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MarTech » Performance Marketing » AWS makes it easier to add machine learning prediction models to your martech tools, dashboards

AWS makes it easier to add machine learning prediction models to your martech tools, dashboards

No need to write complicated code to apply predictions to your CRM lead scoring models, for example.

Amy Gesenhues on November 27, 2019 at 12:44 pm

Amazon is bringing its machine learning capabilities to more business analysts and developers. The company announced Tuesday that Amazon Aurora, Amazon Athena and Amazon QuickSight users will now have access to machine learning prediction models that can easily be integrated into various applications and business intelligence dashboards.

“This makes it more straightforward to add ML predictions to your applications without the need to build custom integrations, move data around, learn separate tools, write complex lines of code, or even have ML experience,” writes Matt Asay, an enterprise strategy and evangelism executive for Amazon Web Services.

Why we should care

Amazon Web Service’s machine learning offering is giving developers tasked with writing SQL queries a low-code option to build marketing-related prediction models. Asay used the following lead-scoring example that shows how it can benefit martech developers:

“You can take a lead scoring model built by your data science team, or one that you have purchased on the AWS ML Marketplace, deploy it to Amazon SageMaker, and then order all your sales queues by priority based on the prediction from the model. Unlike in the past, you needn’t write any glue code.”

The win here is for developers and the teams who want to use sophisticated machine learning predictions models, but lack the time or resources to write complex code to do so. AWS’s machine learning offering removes the need to build out code, move data around or learn new tools — opening up machine learning experiences to more organizations using AWS products.

More on the news

  • AWS reports “tens of thousands” customers are already using its machine learning capabilities via Amazon SageMaker, a managed service platform that allows developers to build and deploy ML models at scale.
  • Developers interested in taking advantage of the new ML offerings are directed to visit Amazon’s Aurora, Athena and QuickSight product pages.
  • In addition to machine learning tools, the AWS Marketplace includes data analytics and data product software, as well as other enterprise solutions.

Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


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About The Author

Amy Gesenhues
Amy Gesenhues was a senior editor for Third Door Media, covering the latest news and updates for Marketing Land, Search Engine Land and MarTech Today. From 2009 to 2012, she was an award-winning syndicated columnist for a number of daily newspapers from New York to Texas. With more than ten years of marketing management experience, she has contributed to a variety of traditional and online publications, including MarketingProfs, SoftwareCEO, and Sales and Marketing Management Magazine. Read more of Amy's articles.

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