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Real-time data augmentation

👉 Learn how to use RAW to augment your data pipelines in real-time. 👈

  • Augmenting your pipelines with real-time information is key to many use cases. For instance, you may need to enrich datasets with publicly available data, build a service that reacts to information that is available externally or process your data using external data cleaning or transformation services.
  • The ability to augment data quickly and efficiently, and without rebuilding ELT/ETL pipelines can mean the difference between delivering results to your users quickly or losing an opportunity.
  • With RAW, you quickly build and deploy APIs - called Snapis - that directly deliver real-time data and integrate seamlessly with your existing data pipelines.

How does it work?

To augment your data pipelines with RAW, you start by building REST APIs. These REST APIs are developed using RAW's built-in language called Snapi. Snapi is a low-code scripting language that provides advanced querying and transformation capabilities over atabases, data lakes, files or web services. Once you've built the REST API in RAW that provides your desired real-time data, you then integrate this API with your existing data tools, whether ETL/ELT tools like DBT, MuleSoft, Denodo, or visualization tools like Tableau or others.

As a result, you do not have to build or modify existing data pipelines, which in turn means you get to deliver projects faster and with access to real-time data.

Other Benefits

Since the RAW platform hosts these APIs as a service, you do not have to worry about operations. You also get access to RAW's built-in monitoring tools, as well as RAW's built-in API catalog. As a result, you have a leaner and faster data integration platform with a secure, single access point of data with very little development and operational effort.

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