Last week the Data 2030 Summit took place in Stockholm, a conference and networking event focusing on how to strategically work with data and AI to achieve innovation and deliver business value. The event covered three tracks: Data Strategy and Governance, Modern Data Platform and Data Architecture and Quality. 

In this second post on becoming data-driven, we’ll dive into three key elements of a modern data strategy; the data operating model, how your strategy can ensure you stay secure and compliant and, lastly, how to pick a technology stack and architecture to implement a data platform that will empower your organization and make you reach your business goals.

Right before a short and well deserved Easter break a few of us went to the GAIA conference in Gothenburg to listen to a bunch of presentations on AI. Beyond first impressions about how far the field and conference has come since the first session a few years back we took some notes and talked to new and old acquaintances around town.

To build on top of the AI and machine learning paradigm, you need to be in control of your own data. Succeeding with your data strategy transformation, becoming truly data-driven, will unlock new business and technical opportunities and allow your organization to end up on top of the next big shift.

In this blog post we’ll share what the most successful data transformations we’ve been involved in has in common and where the challenges reside.

Cloud computing is a key technology for us at Trice. About two decades old it continues to grow in importance for product and service delivery. At the same time a lot of organizations struggle with their cloud journey and, to be honest, there are still a lot of things we miss in terms of simplicity, developer experience, and guidance when working with cloud today.