Remove Interactive Remove Metadata Remove Structured Data Remove Visualization
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Data governance in the age of generative AI

AWS Big Data

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Let’s look at some of the key changes in the data pipelines namely, data cataloging, data quality, and vector embedding security in more detail.

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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

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Turbocharging Target Identification: Ontotext’s AI-Powered Solution at Work

Ontotext

What if we first find out how a disease occurs, what pathological processes are involved on the cellular and molecular levels, which genes and proteins play a role and how they interact? They frequently spend hours reading through hundreds of publications to find new insights and then confirm them with structured information.

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Success Stories: Applications and Benefits of Knowledge Graphs in Financial Services

Ontotext

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

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Next-Gen Graph Technology: A CDO Matters Podcast with Ontotext’s CMO Doug Kimball

Ontotext

And the other thing is another way of displaying it or visualizing it, which is a little more node based or hierarchically based. Doug : You’ve got nodes that describe data and edges that describe the relationships between them. Would you agree with what I just said? I’m a CDO and I’m intrigued.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

AWS Glue crawls both S3 bucket paths, populates the AWS Glue database tables based on the inferred schemas, and makes the data available to other analytics applications through the AWS Glue Data Catalog. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.