We are excited to launch DataSQRL with the mission to help developers and organizations build with data.
Collectively, we have spent decades building or helping others build data products. We have seen many struggles, failures, and piles of money being thrown out the window and figured that there must be a better way. We started DataSQRL to find it.
We believe that the technologies used to build data products are too complex and that the engineering processes used to build them are broken. Here is how we plan to fix these issues.
We developed DataSQRL which compiles a developer-friendly version of SQL into a fully integrated and optimized data pipeline and API server. It takes care of all the laborious plumbing, data massaging, and stitching together of technologies that makes building data products so harrowing. Check out this short tutorial to see how it works - it only takes a few minutes to build an end-to-end data product.
In addition, we are refining a value-focused process for implementing data products that we have developed over the years while working with development teams and organizations. The basic idea is to apply the same software engineering principles that have proven to be successful to implementing data products. That means you don't need a dedicated team of specialists to implement data products and can keep your customers and stakeholders in the feedback loop. Click here to learn more about our process.
That's our starting point for enabling developers to build successful data products quickly and efficiently. We think we got some good ideas, but have been building data technologies long enough to realize that there is a fine line between innovation and wishful thinking.
We hope that you will join the DataSQRL community to share your experience, insights, and opinions to help set us straight.
If you are trying to enable your organization to turn data into valuable data products, consider working with us and get in touch.
We are excited to be on this journey and hope you will join us. Let's build with data together.