Remove 2012 Remove Data Transformation Remove Testing
article thumbnail

Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. This approach simplifies your data journey and helps you meet your security requirements. Choose the created IAM role.

article thumbnail

Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. This solution includes a Lambda function that continuously updates the Amazon Location tracker with simulated location data from fictitious journeys.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Use Snowflake with Amazon MWAA to orchestrate data pipelines

AWS Big Data

If you’re testing on a different Amazon MWAA version, update the requirements file accordingly. For testing purposes, you can choose Add permissions and add the managed AmazonS3FullAccess policy to the user instead of providing restricted access. The requirements file is based on Amazon MWAA version 2.6.3.

article thumbnail

Bringing MMM to 21st Century with Machine Learning and Automation?

DataRobot Blog

Before the data is put into the model comes a process called feature engineering – transforming the original data columns to impose certain business assumptions or simply increase model accuracy. Originating in game theory, there is a reason why Shapley Value earned Lloyd Shapley a Nobel Prize in 2012.