Kariba intelligently catalogs and organizes all your data assets and makes them searchable, findable, and consumable by Data Analysts and Data Scientists. Kariba is the first of its kind data catalog solution developed with data consumers in mind. It is an open platform to build applications on and a window into all your enterprise data assets.

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The Data Catalog is an Essential Capability to Support Self-Serve needs of Analytic Users

Discover the structure of all data catalogs and its associated business terminology and definitions for a better understanding of data sources by IM, Data Services, Informatics, Support Teams, Consuming Systems, and Business Stakeholders
Find relevant data, where it came from, how it’s been used, and why it matches; Directed and deep search guided by relevance can be used anywhere across the business, technical, and operational context
Improve communication between business stakeholders, data owners, stewards, and data analysts fostering a more collaborative approach to data management.
White papers, Source-to-Target Maps, and conversations about data provide context to the data in the catalog, identify relevant business information, and provide resources to find the right data and experts
Users can easily identify tables or columns which contain sensitive information, protecting information workers and providing clarity for data delivery tasks
Select data assets to copy or view within a sandbox managed by the user, in a self-serve model, or as a collaborative group, in a shared model

Data Consumer Self-Service Interface

Search and Explore All Levels of Metadata with Kariba

Kariba aggregates business, descriptive, and technical metadata into the catalog:

• Level One: Directly associated to registered assets (technical)

• Level Two: Enriched metadata associated with registered assets (business,
operational)

• Level Three: Profiled data extracted and indexed from registered assets (codes,
unique IDs)

• Level Four: Relationship maps of registered assets (keys)

Understand Data Lineage from Source to Publication

Perform Impact Analysis – Visibility into data flows throughout the Information Supply Chain by maintaining the lineage of all ingestion sources and data mappings with relevant trusted information.
• Improve Report and Application Development – Understand data delivery end-points from a business and recommended usage point of view, with the ability to follow lineage back through all zones and to the originating data source.
Support Self-Service Data Provisioning – Intuitive interface leveraging machine learning recommendations to help data consumers select the right data assets to copy or view into a sandbox managed by the user or as a collaborative group, for further analysis and modeling.

Learn how Kariba can help you maximize the value of information in your organization.

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