Remove Data Warehouse Remove Metadata Remove Structured Data Remove Testing
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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. It consists of full-day and intraday tables.

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Key considerations when making a decision on a Cloud Data Warehouse

Cloudera

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

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Data platform trinity: Competitive or complementary?

IBM Big Data Hub

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

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Implement a serverless CDC process with Apache Iceberg using Amazon DynamoDB and Amazon Athena

AWS Big Data

On the Code tab, choose Test , then Configure test event. Configure a test event with the default hello-world template event JSON. Configure a test event with the default hello-world template event JSON. Provide an event name without any changes to the template and save the test event.

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Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

AWS Big Data

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. Navigate to the side menu Virtual clusters , then select the HiveDemo cluster , You can see an entry for the SparkSQL test job.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.