Person managing product information

Gartner, Forrester, and IDC analysts all 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.

What is data fabric?

Gartner defines data fabric as a design concept that serves as an integrated layer (fabric) of data and connecting processes.

A data fabric uses 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.

Gartner identifies these five key pillars of a data fabric:

  1. Augmented data catalog: Data fabric must collect and analyze all forms of metadata using AI/ML automation.
  2. Knowledge graph enriched with semantics: Data fabric must create and curate knowledge graphs and enable analytics over connected metadata in a knowledge graph using AI/ML algorithms.
  3. Metadata activation and recommendation engine: Data fabric must convert passive metadata to AI/ML-assisted active metadata.
  4. Data preparation and data delivery: Data fabric must have a robust, AI-powered data integration backbone.
  5. Orchestration and DataOps: Data fabric must have the capability to automate data orchestration with AI/ML assistance.

Why do you need a data fabric?

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.

Data fabric benefits:

A data fabric enables speed, resilience, and efficiency, resulting in reduced costs, increased productivity, and faster time to value. Here are a few examples:

  • Accelerates self-service data discovery and analytics by making trusted data accessible faster to all data consumers.
  • Automates data engineering tasks and augments data integration to deliver real-time insights.
  • Automates data governance and protection by leveraging active metadata for data quality improvements, data curation, data classification, policy enforcement, and more.
  • Automates workload orchestration, along with elastic scaling, self-tuning, self-healing, preparing your jobs for any environment and any data volume.
  • Automates linking discovered data assets and enriching them with knowledge and semantics, allowing consumers to find and understand the data.

Informatica enables the five key pillars of a data fabric

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.

  • Provides comprehensive metadata connectivity for all enterprise data.
  • Enables AI-powered automatic discovery, automated data lineage, classification of data assets along with business context.
  • Facilitates collaboration and social curation to tap into shared data knowledge from the community.
  • Delivers data asset analytics to understand and measure data value and increase levers to improve data value.

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

  • Facilitates understanding of your data assets and data models, with an automatically assembled knowledge graph.
  • Enables exploration and navigation of networks of relationships to uncover value of new connections between existing data.
  • Enables holistic enterprise views, data sharing, and self-service with auto-generated, cross-departmental knowledge graph.
  • Automatically links identities to sensitive data in compliance with GDPR and other data privacy regulations.

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.

  • Enables comprehensive, unified metadata foundation with 50,000+ metadata-aware scanners and broadest deployment of AI/ML algorithms.
  • Activates metadata to deliver intelligent automation for all data management functions like integration, preparation, data quality, governance, and master data management.
  • Provides intelligent recommendations like next-best transformation, additional data assets, data quality rules, and more.

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.

  • Provides capability to discover, explore, prepare, integrate, publish, visualize, and share data, collaborate on data, and operationalize in a single environment.
  • Includes Excel-like interface for advanced data preparation to blend, transform, cleanse, enrich, shape by leveraging 100s of pre-built data quality rules.
  • Enables fine-grained control of data preparation activities by providing capability to define and manage user access privileges.
  • Delivers intelligent recommendations like alternate data assets and next-best action and more.

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.

  • Enables end-to-end CI/CD approach with DataOps, MLOps, and InfoSecOps capabilities.
  • Applies AI capabilities in the data lifecycle to automate tasks, auto-scale, self-tune, self-heal, and self-secure.
  • Reduces test cases by 100x with metadata-driven and dynamic template approach that maximizes reusability and auto-generation of data pipelines.
  • Delivers intelligent operational insights for continuous observation and improvement.

Informatica data fabric benefits

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 transforms complex technology into extraordinary business performance with a data fabric

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.

The transformative next step is data fabric

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.

Get started with an intelligent data fabric to accelerate your AI initiatives

To learn how Informatica can accelerate your AI initiatives, visit our Intelligent Data Management Cloud page.