Remove Data Governance Remove Data Lake Remove Structured Data Remove Visualization
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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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

AWS Big Data

A data hub is a center of data exchange that constitutes a hub of data repositories and is supported by data engineering, data governance, security, and monitoring services. A data hub contains data at multiple levels of granularity and is often not integrated.

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Data Swamp, Data Lake, Data Lakehouse: What to Know

Alation

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

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Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

The solution uses AWS services such as AWS HealthLake , Amazon Redshift , Amazon Kinesis Data Streams , and AWS Lake Formation to build a 360 view of patients. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.