Data Resiliency Assessment Step 1 of 9 11% CompanyThis field is for validation purposes and should be left unchanged.Discover how your business stacks up. This brief questionnaire will help you identify your strengths, uncover gaps, and empower you to build a more resilient data environment—so you can protect what matters most and keep your operations running smoothly, regardless of what comes your way.Start your assessment now and take the first step toward greater confidence in your data resiliency. We’ll email you our assessment shortly after you complete it. Name(Required) First Last Email(Required) PhoneTitleCompany Directions: After each description of a Data Resiliency component, choose the response that best describes your organization.Data Strategy: Involves aligning business goals with resilience planning, defining ownership, and ensuring consistent practices across people, processes, and technology.(Required) Unsure of where we are currently with our Data Strategy. We have established a clear understanding of data initiatives, assigned owners to specific data, and allocated a budget for data resiliency. We have made sure our plan covers localization and retention requirements. We conduct an annual BIA (Business Impact Analysis), have documented our critical systems, and have automated tracking of regulatory requirements applicable to our organization. We have an enterprise-wide resiliency strategy covering suppliers, third-party business partners, and every active directory domain. We have SLAs in place. We conduct audits tied directly to business KPIs. People and Process: People are human resources involved in managing and recovering data, including their skills, knowledge, and roles. Process is the established methods and workflows that guide an organization's data management and recovery efforts.(Required) We are unsure of our current status regarding People and Process in relation to data resiliency. We have laid the groundwork with clear roles, a basic RACI (Responsible, Accountable, Consulted, and Informed), and assigned a senior leader to be responsible for data resiliency. Everyone is aligned with standardized processes for IT changes, incident management, and data recovery. We cross-train our teams, conduct simulation exercises, and ensure policy enforcement. We have appointed a Chief Resiliency Officer to lead organization-wide efforts. We have a centralized incident management playbooks that guide cross-functional teams through any scenario of data recovery. Data Backups: Different types of backups, such as full, incremental, and differential, offer various levels of protection and recovery options. Implementing a robust backup strategy enables you to restore data quickly and efficiently in the event of a loss.(Required) We are unsure of our current status regarding data backups. We currently run basic backups, which include scheduled regular backups, and we monitor backup job success to ensure coverage of the basics. We have gone above basic backups by adding snapshots and tiered storage. We have configured immutability protections. Our current solution complies with the 3-2-1-1-0 rule to protect our critical workloads. We use AI to catch backup gaps. We have configured CDP (Continuous Data Protection) for our critical data workloads, replicating continuously across geographic zones. Data Recovery: The process of retrieving digital information that is lost, corrupted, or inaccessible from storage devices, due to accidental deletion, system crashes, physical damage, or being locked by a bad actor.(Required) We are unsure of our current status regarding Data Recovery. We have a basic recovery plan that utilizes some automation. We occasionally test-restore our backups. We have automated full recovery flows, test recovery early and often, and are keeping our disaster recovery documentation up to date. We have automated recovery end-to-end. We conduct Disaster Recovery training twice a year and thoroughly test our recovery quarterly. Data Architecture: A blueprint or framework that defines how an organization acquires, stores, processes, and uses its data, ensuring it aligns with business strategy and supports data-driven decision-making.(Required) We are unsure of our current status regarding our Data Architecture. We have designed our stack for resilience with a tiered protection plan, offsite capacity, and the ability to recover to secondary infrastructure rapidly. We utilize a consistent cloud and data platform across environments, enabling cross-platform recovery, and ensure that we can scale secondary infrastructure within 24 hours. We enabled cloud-to-cloud and cross-platform mobility for nearly all workloads, and our infrastructure can scale in under 12 hours. Data Security: The process of safeguarding digital information throughout its entire life cycle to protect it from corruption, theft, or unauthorized access.(Required) We are unsure of where we are currently with our Data Security. We have established our security foundation by implementing logging, encryption, and system hardening. We have, or plan to implement, quarterly testing and digital forensics to identify gaps before they become significant. We have shifted to real-time detection, dynamic access controls, and micro-segmentation to proactively protect critical systems from lateral threats. We have advanced to adaptive security with real-time logging, continuous authentication, monthly pen testing, and a standing ransomware response team. Data Reporting: The process of collecting, organizing, analyzing, and presenting raw data in a structured format to provide actionable insights and support informed decision-making.(Required) We are unsure of our current status with Data Reporting. We have begun tracking incidents in real-time and reporting on trends to identify what’s slowing us down. We have standardized incident reporting across all sources and have integrated it with our compliance tracking to stay ahead of evolving regulations. We use real-time monitoring and automated systems to track data demand and deliver insights across teams. Data Intelligence: Encompasses the entire data lifecycle, including data governance, quality, integration, and security.(Required) We are unsure of our current status with our Data Intelligence. We have utilized vendor tools to run basic analysis on backup data and have started building context around what’s being protected. We have developed and implemented methods to ingest and contextualize resilient data, and then analyze patterns to optimize storage and identify risks of disruption to the business. We have put AI to work with copilots that guide daily tasks, tools that predict outages, and automated monitoring that flags real-time risk, all while consistently tagging sensitive data to protect critical data.