Data mishaps to watch for in operational analytics | Census

Operationalizing data can be a game-changer for businesses, but it's not without its challenges. One common roadblock is API quotas, which can be easily overwhelmed if not carefully managed. Another issue is pushing too much data into applications, which can lead to problems like duplicate emails and application slowdowns. When multiple writers are involved, data can become inaccurate and duplicated due to overlapping updates. To avoid these mishaps, it's essential to develop a hub-and-spoke model for data syncing, align with departments closely, and understand the API limitations of each application. By taking these precautions, businesses can ensure accurate and up-to-date data while avoiding costly mistakes.