AWS IoT Analytics adds schema inference support for Apache Parquet based data stores
AWS IoT Analytics is a fully managed service that makes it easy to collect, pre-process, enrich, store and analyze IoT data at scale to run sophisticated analytics on massive volumes of IoT data and gain insights into how IoT devices are operating without having to worry about the complexity typically required to build an analytics platform.
AWS IoT Analytics is a fully managed service that makes it easy to collect, pre-process, enrich, store and analyze IoT data at scale to run sophisticated analytics on massive volumes of IoT data and gain insights into how IoT devices are operating without having to worry about the complexity typically required to build an analytics platform.
We are excited to announce that AWS IoT Analytics now supports schema inference for data stored in Apache Parquet format. Previously, customers had to specify the schema for their data and this feature helps simplify the customers experience by automatically inferring schema from the stored data. Our customers can use this feature on the console to infer the column schema from a raw JSON, or a channel, or an existing Apache Parquet data store.
To learn more about how you can use schema inference for your data in Parquet format, please read our documentation here.
To get started with AWS IoT Analytics, use the Quick start feature from the AWS IoT Analytics console to create a channel, data store, pipeline and data set with a single click. You can send data from devices to AWS IoT Analytics using AWS IoT Core Rules. Visit the AWS IoT website and the AWS IoT Analytics website to learn more about AWS IoT services.