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Multicloud data lake analytics with Amazon Athena

AWS Big Data

Many organizations operate data lakes spanning multiple cloud data stores. In these cases, you may want an integrated query layer to seamlessly run analytical queries across these diverse cloud stores and streamline your data analytics processes. Refer to the respective documentation for details.

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Announcing the AWS Well-Architected Data Analytics Lens

AWS Big Data

We are delighted to announce the release of the Data Analytics Lens. Using the Lens in the Tool’s Lens Catalog, you can directly assess your Analytics workload in the console, and produce a set of actionable results for customized improvement plans recommended by the Tool. What’s new in the Data Analytics Lens?

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

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. Apache Iceberg integration is supported by AWS analytics services including Amazon EMR , Amazon Athena , and AWS Glue. AWS Glue 3.0

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Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Insiders Cite The Wondrous Benefits Of Big Data In Fortnite

Smart Data Collective

Big data in the gaming industry has played a phenomenal role in the field. We have previously talked about the benefits of using big data by gaming providers that offer cash games, such as slots. However, more mainstream games use big data as well. Big Data is the Lynchpin of the Fortnite Gaming Experience.