Big data projects are never simple and straightforward, and neither is building an in-house big data capability. In a new field with so few established experts, who should you look for to join your team? How can life sciences companies lure these people away from big, glossy technology companies in dynamic tech hubs like Silicon Valley? And since there’s so much groundbreaking yet to be done in big data, particularly in life sciences, what should you look for in a good professional services partnership? Moreover, since the tech landscape changes so dramatically—and so quickly—how do you keep pace? How do you avoid analysis paralysis and get started? ZS Principal Sandeep Varma and Associate Principal Vickye Jain have spent a lot of time answering these questions for life sciences companies, including in their work on a revolutionary, enterprise-scale data lake at Amgen. We recently caught up with them to help us see beyond the hype and understand what really goes into building a successful big data project, and to learn what they’ve observed from life sciences companies that have developed their own in-house big data capabilities.