The IMD Wrap: Quality drivers—the sticks and carrots accelerating the data quality race

Like a Formula One Grand Prix, data management is a race that can be won or lost. And just as each race is part of a larger F1 championship that pays large sums of TV money to the winning team, winning or losing one race can contribute to winning or losing an endgame with much more at stake.

Anyone who watched this weekend’s Hungarian Formula One Grand Prix may have been shocked to see and hear some of the supposedly best race car drivers in the world whining over their team radios like petulant children. Max Verstappen, for example, admittedly an incredibly talented driver, managed to blame his strategists, his car, his long-suffering race engineer Gianpiero “GP” Lambiase, and other drivers—though notably not himself for staying up late the night before playing simulation racing

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Back to basics: Taxonomies, lineage still stifle data efforts

Voice of the CDO: While data professionals are increasingly showing their value when it comes to analytics and AI adoption, their main job is still—crucially—getting a strong data foundation in place. That starts with taxonomies and lineage.

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