Tamr

EGUIDE:Potentially a surprise to no one—machine learning (ML) technologies are not only here to stay, but are becoming mainstream for data analytics and management pros. Read this e-guide to learn why machine learning interests have snowballed so suddenly, and what benefits a more liberal use of ML technologies could bring to your business.

Posted: 23 Oct 2019 | Published: 23 Oct 2019

WHITE PAPER:Due to changing requirements, modern data and analytics use cases need a portfolio of capabilities that cannot be fulfilled by existing, stand-alone products. Dive into this Gartner white paper to learn how modern data and analytics requirements demand a convergence of data management capabilities.

Posted: 16 Oct 2019 | Published: 11 Sep 2019

WHITE PAPER:Read this research paper for insights from data and analytics professionals, as well as an overview of current trends in DataOps and how it’s helping appease these pain points.

Posted: 11 Oct 2019 | Published: 11 Oct 2019

WHITE PAPER:Organizations with a wealth of customer data distributed across a variety of systems need a way to unify this data. Read this white paper to find out about a new MDM reference architecture, based on Tamr, that applies machine learning algorithms to remedy these problems—and more.

Posted: 10 Oct 2019 | Published: 10 Oct 2019

WHITE PAPER:In this white paper, discover why old approaches to data mastering are no longer sufficient in keeping up with increasing data volume, velocity, and variety. Explore how data mastering with human-guided machine learning can help your organization deliver decision-driving analytics from unified data, improve business processes, and more.

Posted: 23 Aug 2019 | Published: 23 Aug 2019

WHITE PAPER:Read this e-book to learn more about what makes DataOps a revolutionary strategy that keeps traditional businesses competitive with a growing number of digital-native rivals—and how to execute it right.

Posted: 10 Jun 2019 | Published: 31 Dec 2018

WHITE PAPER:In reality, data comes from a wide array of sources that aren't easily accessible and are often times plagued with inaccuracies—and it's not always the tech that's the problem. Read this white paper to discover the process of "agile data mastering"—which could help you get a better grasp on your data and decision-making.

Posted: 05 Jun 2019 | Published: 31 Dec 2018

WHITE PAPER:Gartner predicts that by 2022, data preparation will be utilized in more than 70% of new data integration projects for analytics and data science. Now is the time to get a job on your preparation strategies - read this Gartner report for more information.

Posted: 26 Apr 2019 | Published: 31 Dec 2018

WHITE PAPER:When applied correctly, artificial intelligence (AI) and machine learning (ML) can solve business-critical challenges and provide actionable insights for enterprises. With new technologies like AI and ML comes many questions - read this white paper for the answers.

Posted: 11 Apr 2019 | Published: 31 Dec 2018

RESOURCE:Having dirty data can often be worse than not having any data at all, according to prominent data scientist Ihab Ilyas. Read this 15-page chapter excerpt by Ilyas on modern data integration platforms and a "data tamer" that can enable your data analysts to get high-quality data quickly.

Posted: 12 Mar 2019 | Published: 12 Mar 2019

WHITE PAPER:This resource compares different technical approaches to achieving clean, accurate, consolidated data sets, and provides an introduction to data unification – highlighting 7 principles that data management pros should consider.

Posted: 29 May 2018 | Published: 29 May 2018

CASE STUDY:A multinational medical devices, pharmaceutical, and consumer packaged goods organization needed to unify the disparate datasets to provide a single view of all customers and products that would feed downstream analytic tools. Explore the approaches they tested, and what option they ultimately selected.

Posted: 25 May 2018 | Published: 25 May 2018

EBOOK:This 36-page e-book details the current status of DataOps and the practical steps enterprises should take to pay down their data debt – including behavioral and technological – all of which center around data unification. Dive deep into DataOps best practices, real world examples and much more.

Posted: 25 May 2018 | Published: 25 May 2018