Remove 2015 Remove Data Analytics Remove Data Warehouse Remove Metadata
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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. The output will give a count of the number of data and metadata files deleted.

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The Very Group adopts a data catalog to better organize and leverage its online retail capabilities

CIO Business Intelligence

It launched its first online-only brand, Very, in 2009 and finally abandoned its printed catalogs to go all-in online in 2015. He found a rich collection of data assets, including information on over 2.2 As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence.

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Turning Streams Into Data Products

Cloudera

In 2015, Cloudera became one of the first vendors to provide enterprise support for Apache Kafka, which marked the genesis of the Cloudera Stream Processing (CSP) offering. The DevOps/app dev team wants to know how data flows between such entities and understand the key performance metrics (KPMs) of these entities.

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How SumUp made digital analytics more accessible using AWS Glue

AWS Big Data

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.