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DS Smith sets a single-cloud agenda for sustainability

CIO Business Intelligence

Its digital transformation began with an application modernization phase, in which Dickson and her IT teams determined which applications should be hosted in the public cloud and which should remain on a private cloud. Having that data in the cloud and piping it into our data pipelines is a much more effective way to do that.”

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10 Things AWS Can Do for Your SaaS Company

Smart Data Collective

Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. Management of data. Artificial intelligence (AI). Messages and notification. Easy to use. Thank you for taking the time to read this blog post.

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Announcing the 2021 Data Impact Awards

Cloudera

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. We saw a record number of entries and incredible examples of how customers were using Cloudera’s platform and services to unlock the power of data. DATA FOR ENTERPRISE AI.

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Introducing Amazon EMR on EKS job submission with Spark Operator and spark-submit

AWS Big Data

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows organizations to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). This performance-optimized runtime offered by Amazon EMR makes your Spark jobs run fast and cost-effectively. The EMR runtime provides up to 5.37

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Join a streaming data source with CDC data for real-time serverless data analytics using AWS Glue, AWS DMS, and Amazon DynamoDB

AWS Big Data

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Traditional batch ingestion and processing pipelines that involve operations such as data cleaning and joining with reference data are straightforward to create and cost-efficient to maintain. options(**additional_options).mode("append").save(s3_output_folder)

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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How Gilead used Amazon Redshift to quickly and cost-effectively load third-party medical claims data

AWS Big Data

This data volume is expected to increase monthly and is fully refreshed each month. The 3-node RA3 16XL provisioned cluster that had previously been hosting their warehouse was taking around 12 hours to ingest this data to Amazon Redshift , and Gilead was looking to optimize the data ingestion process in a more dynamic manner.