15 Questions to Ask When Evaluating Storage Solutions

Storage Heroes  |  May 30, 2024

Is there such a thing as asking too many questions? Not if you’re a data storage manager; questions are essential given the sensitive nature of the data under management. Many things that need to be considered when dealing with sensitive data. To facilitate effective data management and ensure productivity, we have curated a comprehensive set of 20 questions for daily reflection, tailored for both individual and team assessment.

Regulatory Compliance and Security

To ensure comprehensive data security, it is crucial to follow regulatory requirements relevant to your industry and region. These regulations often mandate specific protocols for data protection and privacy, such as HIPAA for healthcare in the United States. Certain types of data require heightened security measures, particularly financial data, health records, and mission-critical or controlled information. These data types are more secure and valuable and can have severe implications if compromised.

  1. What blanket regulatory requirements do I need to follow? What policies and mandates affect my organization at the national, cabinet-level, and individual level? What specific controls, processes, and requirements has my organization committed to maintaining in our security posture?
  2. How sensitive is the data we handle, and what are the implications of its loss or unauthorized access?
  3. What data needs to be more secure compared to others? Do we have the appropriate governance practices in place to control access, transport and handling of data?
  4. Are we implementing data monitoring and cybersecurity solutions to prevent unauthorized access and enhance our security posture?
  5. What are the industry best practices for data storage and management, and how well do we adhere to them? Are we architecting for simplicity, scale, and sustainability?
  6. If this data gets lost, what is the action plan for recovery? What SLAs can we guarantee to our end users regarding downtime and data loss prevention?
Data Management and Storage Solutions

Data is the fuel for innovation, decision-making, and national competitive advantages. But the volume and complexity of data is increasing at an exponential rate, especially for government agencies. Storage managers and data center operations teams in government need to stay abreast of this data deluge by planning for anticipated future needs today.

  1. What types of data are we supporting and for what purposes? Is there any data that is unstructured or semi-structured? If so, how are we taking advantage of metadata?
  2. Does my current data solution fit my agency’s anticipated future needs? Factoring in procurement and deployment timelines, how quickly can we scale to meet unexpected changes in demand?
  3. What cost considerations are most important to me and my agency? Aside from financial considerations, are there hidden costs such as additional required labor and training, or environmental costs we need to factor into our evaluation criteria?
  4. Do we need to consider how this storage solution interoperates with hyperscaler clouds or colocation services? Is hybrid cloud a core requirement for this architecture?
  5. How much data redundancy is too much? How are we handling deduplication, compression, and snapshots to enhance resiliency without wasting resources?
  6. What is considered the full lifecycle for our mission data? How do we ensure data integrity, accuracy, and consistency throughout its lifecycle?
Data Analysis and Usage

The ability to analyze data is vital for data-driven decision-making and generating new insights. While the safeguarding and efficient management of data is critical for government storage managers, the ability to make that data actionable for analytics and applications is what separates future federal data leaders from the rest.

  1. Can I find a specific piece of data at the drop of the hat? Are we taking advantage of metadata for indexing and search across structured, semi-structured and unstructured data?
  2. What data pipelines do we need to prepare for? What are their performance and configuration requirements?
  3. How can we build flexibility into our digital infrastructure, and posture ourselves to more quickly react to and support future emerging technologies such as AI?