March 7, 2017 This webinar has passed. The recording is available On Demand.
TIME: 2 PM Eastern / 11 AM Pacific
PRICE: Free to all attendees
This webinar is sponsored by:
About the Webinar
Analysts in the line of business deal with a myriad of time-consuming data preparation and analytic challenges that often require IT or DBA intervention to deliver a requested dataset. Others have taught themselves “enough SQL to be dangerous”, learning the necessary code to extract the data needed to answer their business question. Self-service data analytics empowers these business analysts to take control of the entire analytics process, delivering the necessary results for better business decisions.
Join us to learn how self-service data analytics allows analysts to:
- Utilize a drag-and-drop workflow for data and analytic processes without writing code
- Minimize data movement and ensure data integrity through in-database capabilities
- Easily work across relational and non-relational databases to deliver faster business results
Self-service data analytics delivers a repeatable process that is transparent to not only business analysts, but also SQL coders and decision makers across the organization.
About the Speakers
Sr. Product Marketing Manager, Alteryx
Beth Narrish is a Senior Product Marketing Manager for Alteryx. She has over 10 years of experience in finance, market research, and analytics software, with roles in product marketing, channel marketing, and solutions marketing. A strong communicator with excellent inter-personal skills, Beth exhibits a high-energy, can-do attitude with the unique ability to manage cross-functional teams, drive collaboration and deliver on a unified vision.
Solutions Architect, Alteryx
Dan Hilton provides solutions and service focused on analytics, big data processing, predictive modeling, and server integrations. He has delivered analytic projects across many industries including real estate, health care, retail, marketing, and financial services. His current role as Solutions Architect focuses on server implementations, application architecture, and data governance.