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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. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

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Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Big Data

This post explains how to create a design that automatically backs up Amazon Simple Storage Service (Amazon S3), the AWS Glue Data Catalog, and Lake Formation permissions in different Regions and provides backup and restore options for disaster recovery. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake. For traditional analytics, they are bringing data discipline to their use of Presto. It lands as raw data in HDFS.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk.

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