The volume of data collected by the organizations is increasing at a record pace every year. The International Data Corporation (IDC) estimates that by 2025, the worldwide data will grow to 175 zettabytes with as much of the data residing in the cloud as in data centers1. In addition to that about 66% (5.3 billion) of the world’s population will have access to the internet in 2023 a number up from 51% (3.9 billion) in 20182. On top of it, the developments across countries to secure their citizens’ data has brought in a global evolution of personal data protection and privacy laws. Maintaining visibility and control over the data collected, stored, and processed needs to be the top priority for any organization to protect itself from the risks of data exposure and breaches.
But protecting the data from such risks comes with its challenges. With the exponential growth of data, it becomes complex to understand its origin, value, purpose, and sensitivity. In addition to that, poor access management may lead to sensitive information ending up in the wrong hands without adequate precautions in place.
In a digitally-driven world, data is the most valuable asset for an organization, and it needs to be protected at all costs. Increased use of technology and growing visibility into evolving cyber threats have led to an ever-changing landscape for data security and privacy.
Data privacy focuses on defining the organizational practices and policies that ensure the use of customer data for the intended purpose only. It also gives the customer the right to have control over the collection and usage of their personal data.
To regulate and secure the processes of organizations that deal with personal data, global regulators and governing bodies have enforced various data protection laws that highly prioritize data privacy. Some of the prominent among them are:
Data discovery and classification act as a foundation for data privacy and security strategy. Both the functions together serve the purpose of enhancing data visibility, analysis, categorization, and remediation. But manual implementation of such practices, especially in larger organizations that deal with personal data on a global level, is a tedious task that is generally prone to errors, as well as extremely time-consuming.
Automated data discovery and classification help better understand the context of data, increase the accuracy of identifying sensitive data, and effectively protect it. Automation software or tools inculcate both the standards of regulatory compliance and the policies derived by the organization to safeguard sensitive data and access controls.
Intelligent data discovery tools help scan varied targets ranging from endpoints, network servers, and hosts to databases, web applications, and storage files to identify the sensitive data. These tools also make it quick and easy to analyze the data stored in various file formats such as text, spreadsheet, images, audio, PDFs, etc.
Automated tools search for the places where the data lives whether in structured, semi-structured, or unstructured format across the organization’s network and cloud. Tools integrated with artificial intelligence and machine learning technologies help combat the challenges faced by security teams to constantly monitor the dynamic environments in search of sensitive information.
Followed by the data discovery process, data classification identifies the type within the discovered data to categorize it based on the set keywords, patterns, and labels. Data classification tools help link one piece of data to another to fulfill the organization’s need to process different data sets for different purposes.
Automated data classification tools also overcome the limitations posed by manual processes such as inconsistent or inaccurate classification of data by multiple employees. Such tools help save time and effort that security teams may put to manually classify the datasets as well as eliminate the chances of human error. With accurate data classification, organizations can take quick remediation actions of masking, truncating, or deleting the data to maintain data privacy for their customers.
With traditional data discovery methods not serving the needs of organizations in today’s data-driven world, automation has become more of a necessity than an option. Data discovery, being one of the most effective solutions to stay one step ahead of the data security risks, is now a basic requirement for organizations to effectively manage the growing data and meet compliance needs. In addition to being flexible, less time-consuming, and user-friendly, some advanced features of a data discovery tool are essential to determine its effectiveness.
Data discovery and classification are among those essential components of developing a cybersecurity strategy that cannot be overlooked. These solutions provide visibility to organizations that help them drive the security and compliance efforts and effectively handle the data flowing across the organization’s networks. The advantages offered are manifold, that include:
The right data discovery and classification tool not only helps streamline sensitive data management but also drives innovation and enhances compliance and risk management. Implementation of such tools also determines the organization’s commitment to protecting sensitive data and building customer trust.
For organizations facing challenges with sensitive data discovery and management, SISA Radar – SISA’s proprietary data discovery and classification platform, offers an end-to-end data solution to ensure the confidentiality, integrity, and security of sensitive data. SISA Radar’s forensics-based approach helps you to discover and secure sensitive data that the attackers target most, and classify, encrypt, and manage your data to prepare you to face any data security challenges. With the ability to scan more than 500 file types in both remote and corporate systems, SISA Radar safeguards sensitive data from unauthorized access, helps organizations navigate through the ever-changing risk landscape and remain compliant.
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