This course is designed to explain and demystify Big Data in non-technical terms. It bridges the gap between market buzz about Big Data and business realities. It documents real-world usage and ROI of Big Data, delineates successes and failures of Big Data, and the reasons for both. It characterizes what a data scientist is, and what s/he does all day. It discusses the pros and cons of various organizational structures for Big Data and Analytics teams. In short, the course peels away the complexities surrounding Big Data, boiling it down to the essence that managers need to know to make optimal decisions about the use, resourcing, risks, and value of Big Data. Sandra Hendren, the instructor, is an energetic and entertaining speaker. She is a 30-year veteran of data and analytics, immersed in the evolution from “small data” and “analyses and reporting” in the 80’s to “big data” and predictive analytics today. Her experience is 1) hands-on - she still writes code and develops predictive models and machine learning algorithms -2) functional management in charge of multiple data and analytic development teams, and 3) at the executive level - most recently as Chief Data and Analytics Strategist for UnitedHealth Group, the 12th largest company in the nation. This course is guaranteed to be different. It is an honest, technology-agnostic, vendor-neutral explanation of the rhetoric and the realities of Big Data. Ms. Hendren is sometimes blunt, often funny, and always clear. You're invited to learn a lot and enjoy yourself while doing so in this 4-hour course.
What am I going to get from this course?
- Understand what’s real and what’s not – the rhetoric and realities of Big Data
- Have a working knowledge of the business challenges and strategic rewards of Big Data initiatives
- Be conversant in real world case studies, both successful and unsuccessful ones, and the reasons for each
- Distinguish different organizational structures for Big Data and Analytics teams, and the pros and cons of each
- Understand the skills needed for professionals of a Big Data and Analytics team, including what is really important to look for in a Data Scientist
- Empower managers with the knowledge necessary to make optimal decisions about the use, resourcing, risks, and value of Big Data