Super Easy 6 Ways To Improve Data Accuracy

EM Admin
Aug 21, 2020
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Not just any data, but the quality of data matters. The concept called data quality management can help in keeping up the accuracy, consistency, and normalcy of files in your database. Simply put, data quality management involves the right-fit talent, processes, and technologies with a common goal, which is to evaluate the quality metrics of information.

To get rid of these unfortunate conditions, focusing on qualitative records is essential. Here are a few ways to improve it.

Super Easy Six Ways to Improve Data Accuracy

Super Easy 6 Ways To Improve Data Accuracy

Some key ways are here to improve data accuracy

Discover Causes of Inaccurate Data

The data sources, both internally and externally, should be error-free and seamless. But sometimes, certain things can let you compromise on the quality. These causes can be data migration, data entry mistakes at the point of entry, incompatible format, system error, presence of incorrect values, changes in time-bound data, & null problems.

Focusing on figuring out the exact cause can help you to identify the primary reason for inaccuracies. Once tapped, its fixing won’t take too much time.

Set Realistic Quality Goals

Setting realistic goals makes them achievable. So, it is vital to carry out the work on realistic accuracy-based targets. The data management team should take the causes into account at the very entry point of records and fix them right away. Afterward, they should follow precautionary measures accordingly to avoid any scope of such errors. With the help of programmers, data researchers, or MIS experts, coding can be done to identify, verify or validate, and correct anticipated errors.

Overloading is Disastrous

Overloading can occur if there is a rush to deliver files & you have the least time & resources to process or cleaning files. An efficient and experienced manager can accurately project timelines for delivery as per available resources. Having extremely efficient experts can do no good because your overload can exhaust them. The resentment may happen, which causes errors. To deal with this problem, you should evaluate delivery time corresponding to the efficiency of your team. Delegate tasks as per efficiency & expertise and span it over weeks.

Revise Entries

Reviewing data over and over is the best policy to keep up with consistency and high quality. Data validation can be an effective function if you want to review customised datasets in Excel or Google spreadsheets. Or, you may deploy any validation tool to automatically check the accuracy of a colossal-sized table, or database. This is how you can monitor and reduce errors to a large extent.

Automated Error Reporting

Automated Error Reporting is a practice of pooling and reverting information when your team or program is incapable of handling exceptions on end-users mistakes.

This error report covers full-stack details about the errors or exceptions. You may withdraw bespoke information, like log files or screenshots. It can be used in two circumstances, which are the following:

When you want to discover useful information prior
When you want to reduce the time to debug and fix your application via the filtered information to understand the context of exceptions (errors)

Adopt Accuracy Standards

The quality standards for maintaining any database are must-haves. These standards can be related to matching, geocoding, monitoring, data profiling, linking, etc. This practice ensures that the entered tables or details conform to preset standards. Following this practice can help in bettering its quality.

A Bonus Point

Have a Safe Storage

Cloud storage, these days, is the best way to stock your data for a long period of time. Adopting it lets you keep your data intact and security higher and more reliable. This is ensured through end-to-end encryption, which covers data privacy. Besides, it helps you to put the burden of keeping data intact during migration off the shoulder automatically.

Final Words

With relevant, complete, and error-free records, the company builds a way to decisions that are fact-based and feasible enough to attract success. A meager typo or incomplete details can cast a ripple effect, which continuously spread the results of a wrong data entry. These results can be a colossal monetary loss or defame for your company.