Enterprise Data Management Best Practices

By Author: Martin Lobo
Total Articles: 355
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Regardless of the industry, strategic management of data and effective transformation of data into an actionable resource are common challenges. Most often than not, instead of resorting to a comprehensive data management solution, organizations tend to maintain multiple databases, spreadsheets etc. in numerous locations. This leads to several problems including data loss, lack of protection for sensitive data, delay in retrieving data at the time of need, etc. In turn businesses tend to hire consultants to take up data warehousing projects. However, a majority of these data warehousing projects fail, or do not deliver the expected outcome.

It is important to treat data as a strategic asset, and therefore data has to be efficiently managed throughout its lifecycle. As with any process, data management will be successful only when certain best practices are employed in the process of managing data:

• Data Awareness- It is important for every enterprise to be completely aware of the data that exists/is being generated on a daily basis. Without a clear understanding of the volume and nature of the data ...
... generated, no enterprise can put their data to good use. In order to be aware of the data, organizations should conduct a thorough data analysis and categorize data appropriately.
• Data Growth Management- Data is subject to growth. Massive growth of data can be a great challenge if an entity does not have the right means and expertise to manage data growth. It is therefore essential to adopt a data management solution that can efficiently control growth and store data in a well-organized and easily retrievable fashion.
• Test Data Management- Most often managing test data is an ongoing challenge for enterprises. Inefficient management of test data can cause a number of problems and impact productivity. Hence organizations should adopt an effective test data management solution that can streamline access and improve the testing process.
• Complete Access Control- One of the most common challenges in enterprises is controlling access to sensitive data. With data protection laws becoming more stringent, organizations are often unaware, or have no control over who has access to data. Adopting an integrated data management solution that can manage access control and ensure complete data security is therefore a must.
• Efficient Data Archiving- Data that is no longer in active use has to be stored in such a way that they can be accessed easily when the need arises and yet there are no redundant databases being created. This calls for a solution that can archive data in a centralized and integrated platform which is easily accessible at the time of need.

These and many other best practices are crucial to the effective management of data in an enterprise. The best means to ensure that these practices are adopted is to resort to an integrated and automated enterprise data management solution that can effectively control and manage data in an ongoing basis.

Also read about : IBM Optim Solutions, IBM Optim data privacy