Remove Big Data Remove Data Warehouse Remove Operational Reporting
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How Gupshup built their multi-tenant messaging analytics platform on Amazon Redshift

AWS Big Data

About Redshift and some relevant features for the use case Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that offers simple operations and high performance. This compiled data is then imported into Aurora PostgreSQL Serverless for operational reporting.

Analytics 119
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How HPE Aruba Supply Chain optimized cost and performance by migrating to an AWS modern data architecture

AWS Big Data

The application supports custom workflows to allow demand and supply planning teams to collaborate, plan, source, and fulfill customer orders, then track fulfillment metrics via persona-based operational and management reports and dashboards. The following diagram illustrates the solution architecture.

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

Jet Global

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster.

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

Data Lake 115
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Migrate data from Azure Blob Storage to Amazon S3 using AWS Glue

AWS Big Data

Conclusion In this post, we showed how to use AWS Glue and the new connector for ingesting data from Azure Blob Storage to Amazon S3. This connector provides access to Azure Blob Storage, facilitating cloud ETL processes for operational reporting, backup and disaster recovery, data governance, and more.

Data Lake 111
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Use AWS Glue to streamline SFTP data processing

AWS Big Data

Introducing the SFTP connector for AWS Glue The SFTP connector for AWS Glue simplifies the process of connecting AWS Glue jobs to extract data from SFTP storage and to load data into SFTP storage. Solution overview In this example, you use AWS Glue Studio to connect to an SFTP server, then enrich that data and upload it to Amazon S3.