Industry analysts widely agree that data fabrics are key to data and analytics transformation in 2021 and beyond. A data fabric integrates and connects all your organization’s data for improved business outcomes. The ROI around data fabric can be recognized as the business value aggregate of a new degree of automation of data-driven insight.
Gartner® defines “data fabric as a design concept that serves as an integrated layer (fabric) of data and connecting processes. A data fabric utilizes continuous analytics over existing, discoverable and inferenced metadata assets to support the design, deployment and utilization of integrated and reusable data across all environments, including hybrid and multi-cloud platforms.”1
The complexities of modern data management are expanding rapidly as new technologies, new kinds of data, and new platforms are introduced. Changing and bolstering data management methods with each technological shift is difficult and disruptive. With technology innovation accelerating, the traditional approach to data management has become unsustainable.
A data fabric can minimize disruption by creating a highly adaptable data management strategy with augmented data integration and management.
A data fabric is agnostic to deployment platforms, data processing methods, data delivery methods, locations, and architectural approach. It facilitates the use of data as a strategic asset by abstracting complexity. A data fabric ensures any data on any platform from any location can be successfully combined, accessed, shared, and governed efficiently and effectively.
A data fabric enables speed, resilience, and efficiency, resulting in reduced costs, increased productivity, and faster time to value. Here are a few examples:
Informatica Intelligent Data Fabric is a hybrid, multi-cloud data fabric that enables autonomous data management and delivers trusted data for your AI initiatives.
1.Augmented data catalog: The AI-powered, Intelligent Data Catalog enables you to find, understand, and prepare all your data with AI-driven metadata discovery and data cataloging.
2. Knowledge graph enriched with semantics: Enterprise Knowledge Graph, a capability within the metadata-driven AI engine (CLAIRE), puts data in context by linking and enriching semantic metadata to deliver intelligence to data management functions like data cataloging, data governance, data integration, data quality and master data management
3. Metadata activation and recommendation engine: The CLAIRE engine learns your data landscape to automate thousands of manual tasks and augment human activity with recommendations and insights, allowing you to scale your data management to meet your business’s needs.
4.Data preparation and data delivery: Enterprise Data Preparation enables you to simplify and speed up data preparation with advanced ML-based automation and data cataloging.
5.Orchestration and DataOps: Enterprise orchestration and XOps enables automatic orchestration of all data delivery flows by employing DataOps, MLOps, and InfosecOps in support of continuous analysis and monitoring. InfosecOps in support of continuous analysis and monitoring.
Expedites time to value: Industry-leading innovations in active metadata and AI/ML-powered data management accelerates time to value.
Optimizes costs while maintaining elasticity: Flexible consumption-based pricing optimizes your data management costs by enabling you to dynamically scale up or down and leverage capabilities that fit your needs.
Facilitates data-driven decision-making: Automated data governance and privacy enforce governance and compliance across all data consistently. Increases transparency and collaboration while reducing compliance risks.
Supports multi-cloud, hybrid environments: Multi-hybrid, multi-cloud enables you to run, interoperate, and support any combination of cloud and hybrid infrastructures.
BMC software (BMC) helps companies around the world harness technology to improve the delivery and consumption of digital services. The company’s accounts payable (AP) and generic ledger (GL) operations were handled by decentralized regional services centers, using manual processes. This, in turn, caused a widespread lack of standardization across countries that impacted the BMC treasury team’s ability to view current account balances, resulting in the need to maintain excessive cash reserves to cover the possible occurrence of any unpredicted cash needs.
With Informatica, BMC built a functional system in a very short period of time and then layered on more sophisticated capabilities. The company dramatically improved visibility into actual and projected cash flows, enabling them to better manage cash positions and optimize use of their working capital.
BMC saved hundreds of thousands of dollars and have much better reporting and control across the hundreds of bank accounts. They now have accurate and timely visibility into their cash holdings and have been able to elevate the rigor behind their risk management and mitigation strategies.
Data fabric is the transformative next step for your enterprise. With a data fabric, you can automate data management in a hybrid, multi-cloud data landscape. Employ a data fabric to enable faster time-to-value for business users, increase productivity for data engineering, provide greater efficiency for operations, and deliver robust governance and compliance fidelity.
To learn how Informatica can accelerate your AI initiatives, visit our Intelligent Data Management Cloud page.
1 Smarter With Gartner, “Data Fabric Architecture is Key to Modernizing Data Management and Integration,” May 11, 201, https://www.gartner.com/smarterwithgartner/data-fabric-architecture-is-key-to-modernizing-data-management-and-integration
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