Tamr Announces Cloud-Native Capabilities on AWS to Help Customers Achieve Cost-Effective Data Mastering

Customers, such as Johnson & Johnson, are running Tamr on AWS to prepare analytics-ready datasets, leveraging AWS analytic services to drive business insights using clean, curated data.

Tamr, Inc., a cloud-native data mastering platform used by some of the world’s largest enterprises to solve their toughest data challenges, today announced cloud-native deployment of Tamr’s software on Amazon EMR, Amazon Relational Database Service (Amazon RDS), Amazon Elasticsearch Service (Amazon ES), and Amazon Simple Storage Service (Amazon S3). This deployment allows customers, including global healthcare company Johnson & Johnson, to master their data with Tamr while taking advantage of the flexibility, scalability, and analytic services of Amazon Web Services (AWS) to drive business insights and cost savings.

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Johnson & Johnson, a Tamr and AWS customer, uses appropriately scaling cloud services to better approach its consumer product mastering projects. This data provides Johnson & Johnson with better visibility into its global product base, leading to increased sales. Additionally, replacing manual data preparation processes with machine learning has generated cost savings and faster business analytics.

“Cloud computing lets us increase and decrease our storage and compute usage based on demand, allowing us to more efficiently master data,” said Peter Tsang, Data & Analytics Product Line Owner, at Johnson & Johnson.

Tamr’s data mastering solutions use machine learning instead of rules to do the heavy lifting to consolidate, cleanse, and categorize data as customers provide feedback, while the cloud-native capabilities of AWS let customers scale their usage of compute and storage. Tamr’s approach lets customers more easily prepare analytics-ready datasets, including golden records, and leverage the broad range of AWS analytic services to drive business insights.

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“Companies are moving their data to AWS, which provides them with immediate access to an elastic and ephemeral platform. These developments create an ideal situation for using machine learning to master data. Companies can scale up their compute and storage usage based on their needs, allowing them to cost-effectively master data compared to on-premise deployments. Machine learning and the cloud are key components in adopting a modern approach to data management,” said Tamr Chief Product Officer, Anthony Deighton.

In addition to Johnson & Johnson, companies including Toyota, Thomson Reuters, and Novartis run Tamr on AWS to boost business outcomes such as improving customer service, increasing sales, and optimizing spending.

“Organizations need ways to quickly cleanse, consolidate, and categorize data from multiple – often siloed – operational systems,” said Jorge A. Lopez, Global Lead, Big Data & Analytics Partner Strategy, Amazon Web Services, Inc. “We are delighted to work with Tamr to help customers curate and consolidate their data into a data lake on Amazon S3, making it available to a broad set of analytic engines to drive relevant business outcomes.”

Tamr achieved Advanced Technology Partner status in the AWS Partner Network (APN) as well as AWS Machine Learning Competency status and AWS Data and Analytics Competency status, providing customers with the highest confidence in Tamr’s capabilities when deployed on AWS. Customers benefit from working with AWS and Tamr as one collaborative team, and have the option to purchase Tamr through the AWS Marketplace. Tamr and AWS are dedicated to providing enterprises with the cloud expertise and data mastering technology needed to drive transformational business outcomes.

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AWSAWS Partner NetworkCloud-Native CapabilitiesCost-Effective Data Masteringdata masteringJohnson & JohnsonNewsTamr
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