In the context of Big Data London and its focus on AI and ML, adopting innovative technologies requires mature data processes. Many European enterprises struggle to leverage data due to difficulties in reliably moving large volumes of data from various systems and transforming it for use. Automation, reliability, and scale are key elements of mature data-driven organizations. Without these traits, businesses risk missing out on opportunities and struggling to stay competitive. Automation unlocks the value of data and provides efficiency, freeing teams to focus on higher-value work. Reliable access to accurate, fresh data is crucial for business-critical applications, as seen in JetBlue's use of automated data movement to inform revenue forecasting and maintenance decisions. Democratizing access to data enables innovation at every corner, as exemplified by Engel & Völkers' centralized data landscape and self-service analytics. Ultimately, businesses must assess their readiness to harness the power of data-driven decision-making.