The data validation process ensures that imported and processed data is accurate and of high quality. It’s also a type of data purification. Validating your data ensures that it is unique and falls within the expected set of variables. ETL (Extract, Transform, and Load) procedures include data validation as an aspect of the data transmission phase. It allows you to enroll the repository database’s data with the specific data warehouse for evaluation. When performing analysis, data validation helps determine the integrity of your findings.
Importance of Data Validation
The following are the benefits of data validation:
- Validation of data guarantees the accuracy of the data you have stored in your device. It could help your business in various ways, but it’s pivotal for boosting revenue.
- When building and maintaining accurate marketing lead lists and pitching to prospective clients, you can rely on data validation to get accurate statistics.
- Data validation can help you avoid inaccurate information that could cost your business money while also putting you at risk of missing out on valuable insights.
- Data validation allows you to detect problems and errors easily and sort them out before they become cancer that eats deep into your business.
- You can use data validation to look for discrepancies; business contact numbers must always go through the data validation testing. It ensures that the data in your file is accurate.
- It helps you manage decisions that will help you improve productivity while solidifying the reputation and credibility of your company.
- Data validation enables you to work with reliable data when dealing with regular clients, corporate structure, executive timesheets, and financial information.
Challenges of Manual Data Validation
The following can make manual data validation a challenging procedure:
- Manual data validation can be a complex process due to the different locations of data on the system.
- Manual data validation can be an extensive process, particularly if you have a massive database. The time taken is too long. Validation analysis, on the other hand, can help to shorten the process.
What to Expect from a Robust Data Validation Engine
- It should automatically make suggestions for users.
- The robust data validation engine should be able to accommodate various data formats.
- It should make validation rules simple for the user to create.
- It should be capable of importing data from multiple databases.
- Automatic updating of rules while making use of them in productive aspects.
- It should be able to use any input feed to create orderly rules.
- It should be able to make use of reusable library rules.
- The data validation engine should carry out importation and exportation of the rules.
- It should be able to differentiate the bad data from good data.
- It should enable the user to download the good data and bad data for corrections to be carried out where necessary.
- It should be able to track problems using the detect management tool it has in it.
Benefits and Offering of DataQ
- DataQ is a data validation tool that can help many companies cut costs and improve production efficiency via its automated process.
- You can use DataQ in conjunction with SQL queries to construct a data validation section.
- DataQ is capable of setting up various connections to different sources of data.
- DataQ can accommodate multiple file formats to use as input.
- They can absorb file formats like XML, JSON, ORC, and CSV.
Data validation is the best process that provides data quality and accuracy to ensure a productive outcome. Using the right data validation tool to carry out the data validation process can help you save costs and time for your business. It’s a guaranteed means that will be very beneficial to your business in the long term.