
All too often Data Science projects fail to deliver measurable impact on organization’s profit and loss statements. Even successful prototypes do not make it into production when essential success factors like identifying the right cases, establishing a product mindset or focusing on operationalization are ignored. Carsten and Holger share best practices compressed into 10 key aspects that ensure P&L impact for Data Science.