Mantra wires your enterprise with AI-ready data — federated, contextualized, and intent-resolved — so any agent can deliver insights you can trust.
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When it comes to managing access to data on an organizational level, there are a number of models that are used the latest is data fabric.
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A data fabric creates a virtual layer that joins all of an organization’s data with the process and platforms necessary for decisionmaking.
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The growth and increasing complexity of enterprise data architectures have created a need for the ability to query multiple dataset.
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Data Silos have become something of a dirty word within the data management, analytics and storage industries because they make it difficult
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As the variety of data being used to make data-derived decisions expands, the scope and requirements for metadata services also expands.
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Here are a few tips for making your dashboard a go-to resource for your organization’s decision makers.
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The Data Fabric concept pushes beyond traditional thinking and is a big idea for changing the way data is made accessible.
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Extract, transform, load (ETL) describes the process of copying data from a single or multiple repositories into a new centralized system.
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Augmented analytics involves using machine learning and natural language processing (NLP) to assist with data prep, analysis and reporting.
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The industry has looked to several models to collect, store and impose order on an organization’s data. The Data Lake is one of them.
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A data warehouse is a data management system designed to support business intelligence (BI) activities.
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Sample Data Engineer Job Description.
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