GoodData: Exiting stealth mode

It takes 10 years to become an overnight success.

Exiting stealth mode

We started GoodData with the vision of data and analytics in the cloud. This was 10 years ago. But at that point, enterprise data wasn’t commonly available in the cloud — and that could have been easily the end of this story. Instead, we focused our business on white-labeled OEM analytics (helping other companies provide self-service insights to their customers). OEM analytics was an excellent initial focus for many reasons:

• Most companies needed to communicate data to their customers or partners.
• The analyzed data was already leaving the companies’ four walls.
• There was a greater willingness to use a cloud-based solution.

Even with early cloud infrastructure, the advantages of cloud elasticity, performance, and global presence were better suited to solve the customer-facing analytics problem at scale. The other alternative was an in-house solution — which we were replacing for our customers.

Our unique advantage

The GoodData platform was designed to be optimized for customer-facing, OEM solutions. In reference to the Model T, Henry Ford once remarked, “You can have it in any color you want, as long as it is black.” GoodData was once the same — we could run on any cloud or cloud database, as long as it was Rackspace and Vertica.

But at the time, only Rackspace and Vertica were able to meet the extreme demands of our analytics solutions: providing analytics to over 1,000,000 users at 150,000 companies, using 20,000 CPUs, 200TB of RAM, and 5 petabytes of SSDs.

However, in finding a way to solve these requirements, we were given unique access to the problems of global leaders in high-tech, payments, travel and hospitality, healthcare, retail, and other verticals. For 10 years, we learned every day from our clients.

The GoodData team generated a vast amount of IP (most of it patented); developed and operated a global data platform at an enormous scale; and helped bring data to the cloud. Ultimately, we supported our customers with the delivery of massive analytics operations with a focus on monetization or commercialization of data.

When considering our path forward over the coming years, we have so much to build on — fantastic use cases, various scales of distribution, and huge value that had already been generated for our customers. With our analytics powering over 140,000 businesses across the globe, we have seen it all. Our 10 years were well worth the wait; we wouldn’t trade it for the world. But we are now ready for the next chapter of the GoodData evolution.

Why now?

The market is ready for what we started. Data is moving to the cloud at accelerating speed, and enterprises are now comfortable integrating and storing datasets in the cloud with services like Snowflake and Redshift.

Technologies that enable our scale, performance, and operational excellence are maturing very quickly. Cloud-native infrastructure is growing into normalcy with Kubernetes, Docker, Helm, Terraform — none of which existed 10 years ago.

As the global economy advances, the need for self-service analytics is growing across the board — and access to accurate, real-time, and well-governed data separates the winners from the laggards. Simultaneously, the existing on-prem data infrastructure is absolutely unprepared to support the increased requirements for insights, and trust in data has thus remained low. And with the increased focus on data privacy and regulations, the gap between data capabilities and requirements is not getting smaller.

It’s a nexus of forces. The shifts we see today have created the perfect storm, and we’re launching a new platform in the middle of it. We’re confident that this will change the industry as we know it.

What next?

On April 15th, we are launching GoodData into the next phase of analytics.

Our next step will surface a completely new category that will better support the needs of today’s enterprise than the world of batch-oriented and ungoverned monolithic BI tools.

We call this category Data as a Service (DaaS). And our vision has not changed from day one: data and analytics in the cloud — we’ve traversed this path from the start. Leveraging all that we’ve experienced and learned, we’re on to something bigger than business intelligence. With data as a service, we will enable companies to make every decision data-driven.

Data as a Service is the future of analytics: real-time, governed, secure, and scalable. Within the context of DaaS, we are opening our platform and making our experience with large scale analytics, data privacy, security, and operational excellence available for anyone to leverage to build and scale any of their data use cases; from self-service and embeddable analytics, to machine learning and IoT. Our unique advantage will be available to companies small and large — and on any cloud and cloud database.