Data validation is critical to helping you make better business and IT operations decisions. And the market for data validation is increasing, all for good reasons. The factors such as increasing volume of business data, increasing use of external data sources, and increasing regulatory pressure are expected to emerge as the significant factors accelerating the growth of the data quality and validation tools market.

In addition, increasing the reliability of data for strategic decision-making across different organizations and growing concern to maintain a standard data quality discipline across various organizations globally will further aggravate the growth of the data validation tools market.

However, factors such as lack of awareness and integration challenges are affecting data timeliness results, resulting in a growth restraint for the market. Basically, to work with data validation effectively, you’ll want to leverage a good partner.

Let’s explore data validation and why it is essential for IT professionals and their success.

What is Data Validation?

Data validation is the process of ensuring that data is accurate, complete, and consistent. Data validation can involve various activities, including:

• Data Integrity: Data integrity involves ensuring the data is accurate and reliable. This includes verifying that the data is complete, consistent, and error-free.
• Data Verification: Data verification involves checking that the data meets the required standards and specifications. This includes validating the data against the expected format, field types, and values.
• Data Quality: Data quality involves ensuring the data meets the required standards. This includes evaluating the data for completeness, accuracy, consistency, and timeliness.
• Data Cleansing: Data cleansing involves identifying and correcting errors or inconsistencies in the data. This can include removing duplicates, correcting misspellings, and standardizing data formats.

Why is Data Validation Essential for IT Operations Professionals?

Data validation is essential for IT professionals for several reasons:

• Data Quality: IT professionals use data to drive their operations and decision-making. Data validation ensures that the data is accurate, complete, and consistent, improving the data’s quality and the insights gained from it.
• System Performance: Incorrect or incomplete data can impact system performance and cause errors or delays. Data validation helps ensure that the data is of high quality, validated, and cleansed before being used in systems.
• Compliance: Data validation is critical for compliance with legal and regulatory data privacy and security requirements. IT professionals must ensure that they comply with these requirements and that the data they use is accurate and complete.
• Cost Savings: Data validation can lead to cost savings by reducing the time and resources required to correct errors and inconsistencies in the data. This can also lead to improved efficiency and productivity.

How to Perform Data Validation?

There are several steps involved in performing data validation:

1. Define Requirements: The first step is to define the requirements for the data. This includes identifying the data sources, types, and quality standards.
2. Develop Validation Rules: The next step is to develop validation rules based on the requirements. These rules should specify the format, field types, and values required for the data.
3. Validate Data: Once the validation rules have been developed, the next step is to validate the data. This involves comparing the data against the validation rules to ensure it meets the requirements.
4. Correct Errors: If errors are identified during the validation process, the next step is to correct them. This can involve removing duplicates, correcting misspellings, and standardizing data formats.
5. Monitor and Maintain: Data validation is an ongoing process. IT professionals must monitor the data regularly to ensure that it meets the required standards and specifications. This can involve implementing automated data validation tools and processes.

Getting started with data validation

Data validation is critical for IT operations professionals and their success. IT professionals can improve data quality, system performance, compliance, and cost savings by ensuring that it is accurate, complete, and consistent. As discussed, data validation involves defining requirements, developing validation rules, validating data, correcting errors, and monitoring and maintaining the data.

IT operations professionals must implement effective data validation processes to ensure their data is high quality and meet the required standards and specifications. As we look ahead, complex data structures will challenge the data quality validation market. To overcome these headaches, schedule a time to chat with TFORM’s data validation professionals and learn how leaders in the IT space are leveraging the best data sources for their business.