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Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS Big Data

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 103
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Salesforce debuts Zero Copy Partner Network to ease data integration

CIO Business Intelligence

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

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Access Amazon Redshift data from Salesforce Data Cloud with Zero Copy Data Federation

AWS Big Data

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 111
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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

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Informatica’s new data management clouds target health, finance services

CIO Business Intelligence

In order to help maintain data privacy while validating and standardizing data for use, the IDMC platform offers a Data Quality Accelerator for Crisis Response. Cloud Computing, Data Management, Financial Services Industry, Healthcare Industry

Finance 140
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Read and write S3 Iceberg table using AWS Glue Iceberg Rest Catalog from Open Source Apache Spark

AWS Big Data

In today’s data-driven world , organizations are constantly seeking efficient ways to process and analyze vast amounts of information across data lakes and warehouses. This post will showcase how this data can also be queried by other data teams using Amazon Athena. Verify that you have Python version 3.7

Data Lake 106
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Optimize your workloads with Amazon Redshift Serverless AI-driven scaling and optimization

AWS Big Data

The current scaling approach of Amazon Redshift Serverless increases your compute capacity based on the query queue time and scales down when the queuing reduces on the data warehouse. This post also includes example SQLs, which you can run on your own Redshift Serverless data warehouse to experience the benefits of this feature.