Remove Download Remove Metadata Remove Structured Data
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Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes. Table metadata is fetched from AWS Glue.

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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. The synchronization process in XTable works by translating table metadata using the existing APIs of these table formats.

Metadata 105
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Deep automation in machine learning

O'Reilly on Data

For any codebase, it can tell you where the code came from (provenance), and all the changes that led from the original commit to the version you downloaded. If you suddenly see unexpected patterns in your social data, that may mean adversaries are attempting to poison your data sources.

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Salesforce debuts Zero Copy Partner Network to ease data integration

CIO Business Intelligence

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

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Why Your Data Lineage is Incomplete Without an Automated Business Glossary

Octopai

While some businesses suffer from “data translation” issues, others are lacking in discovery methods and still do metadata discovery manually. Moreover, others need to trace data history, get its context to resolve an issue before it actually becomes an issue. The solution is a comprehensive automated metadata platform.

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Enhance query performance using AWS Glue Data Catalog column-level statistics

AWS Big Data

Data lakes are designed for storing vast amounts of raw, unstructured, or semi-structured data at a low cost, and organizations share those datasets across multiple departments and teams. The queries on these large datasets read vast amounts of data and can perform complex join operations on multiple datasets.

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Implement data quality checks on Amazon Redshift data assets and integrate with Amazon DataZone

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Amazon DataZone natively supports data sharing for Amazon Redshift data assets. In the post_dq_results_to_datazone.py