Organizations around the world, both small and large, are embarking on the journey to realize the benefits of Open Data Science. To succeed, they need to establish the right team, use the right technology to achieve their goals, and reduce migration risks. For most organizations, this journey removes barriers between departments as teams start to actively engage across the company and shift from incremental change to bold market moves.
The journey to Open Data Science is being forged with new practices that accelerate the time to value for organizations. In the past, much of the analysis has resulted in reports that delivered insights but required a human in the loop to review and take action on those insights. Today organizations are looking to directly empower frontliners and embed intelligence into the devices and operational processes so that the action happens automatically and instantaneously rather than as an afterthought. Adopting an Open Data Science approach is different from merely adopting a technology, however.
Moving to any new technology has an impact on your team, IT infrastructure, development process, and workload. Because of this, proper planning is essential. The drivers for change are different in every organization, so the speed and approach to the transition will also vary.
Shifting to an Open Data Science paradigm requires changes. Successful projects begin with people, and Open Data Science is no different. ...