Data Fabric Solution

It is a marketplace to find, collaborate, get access to data (this could also include a feature store, or popular queries, etc.) and ability to query data anywhere. Business users need to have self-service access to quality data so that they can make the most out of it, having the minimum support from IT.

The intelligent catalog is infused with machine learning and AI to get a good data quality, metadata across your organization, an also to be able to search for relevant assets required for your analysis.

To avoid moving data unnecessarily you need to have an effective pipeline to access your data. With a range of integration styles to extract, ingest, stream, virtualize, and transform data, driven by data policies to maximize performance while minimizing storage and egress costs, and ability to train models without copying data (e.g., vertical federated learning).

It is important to have an unified definition and enforcement of data policies tied to the other layers (i.e., associate policies with data, control access, etc.), data governance, data quality and data stewardship.

It is necessary to define an end-to-end lifecycle to compose, build, test, deploy, and manage the various aspects of the data fabric (e.g., compose, deploy, and manage a data pipeline).

A Data Fabric allows to automate data engineering tasks and augment data integration across hybrid cloud resources. It aims to address the data challenges arising out of a hybrid data landscape.

As part of a modern data management approach, a robust governance and privacy capability helps organizations thrive in the midst of growing data volume. With an integrated data governance layer in the Data Fabric architecture you will be able to shape behavior around data quality, privacy, security and management.

This solution automatically enriches discovered data assets with knowledge and semantics, allowing consumers to find
and understand the data.

A Data Fabric allows to identify challenges and opportunities to speed up and improve decision making, base on accurate data  applications

The self-service capability of the Data Fabric architecture enables the reduction of data bottlenecks resulting in greater productivity, enabling business users to make faster business decisions.