Remove 2022 Remove Data Analytics Remove Metadata Remove Snapshot
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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

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AI at Scale isn’t Magic, it’s Data – Hybrid Data

Cloudera

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. And that data is likely in clouds, in data centers and at the edge.

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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

Iceberg doesn’t optimize file sizes or run automatic table services (for example, compaction or clustering) when writing, so streaming ingestion will create many small data and metadata files. Offers different query types , allowing to prioritize data freshness (Snapshot Query) or read performance (Read Optimized Query).

Data Lake 109
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Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.