4 Areas of Focus to Become a Data-Driven Enterprise

February 15, 2019
Roman Stanek's picture
Founder & CEO
Roman Stanek is a passionate entrepreneur and industry thought leader with over 20 years of high-tech experience. His latest venture, GoodData, was founded in 2007 with the mission to disrupt the business intelligence space and monetize big data. Prior to GoodData, Roman was Founder and CEO of NetBeans, the leading Java development environment (acquired by Sun Microsystems in 1999) and Systinet, a leading SOA governance platform (acquired by Mercury Interactive, later Hewlett Packard, in 2006).

This week, I am pleased to announce that GoodData is positioned in the 2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms. This is a big deal for GoodData, and we believe that this cements our position as a leading provider of powerful enterprise analytics for every user, everywhere.

Over the last couple of years, we’ve gone through a significant transformation, going from a Cloud BI provider focused on SMBs to an enterprise data and analytics platform company that delivers insights to over 50% of Fortune 500 companies. Our customers now include credit card companies, insurers and financial services companies, healthcare providers, large travel agencies, car manufacturers, retailers, and e-tailers. Our deployments collect and analyze hundreds of terabytes of data instantly to provide insights to action to hundreds of thousands of people, all with industry-leading performance, scalability, and SLAs.

But if there was one thing our global enterprise customers were looking for, it was validation from leading industry analysts that their choice to use the GoodData platform for global, mission-critical data deployments was the right one. This is why being positioned in the 2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms is so important to us.

But our vision is not limited to the current state of business intelligence. Here at GoodData, we absolutely believe in a focus on data-driven enterprises, on what Accenture calls Data Industrialization: an ideal state where enterprise leaders tap the best available data at any time for actionable insights and optimized decisions.

And for GoodData, a focus on data-driven enterprises means four things:

1. Access

Access to actionable insights is not limited to a few analysts or data scientists. Insights need to be embedded in every layer of the organization and in every decision. This is the most difficult problem that at-scale analytics needs to solve: bridging the “last mile,” or delivering the right insights to the right people at the right time in a way that informs their decision making to drive business outcomes.

2. Trust

Data and insights are trusted by people who will make critical decisions based on them. This aspect of “data industrialization” goes beyond a simple product. It requires the coordination of people, processes, and technology to enable an organization to leverage their data as an enterprise asset with strong governance and transparency.

3. Support for change

Data and analytics infrastructure supports constant business change. Data-driven enterprises need to manage all the stages of their data and analytics infrastructure—from the original concept through to implementation and testing. Data sources and data models, algorithms, analytic processes, and UI need to be maintained for the life of the system. Most business intelligence projects fail because they get disconnected from the underlying business reality, and this is why our support for analytics life cycle management is so important.

4. Product

Data is treated like every other product. Product quality, usage levels, SLAs, and everything else needs to be measured and maintained. A data-driven enterprise’s commitment to its data production quality requires DevOps processes that allow for rapid iteration to deploy, secure, optimize, scale, and redeploy new datasets and methods to best support the business.

I believe that Gartner’s positioning of GoodData reflects our focus on data-driven enterprises. Not surprising, we share a similar vision that analytics will become increasingly embedded into all business processes, accessible on all devices, and built into all applications. The goal is for analytics to be pervasive but less visible to users. It’s the responsibility of the machine to deliver predictive analytics to the user.  

And this is what GoodData is built to deliver. But we are not standing still. Next week, we will launch our developer community portal. We also release updates to the GoodData platform every week, and the number of industry partnerships continues to grow. This is just the beginning—we can’t wait to show you what’s next.

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