How do you secure data and comply with standards?

2 Implement data encryption and masking

One of the most effective ways to secure your data is to encrypt it, both at rest and in transit. Encryption ensures that only authorized parties can access and read your data, even if it is intercepted or stolen. You can use various encryption methods and algorithms, depending on your data type, format, and storage location. For example, you can use symmetric or asymmetric encryption, hash functions, or digital signatures. You also need to manage your encryption keys securely and rotate them regularly. Another technique to secure your data is to mask it, which means to replace sensitive or identifiable data with fake or anonymized data, while preserving its structure and functionality. This is useful for scenarios such as testing, development, or analytics, where you need to use realistic data without exposing the actual information.

3 Apply data access control and auditing

Another key aspect of data security and compliance is to control who can access and manipulate your data, and to monitor and track their activities. You need to implement data access control policies and mechanisms, such as authentication, authorization, role-based access, and multi-factor verification, to ensure that only legitimate and verified users can access your data according to their privileges and roles. You also need to audit and log your data access and usage, such as who accessed what data, when, where, how, and why, and to review and analyze the logs for any anomalies, errors, or violations. You can use tools such as identity and access management (IAM) systems, firewalls, or network security groups to enforce and manage your data access control and auditing.

4 Follow data governance and quality standards

Data security and compliance are not only about protecting your data from external or internal threats, but also about ensuring that your data is consistent, accurate, and reliable. You need to follow data governance and quality standards, such as data definitions, metadata, lineage, provenance, and lifecycle, to maintain the integrity and usability of your data. You also need to adhere to the specific standards and regulations of your industry, domain, or customers, such as GDPR, HIPAA, PCI-DSS, or ISO 27001, which define the rules and requirements for data collection, processing, storage, and sharing. You can use tools such as data catalogs, data dictionaries, or data quality management systems to support and automate your data governance and quality processes.

5 Use data security and compliance tools

Data security and compliance are complex and challenging tasks, but there are tools and platforms available to help. For example, data encryption and masking tools like AWS KMS, Azure Key Vault, Google Cloud KMS, or IBM Data Privacy Passports provide encryption and masking services for your data in various formats and locations. Data access control and auditing tools such as AWS IAM, Azure Active Directory, Google Cloud IAM, or IBM Security Verify offer identity and access management, authentication, authorization, and auditing services for your data users and resources. Additionally, data governance and quality tools including AWS Glue Data Catalog, Azure Purview, Google Cloud Data Catalog, or IBM Watson Knowledge Catalog can provide data cataloging, metadata management, data lineage, data quality, and data compliance services for your data assets and standards. By using these tools and platforms you can take advantage of the best practices of data security and compliance in your architecture while also reducing the complexity and cost of managing your data.