Data compliance identifies the laws, regulations, and standards that a company’s data activities. Compliance requires meeting requirements for the safe storage, legitimate use, and deletion of sensitive consumer data.
Comprehensive data compliance increases your company’s reputation for trust among customers and partners. More importantly, it minimizes the risks of a data breach.
Many regulations governing the collection, storage, use, and deletion of sensitive data are specific to businesses selected industries, such as healthcare or finance, or to firms operating in specific regions such as Europe. U.S. government agencies must meet data standards set by the National Institute of Standards and Technology (NIST) but many private firms voluntarily follow the regulations to as best practices.
The most common data compliance regulations affecting organizations in the U.S. and overseas are:
Several new and updated data regulations took effect in 2024.
A solid compliance strategy does more than just ensure that your organization meets its fiduciary responsibility to protect the data it relies on for its day-to-day operation. Data compliance is now the key to building and maintaining a trustworthy relationship with your customers and business partners.
One of the primary data compliance challenges stems from the inherent usefulness of the data your company is responsible for. It would be simple to keep data safe, if you could just prevent everyone from accessing and using the data, but that is not viable. Today’s businesses run on data. While data is kept and processed in production systems, there are also many requirements to use data in non-production systems. Often it these non-productive uses such as testing, where data breaches can occur.
Production data systems typically are the most secure systems in a company but often copies of production data are used in testing, data analysis and other activities where safeguards are not as rigorous as production systems. It is not uncommon for a business to have dozens of copies of production data, which increases the risk of a data breach significantly.
Data masking can secure data for many non-production uses by hiding details about specific information. In many tasks such as testing and data analysis, the specific private information is not important. Simply put, data masking add value to data protection, ensuring compliance with data compliance standards.
Big Data adds a new challenge to data compliance. The volume of data requires expensive specialized systems to store and process the data. Legacy data masking procedures and tools are not effective masking big data, often having compatibility issues with big data storage formats and performance issues processing the large volume of data.
For companies involved in Artificial Intelligence (AI) training, data masking can assist in maintaining data compliance. AI models trained on big data sets which contain private and sensitive information can end up exposing that data. By masking the training data companies can eliminate the risk of private and sensitive data exposure.
By masking regulated private and sensitive data in non-production systems, Obfusware can be an important component of a company data compliance strategy, especially if the company manages big data which contains private and sensitive data. Obfusware’s versatile data masking algorithms are designed to mask private and regulated data while preserving important data characteristics such as data references and statistical significance. This allows the masked data to be used for training, testing and data analysis where the complex data relationships are critical to achieving realistic and meaning results.