Beginner's Guide to Data & Data Analytics, by SF Data School

Co-Founder of The San Francisco Data School, and Analytics Team Lead at Square. Previously, a Lead Instructor for Data Analytics at General Assembly San Francisco, and an Instructional Associate for Columbia University’s MS in Applied Analytics.

The world of data is incredibly massive. For anyone looking to start their journey in a data profession, it can quickly become an overwhelming endeavor. No one knows this better than Colby Schrauth.

Colby took a non-linear path to becoming a data professional. His educational background is Finance, but he’s spent the majority of his professional career in Business Development roles – selling payroll to small businesses for ADP, helping large enterprises understand the value of online communities with Lithium Technologies, and more. However, the goal of becoming a practitioner of data persisted throughout these experiences.

Along the path to becoming a data professional, Colby was constantly battling internal thoughts of discouragement:

• I don’t have a Computer Science background, will I ever be taken seriously?

• What data tools should I learn, and how do I get started?

• The data ecosystem is complicated and evolving quickly, will I be able to keep up?

The list goes on, and on. Here’s the good news, this real-world experience is what makes him the ideal teacher for those who wish to forge their own path in the world of data. Colby believes that anyone with patience and a deep desire to learn can develop a concrete understanding of data and how to work with it. He’s on an entrepreneurial mission to share the epiphany moments he’s had along the way, and create a linear learning path so that others don’t have to learn the hard way, like he did.