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Amazon SageMaker Integration

Tackle machine learning in one seamless workflow from data prep and model training to reporting

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Machine Learning in Minutes

Easily explore relationships in raw data, rapidly iterate on feature selection and develop even the most complex feature engineering transformations. 

Directly and effortlessly export datasets to Amazon SageMaker to build, train and deploy machine learning models at scale. 

Write the model results back to the data warehouse to leverage trained models for predictive and prescriptive reporting in Periscope Data.

Periscope Data
Data Preparation
  • Data connection
  • Feature selection
  • Feature engineering
  • Data encoding
  • Data cleaning

Collaboration
  • Review and iterate
  • Standardization
  • Reporting
Amazon SageMaker
Experimentation
  • Set up and manage clusters
  • Scale & distribute ML algorithms
  • Build, train and test models

Deployment
  • Set up and manage inference clusters
  • Manage & auto scale inference APIs
  • Testing, versioning and monitoring

Data Prep Made Easy

Leverage the best-in-class tooling for data prep to quickly create great datasets for your model building.

Periscope Data proactively exposes best practices through visualizing the relationship between features, the distribution of the data and the important summary statistics required to make a great dataset for building machine learning models.

Data Access

Access and join the vast amount and types of data required for machine learning experimentation, creating features for models, automating feature generation, and more.

Connect directly to your databases to ensure your datasets and models always use accurate and up-to-date data.

Rapidly iterate and see the changes immediately reflected in your Amazon SageMaker’s Jupyter notebook.

“Answering more complex questions with predictive modeling and machine learning is a core part of our data strategy as we continue to grow. Periscope Data has been an ideal analytics platform for us to get insights on our data quickly, and we’re excited about digging in deeper with this integration to build out our machine learning efforts.”

Brandyn Lee
Senior Data Scientist at Rover