In a perfect world, data engineers, data analysts, and data scientists would work in a collaborative and frictionless environment towards the same goals, according to the same set of priorities. In reality, data analytics projects often fall short of their goals due to unclear expectations and insufficient communication.
Building collaboration between data and analytics teams is critical to boosting efficiency and value creation. This panel discussion from CDAO explores strategies for:
