Data Management: 5 Vital Best Practices to Follow
What is data management? Data management refers to the systematic organization and maintenance of data processes. It is concerned with the implementation of policies and procedures that puts organizations in control of their business data. Data management tools are used to minimize the risks and costs of legal complications, regulatory non-compliance, and security breaches. It also […]
What is data management?
Data management refers to the systematic organization and maintenance of data processes. It is concerned with the implementation of policies and procedures that puts organizations in control of their business data. Data management tools are used to minimize the risks and costs of legal complications, regulatory non-compliance, and security breaches. It also provides access to accurate data whenever required, without ambiguity or conflict, consequently avoiding miscommunication.
Data management best practices
Effective data management is all about solving business issues and improving data trustworthiness through the effective and seamless integration of information with business processes. Here are five data management best practices to follow:
Focus on data quality
In the run for attaining better data management, several companies often tend to ignore the importance of data quality. Poor quality, outdated, or inaccurate data are major barriers to managing a company’s data successfully. Hence, cleaning up data before it is used in any analytics processes is essential. Issues including inconsistent and non-standard formats to spelling error can result in poor-quality data, so having the right data management tools to identify and fix these issues are vital.
As data volumes grow, it’s likely that so too will the amount of duplicated data across the business. Particularly in environments that are transitioning from highly siloed structures to a more centralized system, redundant data takes up space and slows down processing. Therefore, one of the key data management best practices includes identifying duplicate data and deleting it without impacting any processes that rely on it. Spotting data that’s no longer relevant and removing it are also crucial data management best practices.
Prioritize data security
Data security should always be a critical element of focus during data management. Also, with the new government regulations on data security and security breach, this has become more important than ever before. Companies must also ensure that they access adequate control and encryption over the data, and the physical security of data must not be overlooked.
Enable easy access
Possessing enormous amount of data becomes invaluable to any business unless the relevant personnel is able to access it easily as and when they require it. Developing effective access controls is always a tricky balance between convenience and security. However, it is well worth taking the time to ensure that each individual has the level of access that’s appropriate for their role, rather than implementing blanket policies which are either too restrictive for some people or may allow others to access data they should not be given access to.
Formulate a recovery plan
Every company is now transforming into a data-driven business. One of the most damaging problems a firm could encounter is to lose access to their own database. Whether it is a hardware failure or power issues, or even human error, any interruption to a company’s data flow can render an organization completely unable to do business. So, any data management strategy becomes incomplete until it includes a clear backup and recovery plan that clearly indicates how often different types of data need to be backed up and what steps need to be taken to recover them in the case of any mishap.