AI has the potential to revolutionize federal operations, driving innovation in predictive analytics, autonomous systems, and edge computing. However, realizing these transformative opportunities hinges on modernizing agencies underlying storage infrastructure. Our latest industry brief, How to Transform Your Agency Storage Strategy for AI and Analytics Workloads, offers critical insights into the steps agencies can take to align their data storage strategies with the demands of AI.
Why Outdated Technology Holds Agencies Back
Many agencies struggle with storage systems that fail to meet the demands of AI workloads. Predictive analytics, machine learning, video analytics, and edge AI require scalable, high-performance storage capable of handling vast datasets. For example, machine learning models demand massive data sets for training and real-time processing, a challenge for legacy systems. However, attempts to scale data management rapidly are often hindered by the challenges of data complexity and the security risks inherent in managing highly sensitive and classified information.
Core Requirements for AI-Optimized Storage
Implementing AI successfully starts with storage systems purpose-built for high performance, scalability, and security. Creating a robust storage platform for AI and machine learning workloads requires infrastructure that enables efficient data collection, storage, and management. Equally important is safeguarding this data through rigorous governance and security measures to ensure data integrity and compliance with regulatory standards. The industry brief identifies five key criteria for optimizing storage systems to meet the demands of AI workloads effectively:
- Low Latency: AI thrives on rapid data access, making high-speed storage systems a necessity.
- Scalability: As datasets grow exponentially, storage must scale seamlessly without disrupting operations.
- Data Integrity: Reliable and compliant storage solutions are vital for long-term data accessibility.
- Mobility Across Environments: AI workloads often span cloud, on-premises, and edge environments, requiring flexible storage architectures.
- Support for Modern Workloads: Diverse data types, from videos to sensor data, demand solutions that handle both structured and unstructured datasets.
Architectural Strategies for Modern Workloads
To implement an architecture optimized for AI, agencies can adopt a strategic approach using advanced technologies tailored to modern data demands. Distributed architectures enable efficient data management at the edge and in remote locations, ensuring real-time processing capabilities. Hyperconverged infrastructure (HCI) integrates storage, compute, and networking into a unified platform, streamlining AI workload execution. For the large volumes of unstructured data generated by AI and analytics, object storage provides scalable and efficient solutions. Additionally, data tiering and intelligent data placement optimize both costs and performance by prioritizing high-performance storage for critical data while allocating less urgent data to cost-effective tiers. Together, these technologies create a robust foundation for AI-driven innovation.
The Hitachi Vantara Federal Advantage
Hitachi Vantara Federal offers a high-performance digital infrastructure to help agencies build and manage resilient data pipelines that fuel AI innovation and advanced analytics including these solutions:
- Virtual Storage Platform (VSP) One delivers scalability and unparalleled data availability.
- Hitachi Content Platform (HCP) excels in managing vast unstructured datasets for AI.
- Hitachi Ops Center provides AI-driven insights for optimizing storage performance and utilization.
A Call to Action for Federal Agencies
AI offers governments transformative opportunities, from task automation to impactful insights. However, outdated storage systems can hinder progress. Hitachi Vantara Federal addresses this with integrated storage platforms and advanced analytics management, enabling seamless data processing across environments.
This is just a glimpse of what the full asset covers. If your agency is ready to tackle the challenges of AI and analytics workloads, this paper is a must-read. Dive deeper into the strategies and solutions that can position your organization at the forefront of AI-driven transformation. Read the full paper now.