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Practical Applications of Enterprise Meta Data

  • November 01 2004, 1:00am EST

Applications of Enterprise Meta Data that Demonstrate Value

The good news is that more organizations are undertaking initiatives to address enterprise meta data. The downside, however, is that it still remains relatively uncommon overall. In fact, enterprise meta data - that is, all major reference and transactional data sets within an organization - is plagued with the perception that it is a technical luxury. Both information consumers and IT professionals view it more as an embellishment to their organization's information systems architecture than a critical element. Additionally, while most IT professionals believe that there is value in enterprise meta data, they struggle to articulate or convince their business clients of it. Information consumers, even if they understand the concepts of meta data, often consider it an IT amenity - not a business necessity. This narrow perspective of enterprise meta data hinders the ability of individuals to quantify or directly demonstrate the value of meta data, which, in turn, limits the adoption of enterprise meta data standards and integrated practical applications of it.

Calculating ROI can be challenging without broad assumptions, but practical applications of enterprise meta data can create business value. Focusing on the business capabilities instead of the technical aspects of enterprise meta data makes it easier to articulate the benefits to a business audience. In this column, three practical applications of enterprise meta data are explored to demonstrate value through the ability to provide information consumers with access to timely, relevant and accurate data.

Timely: Facilitating Rapid Response to Information Requests

As internal and marketplace changes impact a business, management needs to react for the betterment of the organization. However, to react, data is needed to make informed decisions. This requires information consumers to have access to data, which often includes new sets of data in order to develop greater insights to changes as they evolve. At times, this also requires new presentations of the information for monitoring, reporting, analysis and decision-making purposes. To support the business requirements in a timely manner, the organization needs an enterprise information environment that can enable individuals to respond and quickly develop the information solutions needed for decision making.

The business value that enterprise meta data provides is the ability for individuals to identify, assess and respond to information needs in a timely and efficient manner. This could mean the ability to create new information solutions in a matter of hours or days, rather than over weeks and months. In a dynamic economy, time is money. Every passing day that involves decisions being made "from the gut" - because of a lack of available information - is equivalent to playing darts in the dark. No organization can afford to risk its future because it lacks the ability to provide relevant, timely and accurate information to those who need it.

Relevant: Enhancing Operational Efficiencies

Operational efficiencies are created when manual processes are streamlined or automated. Transactional systems, such as enterprise resource planning (ERP), customer relationship management (CRM) and sales force automation (SFA), were created to automate business processes, thereby creating efficiencies in the manner in which business is conducted. As organizations implement new transactional systems or upgrade their existing systems, the effort involved in analyzing reference and transactional data for configuration purposes can be greatly reduced through the use of enterprise meta data. This translates into reduced cost and amount of time to implement new transactional systems or upgrade them.

In addition, enterprise meta data facilitates the ability to enrich data sets by synchronizing reference data between transactional systems. This, in turn, aids in the ability to develop information solutions that require data from disparate systems. For example, an enterprise meta data solution that addresses reference data such as customer name could be used by ERP, CRM and SFA systems to keep customer name synchronized between the three systems. Such capabilities are needed for near real-time analysis and monitoring, integrated reporting and providing individuals with a complete view of their customer.

Accurate: Creating Confidence

No one is immune to the data quality issues that arise from careless data entry or incorrectly matching data values during manipulations processes. Issues with data quality can have a significant impact on an organization, ranging from impaired decision making to inefficiencies created as individuals attempt to develop their own analysis outside the conventional processes because they lack confidence in the data.

From a data quality perspective, meta data can be used to validate data values and identify and correct errors. Meta data provides the data definitions, which are used to profile data. With data profiling, acceptable values are defined and used in the process of validating, correcting data entry errors and other data anomalies. The cost of inaccurate or poor quality data leads to impaired business decisions and information solutions that no one uses.

Meta data is a business necessity and an important element of the information enterprise. In addition to providing data definitions and lineage information to users, meta data facilitates comparative reporting and analysis, along with efficiencies in developing new information products. One example of meta data success comes from Intel Corporation, winner of Wilshire Conferences' 2004 Meta Data Best Practices award. Intel implemented an enterprise meta data repository solution and achieved an ROI/NPV of greater than $7 million in three years. One of the Intel IT group's internal customers for the meta data repository reported that for every dollar it invested in the repository solution, it saved six dollars on application development and maintenance costs. Intel's experience shows that it is possible to calculate the ROI of enterprise meta data and to sell end users on its benefits. To create and sustain an information enterprise, meta data must be viewed as an integral part of the information architecture.

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