The value of data increases exponentially as it is used and reused across government organizations to deliver their mission requirements. In discussions with government CDAOs (Chief Digital and AI Officers), we have learned that a top objective is to “unlock value” from all data stored across their agencies. But they also need to act on data in a way that complies with internal and external governance rules and regulations. And ultimately, they want to use the data to power mission delivery. However, without suitable systems and architectures, the goal of delivering valuable data at the right time and place to fulfill mission delivery is nearly impossible.
What Is A Data Fabric, And How Can It Work For My Agency?
Data is only valuable once it has been placed in context and then made accessible to users and applications. Data fabrics implemented correctly do this. A data fabric provides agencies with a consistent and coherent view of all the integrated and packaged data they may need, completely agnostic to both the user’s and the data’s location. It can span infrastructures across multiple clouds, data centers, IoT (Internet of Things) gateways, and/or edge devices.
Specifically, a data fabric is a data integration architecture that makes the complex objective of data integration, information enrichment, and knowledge management for agencies a reality today. With a Data Fabric, data practitioners, users, and stakeholders gain access to the right data and decisions at the right time despite the underlying complexity of the data sources, infrastructure, network, and bandwidth. Data fabric solutions deliver data access, discovery, transformation, integration, security, governance, lineage, and orchestration capabilities. A reliable base of trustworthy data is indispensable for effective advanced analytics. Trusted data is a significant component of any enterprise’s digital transformation journey and needs to be addressed in a continuous and evolving manner with the right metrics and analytics.
Deploying a data fabric architecture enhances your DataOps practices and provides agencies with many benefits including:
- A complete, single view of trusted data.
- Data is secure across the entire agency.
- Agencies can provide a self-service and collaborative platform for all stakeholders.
- Real-time data is shared with users, citizens, and other stakeholders.
What Is The Role Of Data Fabrics In Aiding Agencies In AI (Artificial Intelligence) Management?
Data volumes and AI technologies continue to evolve, and agencies must decide how best to extract the value from their data assets. But extraordinarily little of an organization’s data is being used today to gather insights. This leaves a wealth of untapped data resources in agencies, and the journey to exposing this data is often challenging to plan and execute, making the situation worse. As AI continues to become mainstream for many agencies, putting in place solutions to address these data challenges will be essential.
A Data Fabric helps organizations manage AI by providing a unified and agile data infrastructure that supports the data needs of AI initiatives. Here are several ways in which a Data Fabric can facilitate AI management:
- Data Accessibility and Integration: AI requires access to diverse, often siloed data sources. A Data Fabric integrates data from various sources, including on-premises, cloud, and edge environments, making it readily accessible to AI systems. This ensures that AI algorithms can access the data they need for training and inference.
- Data Quality and Governance: AI models rely on high-quality, clean data. A Data Fabric facilitates data quality by enforcing governance policies, ensuring data consistency, and providing data lineage and metadata management. This improves the reliability of AI results.
- Data Versioning and Lineage: AI models are iterative and evolve. A Data Fabric can track data lineage and versioning, enabling organizations to trace the origin of data used in AI models and reproduce results when necessary. This is crucial for compliance and auditing.
- Scalability: AI workloads can be resource-intensive and may require large datasets. A Data Fabric can scale horizontally and vertically, accommodating AI projects’ growing data storage and processing needs without significant disruptions.
- Data Transformation and Preprocessing: AI models often require data preprocessing and feature engineering. A Data Fabric can support data transformation pipelines, enabling organizations to prepare and preprocess data efficiently for AI training.
- Real-time Data: AI applications, such as real-time fraud detection or recommendation engines, require access to real-time data streams. A Data Fabric can handle streaming data, making it available for real-time AI processing.
- Security and Compliance: AI applications often deal with sensitive data. A Data Fabric can enforce security policies and access controls, ensuring AI models comply with data privacy regulations and organizational security standards.
- Data Collaboration: AI is a collaborative effort that involves data scientists, engineers, and domain experts. A Data Fabric provides a shared environment where teams can collaborate, share data, and collaborate on AI model development.
- Resource Management: AI workloads can be resource intensive. A Data Fabric can help manage compute and storage resources efficiently, ensuring that AI training and inference tasks have the necessary resources without causing resource contention.
- Monitoring and Analytics: A Data Fabric can provide monitoring and analytics capabilities to track the performance of AI models, identify anomalies, and optimize resource allocation for AI workloads.
- AI Model Deployment: AI models must be deployed into production environments after training. A Data Fabric can assist in seamlessly deploying models by providing integration with deployment platforms and ensuring the production data is readily available.
A Data Fabric is the foundation for organizations to effectively manage AI initiatives by providing a flexible, scalable, and well-governed data infrastructure. This infrastructure supports the data needs of AI, ensuring that data is accessible, high-quality, and secure throughout the AI lifecycle, from data preparation to model deployment and beyond.
Optimize the Data Fabric with Intelligent Data Operations
Hitachi Vantara Federal’s Pentaho Intelligent Data Operations solutions help agencies build and manage their connected data fabric, deliver trusted data through governance and compliance, and implement an AI/ML-driven cognitive automation strategy.
How does the Pentaho Intelligent DataOps Platform work? The platform enables agencies to automate the daily tasks of collecting, integrating, governing, and analyzing data on an intelligent platform. It provides an open and composable foundation for all enterprise data while providing self-service data access to agencies and user choice of tools and analytics. The portfolio allows agencies to create a seamless data fabric governed by an enhanced data catalog for automated data quality improvements and governance. With Pentaho Intelligent DataOps, agencies can reduce the time and complexity of discovering, accessing, preparing, and blending data across multiple data sources and locations.
The Pentaho Intelligent DataOps Platform specific solutions include:
- Data Integration: To help agencies ingest and distribute IT (Information Technology), OT (Operational Technology), and IoT data.
- Data Catalog: To enable automatic inventory of all data.
- Data Analytics: To help users visualize and analyze data across systems.
- Data Storage Optimizer: To enable cost-optimizing of Hadoop data lakes with smart tiering.
Pentaho DataOps Suite provides organizations with data integration, cataloging, and analytics to orchestrate data flows across all environments. The solutions empower users to break down data silos while ensuring proper governance across the entire data fabric. If your agency works to make all your IT operate smoothly while meeting organizational needs and delivering on its mission, you need a data fabric.
Contact us to speak with one of our solution experts to learn more about Pentaho Intelligent DataOps.
Where to Go From Here?
For more information, check out these resources:
- What is Data Fabric? –https://www.hitachivantara.com/en-us/insights/faq/what-is-data-fabric.html
- Data Fabric Checklist – https://www.hitachivantarafederal.com/wp-content/uploads/2023/09/optimized-cloud-data-fabric-checklist-1.pdf
- Data Fabric for Dummies eBook – https://www.hitachivantarafederal.com/resources-insights/data-fabric-for-dummies/
- Building your Data Fabric with DataOps –https://www.hitachivantarafederal.com/wp-content/uploads/2023/09/building-your-data-fabric-with-dataops.pdf
- BrightTALK Data Fabric 101 – https://www.brighttalk.com/webcast/499/562966