IDC Names Securiti a Worldwide Leader in Data PrivacyView
With data growing at an unprecedented rate, organizations need to know what data they hold for data security & privacy as well as global compliance. While Data Discovery solutions have been traditionally utilized to get visibility into sensitive data, they are not able to scale and offer effective detection at petabyte scale common in a modern cloud environment.
Common challenges include:
An organization must have a plan and process in place to effectively manage personal data breaches. Timely and accurate disclosures to regulatory authorities and impacted data subjects can lessen the adverse impacts of a personal data breach. Besides, organizations can use such events to learn about their weaknesses and gaps, and improve their overall security posture to reduce the risk of personal data breaches in the future.
With the increasing use of technology and businesses starting to collect more and more personal data, there has been a growing concern for data privacy. Securiti’s PrivacyOps methodology enables organizations to implement efficient data discovery tools and breach management. Securiti offers the sensitive data intelligence solution that will help organizations enhance and improve their data privacy and security processes.
1. Discover & catalog shadow and sanctioned assets
One of the most critical capabilities of any efficient data discovery solution is the ability to discover and build a central catalog of all data assets, including all sanctioned & shadow data assets in on-premises & multi-cloud environments. Keeping track of the data is the first step towards protecting it from malicious intent and minimizing the "blast zone."
2. Extract and catalog asset metadata
Sensitive data catalogs provide native connectors and REST-based APIs to scan and extract metadata from all data assets. These include data warehouses, cloud data stores, non-relational data stores, and many more. There are three types of metadata
3. Detect sensitive and personal data
Once on-premises and cloud-based assets are discovered, security administrators need to know what sensitive data is stored in these assets. Few important categories of sensitive environment impacts most businesses:
4. Catalog, classify & tag sensitive data
A sensitive data catalog provides insights into sensitive data attributes and security and privacy metadata such as security controls, the purpose of processing, etc. A sensitive data catalog should be available by default in a good data discovery tool since it parses and organizes the content in a meaningful way. Data catalog capabilities include:
5. Assess overall data risk posture
Sensitive Data Intelligence should provide comprehensive data risk assessments that include data sensitivity, data concentration, and instances of cross-border transfers.
A data discovery tool can use all these parameters to assess the overall data risk score, which can prioritize risk mitigation activities.
6. Built a graph between data and its owners
To fulfill DSR requests promptly, organizations should ensure SDI™ solutions can discover personal data and link discovered data with users' identities automatically.
Fulfilling DSR Requests are a requirement under global privacy regulations, and failure to do so can result in hefty fines.
7. Scale to petabyte volume with high accuracy
As data volume reaches the petabyte scale, the security and privacy risks associated with data increase.
Organizations need a product that can scale to large data volume and provide detection or scanning capabilities that can reduce their total cost of ownership (TCO) over time by minimizing compute resources required to find sensitive data within these assets.
8. Map data to compliance and regulations
With a robust data discovery tool, administrators can build a centralized catalog of their data assets and discover sensitive data stored in them. Using automated discovery mechanisms, organizations can ensure their data maps and Article 30 reports are up to date.
The future of data discovery is here and Securiti has, and always will be the forerunners in enabling organizations. Request a demo today!
With data increasing and traditional data discovery methods not up to the par to survive in a hyperscale environment, organizations need to quickly start thinking of alternatives that will help them manage the growing data and also stay in compliance with privacy regulations. Automation is becoming more of a necessity than ever before and integrating automation within your business processes is now a requirement if your organization hopes stay abide by global privacy laws.
Data discovery methods include data scanning, data mapping, data cataloging, and the use of data discovery tools and software. These methods help organizations identify where personal data is stored and how it is processed.
Strategies for data discovery involve creating a systematic approach to locate, classify, and manage data. This includes conducting data audits, engaging stakeholders, implementing data discovery tools, and documenting data flows and processing activities.
Key factors of data discovery include understanding data sources, data types, data processing activities, data ownership, and data access controls. Effective data discovery also considers regulatory requirements and privacy implications to ensure data protection and compliance.
At Securiti, our mission is to enable enterprises to safely harness the incredible power of data and the cloud by controlling the complex security, privacy and compliance risks.
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