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Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore federation

AWS Big Data

Use cases for Hive metastore federation for Amazon EMR Hive metastore federation for Amazon EMR is applicable to the following use cases: Governance of Amazon EMR-based data lakes – Producers generate data within their AWS accounts using an Amazon EMR-based data lake supported by EMRFS on Amazon Simple Storage Service (Amazon S3)and HBase.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Data architecture strategy for data quality

IBM Big Data Hub

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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How Knowledge Graphs Power Data Mesh and Data Fabric

Ontotext

Data Lakes, Data Catalogs, and Findability Organizations approach data lakes as cheap storage. They move data to data lakes creating another copy – the mantra being – “ Lets move the data to a data lake and then we will figure out what to do with it”.

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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications. Learn more about the zero-ETL integrations, data lake performance enhancements, and other announcements below.

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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. They require specific data inputs, models, algorithms and they deliver very specific recommendations.

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Modernizing the Data Warehouse: Challenges and Benefits

BI-Survey

The primary modernization approach is data warehouse/ETL automation, which helps promote broad usage of the data warehouse but can only partially improve efficiency in data management processes. However, an automation approach alone is of limited usefulness when data management processes are inefficient.