Over the last decade, a transformative shift from siloed data structures to centralized data organizations has taken place. The advent of big data prompted numerous organizations to reassess their data infrastructures and make significant investments in data management. As data production and consumption surged exponentially, the demand for data and analytics as a crucial business function skyrocketed across various industries. To extract value from data assets, central data teams and centres of excellence were established. The transition to centralized data organizations addressed critical challenges related to data discoverability, access, and storage. Further, centralized data and analytics teams facilitated seamless data integration across the organization, breaking down information silos and promoting cross-functional collaboration.
Fast forward a few years and despite these advantages, most organizations have struggled to extract value from data. According to a Gartner survey, only 44% of data and analytics leaders feel that their teams are effective in driving business value. The question persists: How can we make our teams more effective?
Most organizations focus on getting data outcomes but they do not spend sufficient time on how to get to it in the right way. In order to maximize value extraction from data, organizations must focus on building the right foundation. i.e. identifying processes that build presence and drive consistency, and consequently drive the desired outcomes.
