in a city near you. You can register here.

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VP of Worldwide Sales, Crawford Technologies, Inc.

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