Data Loss Prevention (DLP) Readiness Assessment
Due to complex IT environments, along with an evolving threat landscape and the increasing footprint of a remote workforce, securing data presents challenges for IT and security teams now more than ever.
As you accelerate the transition of workloads to the cloud with digital transformation efforts, your level of visibility and control over your data can wane, making it more difficult to secure everything. As the appetite for data analytics and data science increases, the potential for data breaches and compromised intellectual property rises exponentially. You need your data to be current, available, and consistent across your entire organization. Having a concrete data loss prevention (DLP) strategy in place is one the most effective methods for detecting risks to business-critical data.
Stratascale DLP Readiness Assessment
The market is overrun with technology suites and tools available to help ensure data protection, but an investment in technology alone is not enough to effectively secure your data against loss, corruption, or theft. We have developed a DLP security assessment service that aligns with best practices used by the National Institute of Standards and Technology (NIST). A unique understanding of DLP–focused NIST best practices and the importance of DLP to your overall cybersecurity strategy allows our experts to help you develop and adopt a framework that can prevent data breaches and exfiltration. Our structured approach to DLP readiness will:
Identify and classify the following three data types via tool-based data gathering, customer interviews, and documentation review
- Data at rest (unstructured data, backups, etc.)
- Data in transit (network, web, email, etc.)
- Endpoint (mobile, workloads, etc.)
- Pinpoint gaps between newly discovered assets and previously identified assets
- Review DLP policies (low- and high-level designs)
- Analyze gaps between NIST best practice frameworks and your existing deployment
- Produce an executive summary of the most critical findings with highest contextual impact gap analysis
- Create a technical summary of all findings organized by importance and business impact
- Recommend remediation procedures
- Prioritize roadmaps