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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. target_iceberg_add_files/metadata/.

Data Lake 102
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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. To overcome these issues, Orca decided to build a data lake.

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Chose Both: Data Fabric and Data Lakehouse

Cloudera

Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. And second, for the data that is used, 80% is semi- or unstructured. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse.

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Discover Efficient Data Extraction Through Replication With Angles Enterprise for Oracle

Jet Global

The Challenges of Extracting Enterprise Data Currently, various use cases require data extraction from your OCA ERP, including data warehousing, data harmonization, feeding downstream systems for analytical or operational purposes, leveraging data mining, predictive analysis, and AI-driven or augmented BI disciplines.