BLOG

Introducing the RAW Data Product Platform

December 6, 2021
   
Solution / Strategy
Posted by Jeremy Posner

We’re about to launch our Data Product Platform after listening to our customers and many data practitioners around the world — people who develop and use data products were telling us a few consistent messages:

The data space is getting much more complex.

There are more environments and tools than ever — so keeping up is a struggle even if you have people who would be considered as ‘Data Engineers’. Many smaller, growing companies don’t.

A shortage of trained people who can deal with all this complexity.

Companies who have ‘Data Engineer’ and similar roles report they are overwhelmed, often because they are spending too much time on non “business goal” oriented tasks such as infrastructure. Many companies don’t have the staff, but their users still require data. Either way there’s a massive skills shortage.

Users are getting more demanding

They want more data, faster turnaround times, and in a variety of consumption formats. They want trusted data, and therefore…

Managing data as a product is the goal

but the existing tools are not up to the job, and there’s no end-to-end simple solution.

So our team at RAW Labs have developed a unique technology platform to provide Data Products as a Service: A collaborative DataOps platform as a service for data APIs.

The platform enables you to do much more, with less effort, as we take away complexity, manage infrastructure and allow data to be read from many sources and output in many formats for your users’ needs. The platform fits into existing ecosystems of tooling, adopting a DataOps and data-as-code approach.

Interested? sign up for early access to our beta program and whilst you’re there, win a Swiss Army Knife for your efforts!

Watch Georges Lagardère explain how to use it — with a simple example video using Olympic games data:

End to End Walkthrough of the RAW Data Product Platform

And, for those interested in how it works, keep reading….


RAW Data Product Platform

RAW Data Product Platform — see below for descriptions related to numbers above

1. Low-code data query

RAW uses a dialect of standard SQL with simple functional language constructs to enable data access, query and manipulation inside a single powerful and easy-to-use tool. Query nested files (JSON, XML, etc.) or log files using the same simple constructs as tables, columns and flat files such as CSV. Web APIs are also directly accessible so that glue-code is not required.

2. Configuration driven APIs

APIs are created by a simple YAML file, where the API’s definition, metadata, security, and compute class are specified. The compute class can be set per API endpoint, allowing certain APIs needing more resources to use a large cluster. RAW supports multiple resource groups.

3. DataOps environment

RAW harnesses the power of your collaborative software code management environment (e.g. Git) so that data delivery can use the same tools as software delivery, using both DataOps and Data as Code approaches means that iterations are much faster and produce better quality outputs, and everything is tracked and versioned accordingly. RAW syncs with Git automatically so that APIs are immediately available including branches for testing purposes.

4. Platform-as-a-Service

The RAW platform is fully serverless and runs inside Cloud-based environments where multiple resource groups are made available for queries. Single and Multiple tenant options are available including the option to host inside an Enterprise’s Cloud account. The queries are fully isolated from each other using containers, and all data can be encrypted both in-motion and at-rest.

5. RAW Data Engine

The RAW engine is the result of years of research and enables scale-out query execution for distributed, heterogenous data and complex data types. Based on unique monoid comprehension calculus, the engine is built with state-of-the-art ‘JIT’ code generation techniques. This creates high-performance code which also uses a smart caching algorithm with multiple types of cache employed.

6. Administration UI and API Catalog

A UI to administer and view the catalog of APIs, connect to Git repositories, as well as review activity performance, spend, monitor logs and maintain users and RAW roles. APIs can be exported via OpenAPI and integrated with API management tools and catalogs.

7. Enterprise security integration

RAW integrates with Enterprise security systems via standards-based OAuth (Auth0) mechanism, supporting security policies and scopes for controlling data and API entitlements. API Access is fully monitored and can integrate with your API management platform.

Wrap Up

This is only just the start. There’s so much more to creating and managing data as a product. Over the next few years we plan to focus on enabling a simpler, easier and better experience to deliver data.

We will be starting beta testing in February 2022. For further information, sign up for early access to our beta program, and win a Swiss Army Knife for your efforts.

Jeremy Posner, VP Product & Solutions, RAW Labs.


Want to learn more?

Learn More

WHITE PAPERS

RAW Data Product Platform

Read more about our RAW Data Product Platform, including challenges it is designed to solve, and components of the solution

Blog

Data as a Product

Do we really manage our data as a product? What does that mean for customers? Is a data product really that different from a traditional product? And what can we learn from other more established industries about their products, and apply them back to our fledgling data product space?

News

RAW Labs' Co-founder Prof. Ailamaki Receives Argo Innovation Award

RAW Labs’ Co-founder and Chief Scientific Officer Professor Anastasia Ailamaki received an Innovation award for excellence from the Greek President Katerina Sakellaropoulou. The Argo Awards, which honour distinguished figures from...

PRESENTATIONS

Data Products Survey 2021

RAW Labs conducted a survey of data product practitioners in early 2021. We collected opinions on the state of maturity and inhibitors around data product delivery for our own product research and to share back with the community. We hope...