INDUSTRY INTELLIGENCE
Best practices
Securing unstructured data requires a comprehensive approach that addresses the unique characteristics of this data type .
By implementing appropriate security measures and best practices , organisations can protect sensitive information contained within unstructured data and mitigate the associated risks . Here are some steps to take to secure unstructured data with data orchestration .
• Establishing intelligent policies – Orchestrating and managing data globally , regardless of where the data is today or needs to move tomorrow , is a key practice when securing data . Because data services can be applied globally across all storage resources and locations , the implementation of global control eliminates the need for IT organisations to manage multiple point solutions to migrate , protect , or perform other functions , as is typically the case in siloed environments today .
• Securing metadata – Unstructured data often contains valuable metadata , which can provide insights into the data ' s origin , ownership and usage . While metadata itself might not contain the actual content of data , it can still reveal sensitive information and provide insights that could be exploited by malicious actors . Properly managing and securing metadata is important for maintaining data integrity .
• Centralising control – Data orchestration systems provide a centralised control point for managing data flows and interactions across various systems , applications and processes . This enables administrators to enforce consistent security policies and access controls throughout the data life cycle .
• Access control and authentication – Data orchestration systems often include built-in access control mechanisms that ensure only authorised users and systems can access
The role of the data officer is expanding as organisations are paying more attention to storage , backup and data security to prevent data leaks .
and interact with data . Users may be required to validate their identity using strong authentication methods before accessing data through orchestrated processes .
• Encryption and data protection – Data orchestration systems can facilitate encryption of data at rest and in motion . They can automate the encryption and decryption process , ensuring that data remains protected even as it moves between different systems and stages of processing .
• Consistent security policies – Data orchestration helps enforce consistent security policies and practices across diverse data sources , destinations and transformations . This minimises the risk of security gaps or inconsistencies that could arise from manually managing data interactions .
• Real-time monitoring and auditing – Many data orchestration systems offer real-time monitoring and auditing capabilities . This enables users to track data movement , transformations and interactions , making it easier to detect and respond to any unauthorised or suspicious activities .
• Automated compliance – Data orchestration can help users achieve and maintain compliance with data protection regulations by automating the enforcement of data handling and security policies .
Overall , data orchestration enhances data security by providing a structured , automated and centralised approach to managing data flows , interactions and security measures .
It helps organisations mitigate risks , enforce security policies and respond effectively to security incidents in today ' s increasingly complex and dynamic data environments . � www . intelligentdatacentres . com
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