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Use Amazon Athena with Spark SQL for your open-source transactional table formats

AWS Big Data

These formats enable ACID (atomicity, consistency, isolation, durability) transactions, upserts, and deletes, and advanced features such as time travel and snapshots that were previously only available in data warehouses. It will never remove files that are still required by a non-expired snapshot.

Snapshot 106
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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

In this post, we look into an optimal and cost-effective way of incorporating dbt within Amazon Redshift. In an optimal environment, we store the credentials in AWS Secrets Manager and retrieve them. Snapshots – These implements type-2 slowly changing dimensions (SCDs) over mutable source tables.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275
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Your Introduction To CFO Dashboards & Reports In The Digital Age

datapine

By including this cohesive mix of visual information, every CFO, regardless of sector, can gain a clear snapshot of the company’s fiscal performance within the first quarter of the year. Torture the data, and it will confess to anything.”— Ronald Coase. What A CFO Dashboard Or Report Should Focus On? 3) CFO-centric design.

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

AWS Big Data

Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. At the top of the hierarchy is the metadata file, which stores information about the table’s schema, partition information, and snapshots.

Data Lake 123
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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 118
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Bionic Eye, Disease Control, Time Crystal Research Powered by IO500 Top Storage Systems

CIO Business Intelligence

The tech giant’s mid-range storage product has also been equipped with new VMware integrations, including improved vVols latency and performance, simplified disaster recovery with vVols replication, as well as VM-level snapshots and fast clones. Intel® Technologies Move Analytics Forward.