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Strategies for Managing Data Effectively

written by: Bruce Tyson • edited by: Ginny Edwards • updated: 2/13/2011

Collecting accurate and relevant data is important, but gathering data does not by itself guarantee the success of a project. Storing and analyzing data and then applying the lessons learned are requirements for managing data effectively.

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    An Overview of Data Management

    Data management is the system in place within an organization that collects data and uses it as an integral part of that organization's Data Parameter operations. Included in this system is the architecture for collecting and storing data, the procedures for accessing and analyzing data, and the ability to apply data in a profitable manner. Strategies for effective data management will address every aspect of the data management system to make sure it serves as a valuable asset to the organization.

    Image Credit: Wikimedia Commons/Ivan Akira

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    Understanding Data Sources and Quality

    Effective data management demands that data come from reliable sources and contains relevant information. Without assessing these aspects of the data management system, an organization can wrongly rely on data that is incomplete, inadequate, irrelevant, or inaccurate.

    Effective data management requires that the systems used by different departments are identified and inventoried. The profiles of master categories such as customer data, vendor data, product data, financial data, and operating data should be documented so that data is consistently defined and that methods for accessing data across platforms is in place. The value of data often becomes diluted when an organization does not know what data it has and is unaware of where it is kept. Also, redundant, conflicting, and outdated data can cause complications that frustrate organizational efforts to utilize data in routine operations.

    An effective data management strategy will constantly work to qualify and unify the sources of data within the organization to make it more accessible and therefore, more valuable.

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    Unifying Data as an Asset

    Many organizations have a functional approach toward data, employing distinct systems in every department. With such a low-level concept of data, sales, purchasing, product development, customer service, and other sectors often operate without the benefit of seeing the big picture. For example, technical support may routinely have information that should directly affect sales, purchasing, and product development, that never gets to the people who can act on it to make better products, provide better service, or acquire better materials.

    Data management strategies that recognize data as an organizational asset will work to implement high level systems that allow the entire company to act and react on data in real time.

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    Data Maintenance

    Managing data effectively requires that an organization regularly review and update its data assets on a regular basis. Often, inaccuracies and inconsistencies enter into a system, complicating efforts to act on data contained therein. For example, different agents may abbreviate street names differently, resulting in multiple, differing records for the same contact. Similarly, product data often becomes non-uniform with some metrics recorded for some products, but not others.

    Data security is another important requirement for effective data management. A system that secures data used by the organization from unauthorized entities is necessary to maintain its value and to avoid any related legal or ethical liabilities.

    A strategy that constantly monitors the input of data and then periodically scans it for compliance with established standards will be part of an effective data management strategy that increases its accessibility and value.

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    Wrapping It Up

    Managing data effectively will help organizations become more efficient and mature as their data assets are leveraged for cost savings and revenue growth.