11:45 - 11:50: Virtual meeting opens
11:50 - 12:00: Welcome & Chapter announcements
12:00 - 1:00:  Presentation

Data Science Concepts Every Analyst Should Know!

Machine learning models are now everywhere. While business analysts don’t need to know the inner workings of statistical models to perform their job well, a good understanding of some foundational data science concepts can help you acquire a competitive advantage and deliver higher value to your organization by:

• Preventing leaders from making poor decisions based on dubious insights from flawed machine learning models.
• Facilitating buy-in for the implementation of well-performing predictive models that create business value.
• Identifying new opportunities to leverage machine learning to solve important business problems.

Learning Objectives:​

• Types of business problems that are likely to benefit from a machine learning approach.
• Common mistakes unprepared data science teams make and business analysts can help avoid.
• Where to find “bite-size” lessons to develop your competence level in the key data science concepts you need to master in order to understand and communicate effectively on:  a) choosing a sound machine learning strategy;  b) evaluating model performance; c) designing solid experiments.

Presenter

Born and raised in Brazil, since 2004 Adriana Beal has been working in the U.S. helping Fortune 100 companies, innovation companies, and startups gain business insight from their data, make better decisions, and build better software that solves the right problem. In 2016 she shifted her career from product management to data science and started designing machine learning models to improve operational and decision processes in IoT, mobility, healthcare, marketing, sales, human services. Adriana has been a speaker in multiple IIBA events in Austin and across the US, including the Conference Building Busines Capability (BBC 2019).