Five Techniques to Protect Sensitive Data in Your Company

Organizations should automate the reporting of personally identifiable information (PII) to increase accuracy and reduce audit times when making changes to governance artifacts.

Fremont, CA: Organizations gather vast amounts of data from various sources, and any of these data sources could contain sensitive information. In addition, data is frequently transferred for warehousing, reporting, analytics, storage, testing, and application use. From creation through disposal and everything in between, the data lifecycle should be managed. According to Gartner, most enterprises have 40+ tools and solutions in their portfolio to address complex data concerns. Today, 80 percent of businesses are considering vendor consolidation to cut costs and improve security.

There are five essential considerations for your foundation for trusted data when enterprises strive to consolidate their information architecture stack:

· Auditing regularly

· Data management

· The finding of data

· Response and evaluation in a timely manner

· Anywhere deployment

Auditing Regularly

There is a rising need to develop visibility across sources to handle corresponding data. Compliance specialists can monitor various sources thanks to increased data availability made available by real-time integrations. For dynamic domains like cyber risk and data protection, governance, risk, and compliance (GRC), the solution can help give aggregate insights on systemic flaws in controls, processes, and compliance.

Data Management

Typically, organizations need to define and automate policies for enterprise-wide data categorizing and classifying using a data catalog at heart. This must happen anywhere data sits to ensure that the relevant data protection procedures are implemented and triggered when sensitive data is accessed, utilized, or transferred.