The webinar will cover the following topics:
- Fundamental characteristics of big data
- Data science use cases for insights discovery
- The analytics maturity ladder
- How data lakes and integration of high-variety data deliver deeper insights discovery
- Value creation from data assets through data ops
- Micro data lakes – Lentiq data pools - and their benefits
- How data pools enable independent data teams
- How to balance independence with control
- How to move data science projects to production
- Lentiq Demo
Dr Kirk Borne is the Principal Data Scientist and an Executive Advisor at global technology and consulting firm Booz Allen Hamilton. In those roles, he provides mentoring, thought leadership, and consulting activities in data science, machine learning, and AI across a wide variety of disciplines.
Previously, he was Professor of Astrophysics and Computational Science at George Mason University for 12 years in the data science program. Prior to that, Kirk spent nearly 20 years supporting data systems activities for NASA space science programs. In 2016 he was elected Fellow of the International Astrostatistics Association for his lifelong contributions to big data research in astronomy. As a global speaker, he has given hundreds of invited talks worldwide, including invited conference keynote presentations at many dozens of data science and analytics events globally. He is an active contributor on social media, where he has been named consistently among the top worldwide influencers in big data and data science since 2013. He was recently identified as the #1 digital influencer worldwide for 2018-2019.
Cristina Grosu is a young but highly talented technical product manager. She has built Bigstep’s DataLab product and has been part of many consultancy groups visiting data lake customers. She is now leading product development at Lentiq, a Chicago-based company offering a multi-cloud, production-scale data lake as a service platform.
Register now and join Cristina Grosu & Dr Kirk Borne in this interactive webinar on April 16th, 15:00 GMT.
No previous technical background is necessary, but familiarity with analytics and data science will be helpful.