Periscope Data Announces AWS SageMaker Solution to Power Machine Learning
Today, Periscope Data announced a machine learning integration with Amazon SageMaker as part of a comprehensive offering for data teams looking to solve complex machine learning problems within one seamless workflow. This solution is available today and customers can request to test it as part of a private beta program.
Currently, fragmented workflows for data analysts building machine learning models involve many manual steps to join several disparate tools. Data preparation and feature engineering are particularly difficult because of the iterative experimentation involved in the machine learning process. These issues create challenges when accessing and combining data sources and discourage collaboration and reporting on machine learning insights. With businesses of all sizes making substantial investments in machine learning to address their most complex data problems, these issues are widespread and pervasive.
To address these issues, Periscope Data’s new functionality with Amazon SageMaker will allow data analysts to tackle machine learning problems in one seamless workflow, from data prep to model training to reporting.
First, Periscope Data simplifies the data prep, by surfacing distribution and descriptive statistics, helping users recognize where more data cleaning or normalization is required. Data teams can also rapidly iterate on feature selection and develop complex feature engineering transformations by leveraging SQL in views for dataset development within Periscope Data. Next, the datasets are directly and effortlessly exported into Amazon SageMaker to build, train and deploy machine learning models at scale. Model results are then written back to a data warehouse, allowing users to leverage trained models for predictive and prescriptive reporting in Periscope Data to inform business and product decisions.
Amazon SageMaker, is a fully-managed service that disruptive companies worldwide are using to empower developers with easier ways to leverage machine learning. The tool allows developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.
To showcase the new solution, Amazon SageMaker and Periscope Data will be hosting a joint event on Wednesday, July 18, directly following Amazon’s AWS Summit in New York City. This half-day training session will include an overview of the functionality available in the beta program and interactive walkthroughs of Amazon SageMaker to provide additional context on its capabilities for completing the machine learning lifecycle.
Hypergrowth startup Rover is among the first to join the program and will be showcasing their enhanced machine-learning workflow at an event following next week’s AWS Summit in New York.
The Periscope Data integration with Amazon SageMaker will be made available publicly in the coming months. For more information about joining the beta program, or to attend July 18th event, please visit https://www.periscopedata.com/ or contact your Periscope Data representative for more details.