Data Fabric

Connecting Your Business with a Universe of Actionable Data Insights

Metadata Management

Metadata is essential context for understanding relationships and meaning across datasets. A data fabric uses all types of metadata including structural, descriptive and administrative data to continuously collect and analyze information about other data. Active metadata is enabled through embedding machine learning models that allow metadata to be programmatically created and processed at massive scales.

Knowledge Graphs

Knowledge graphs play a key role by formally representing the real-world relationships between entities that exist within the data. They semantically link information by describing the intended meaning of different data components. A data fabric further enhances knowledge graphs over time by incorporating inferences from ongoing metadata analysis to provide richer context.

Data Ingestion and Processing

Multiple data sources containing both structured and unstructured information must be identified and connected. Relevant data is then extracted through transformation and processing operations. A data fabric supports various integration approaches to accommodate different workload needs, including batch-based ETL, real-time data streaming, application integration interfaces, and virtualized access.

Data Access and Integration

Once processed, data must be cleaned and integrated before being orchestrated to consumers based on their needs. A data fabric provides self-service capabilities for exploring governed data employing analytics and reporting tools. It also ensures consistent handling of data across distributed environments spanning cloud platforms, on-premises infrastructure and edge devices.

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Complex Implementations

Anthropic has deep experience unifying massive-scale, heterogeneous datasets across diverse infrastructure footprints. Semantic technologies and graph-based approaches are specialized areas of focus applied to continuously enhance metadata assets.

Comprehensive Methodologies

A holistic methodology is employed considering all necessary pillars for successful data fabric deployments. Both technical and organizational change management factors are addressed from a best practice, people-process-technology perspective.

Continued Optimization

Dedicated support does not end at go-live, as Anthropic ensures the data fabric continuously adapts to new workloads, use cases and information sources through ongoing monitoring, improvements and expansions.

Tangible Business Value

Measurable ROI is consistently achieved in strategic areas like insights-driven decision making, innovation initiatives and operational efficiencies by empowering self-service data access and democratization across an organization.

Data Fabric

Connecting Your Business with a Universe of Actionable Data Insights

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