Security and finance teams are running data lake projects to advance their data analytics capabilities. Their goal is to extract meaningful, timely insights from data. Here are three steps to avoid that happening: Clean up messy analysis workflows from the get-go. Set expectations with budget holders and executives about how important this is and the time it will take. Plan to scale from the start to the long-term success from the data lake project, says John Defterios. The biggest lead time is “understanding the data,” he says.”]