Innovation in Analytics Requires Iteration. And Iteration is Hard
Do your business customers roll their eyes when you tell them the delivery date? Have you had embarrassing production errors? Your team begging to try new approaches? We've been there.
Our view is that Chief Data Officers (CDO/CAOs) and analytic team leaders struggle to keep up with customer requests and let errors slip into production. The solution to that struggle is to innovate with DataOps.
DataKitchen's DataOps software platform delivers previously unavailable business insights by enabling the development and deployment of innovative and iterative data analytic pipelines. Rapidly.
DataOps Runs the Assembly Line from Data to Customer Value. Data Analytic processes are like manufacturing: materials (data), steps (your analytic tools and code) and production outputs (refined data, charts, graphs, model)
DataOps Speeds Ideas to Production. Analytics is Code: continually move from development environments to production
We believe that it is not about how good your tools are or how smart your team is or even how good your data is ... Innovation and quality come from being able to rapidly respond to customer feedback rapidly. That's it.
DataKitchen provides the world's first DataOps platform for data-driven enterprises. DataKitchen enables data analytics that can be quickly adapted to meet evolving requirements while using the tools they already own. Our platform:
When a pharmaceutical company wins FDA approval, they enter a critical time. Celgene's analytic team's internal customers need up-to-date information to allocate samples, plan marketing events, and of course, monitor progress vs. goals. Changes happen at a frenetic pace and the tolerance for error is very low. The DataKitchen DataOps platform plays a key role in delivering insight fast, with high quality using a diverse set of tools. DataKitchen Recipes run daily incorporating the newest sales data from Veeva, corporate MDM data, and multiple syndicated data sources into a large Redshift database. Crack analysts use Tableau and Alteryx to present dashboards and develop predictive models. Read the Case Study and Blog Post
When one of the largest international relief organizations wants to understand their donors and increase the funds able to help 130 million people in more than 90 countries and territories, they know that the traditional slow and fragmented analytic process does not meet their needs. The analytic team needs an integrated database updated daily, the ability to make changes to that database weekly, and the confidence to use Tableau to make changes real-time. They need DataKitchen's DataOps platform to provide the mechanism to make quick changes, keep quality high, and use the tools they love.
Learn More About DataKitchen's Leadership in DataOps from leading thinkers.