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Deep dive into the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

Additionally, a TCO calculator generates the TCO estimation of an optimized EMR cluster for facilitating the migration. After you complete the checklist, you’ll have a better understanding of how to design the future architecture. For the compute-heavy workloads such as MapReduce or Hive-on-MR jobs, use CPU-optimized instances.

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Cloudera Data Engineering 2021 Year End Review

Cloudera

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. .

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. The ultimate goal is to raise awareness of cloud efficiency and optimize cloud utilization in a cost-effective and sustainable manner.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale. Shashank Tewari is a Senior Technical Account Manager at AWS.

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Power enterprise-grade Data Vaults with Amazon Redshift – Part 1

AWS Big Data

Building a starter version of anything can often be straightforward, but building something with enterprise-grade scale, security, resiliency, and performance typically requires knowledge of and adherence to battle-tested best practices, and using the right tools and features in the right scenario. Data Vault 2.0

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Data platform trinity: Competitive or complementary?

IBM Big Data Hub

A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.