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Creating an effective data quality management plan is essential in keeping the quality of data accurate and reliable. Unreliable data and errors in reporting cause a significant loss in revenue each year for a large number of businesses. Regular cleaning out and checking systems can help to resolve certain issues; but setting up a data quality management plan that is well structured and reliable will help to substantially reduce the incidents of bad data. Before you begin, you will need to carry out a data quality assessment in order to ascertain the current state of your data.

Data Quality Management Plan Reduced Bad Data

In today’s online world, businesses frequently receive bad data from social media and other external sources. In order to make sure that your business is able to benefit from the most effective data quality management, it is best to have your data quality tool accessed independently so that bad data that is buried can be successfully discovered. Once you have the full in-depth assessment you will be in a better position to plan and meet data quality objectives that are specific to the individual needs of your business.

Put in place a good data quality fire wall. This will help you to keep your data from being contaminated by bad data. An effective data quality fire wall will detect bad data at the point it enters your system, and will block it. This keeps your internal data clean and clear. Bad data can damage the existing good data and will make it impossible to successfully gather actionable information and clear business insights. Building a fire wall is the first step once you have your assessment done.

Considering the sheer volume of data most businesses today have to deal with, it is essential to prioritize specific types of data for quality management. It is generally impossible to check every piece of data that comes into your system. A Business Intelligence solution can help you to identify and prioritize those types of data that are most important. A BI system will isolate those specific types of data for processing and quality management as a main priority. This will help your business to keep the most valuable data consistently clean and accurate.

Take some time in choosing the key people who will be given the responsibility for maintaining the data. This selection process needs to be a core part of the plan. Having the right people in charge of ensuring the data management strategy is run smoothly and successfully will play a significant role in the success of the process. Appoint specific members of your team to deal with trouble-shooting regarding data quality; and make sure they are fully trained in the policies that are in place.

Keeping your priority data clean is essential to the success of your business moving forward. Taking the time and putting in the effort to put in place a complete, effective data quality management plan will help you to make sure that your business has the edge and the very best foundation for its success.

The author:

RingLead offers a complete end-to-end suite of products to clean, protect and enhance company and contact information, leading to improved organizational efficiency, reliable business intelligence, and maximized ROI on CRM and marketing automation investments.Since 2003 RingLead has helped solve the dirty data problems of large enterprises, Fortune 500 companies and small businesses across the globe.