Remove Data Processing Remove Metadata Remove Unstructured Data
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Implement a custom subscription workflow for unmanaged Amazon S3 assets published with Amazon DataZone

AWS Big Data

Although Amazon DataZone automates subscription fulfillment for structured data assetssuch as data stored in Amazon Simple Storage Service (Amazon S3), cataloged with the AWS Glue Data Catalog , or stored in Amazon Redshift many organizations also rely heavily on unstructured data. Enter a name for the asset.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

In many cases, this eliminates the need for specialized teams, extensive data labeling, and complex machine-learning pipelines. The extensive pre-trained knowledge of the LLMs enables them to effectively process and interpret even unstructured data. Robert bridges tech and business, advocating user-centric digitization.

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SAP enhances Datasphere and SAC for AI-driven transformation

CIO Business Intelligence

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments. “We

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How ZS built a clinical knowledge repository for semantic search using Amazon OpenSearch Service and Amazon Neptune

AWS Big Data

We use leading-edge analytics, data, and science to help clients make intelligent decisions. We developed and host several applications for our customers on Amazon Web Services (AWS). These embeddings, along with metadata such as the document ID and page number, are stored in OpenSearch Service.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. On the navigation pane, select Crawlers.

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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs.

Metadata 124
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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Less data gets decompressed, deserialized, loaded into memory, run through the processing, etc.

Metadata 105