The ugly truth about making analytics actionable (sponsored by SAS)
Companies across industries are adopting data-driven mind-sets, strategies, and cultures. Yet the ugly truth is many still struggle to conquer the last mile—the critical point where analytics drives decisions at scale to create business value. After all, enabling better, faster decisions is how you drive innovation and future-proof your organization.
But only 50% of business’s best analytical models are put into production. And 90% take three months or more to deploy. There are many opportunities lost when half of an organization’s most promising models become shelfware. Think of the investment in people, processes, and technology that goes to waste. There has to be a better way. And there is. By taking a model ops approach, analytics and IT can drive efficient model development, deployment, governance, monitoring, and retraining at scale. This means analytics is continuously available to drive automated decisions.
Diana Shaw digs into how to make analytics actionable within your organization. You’ll see a simple, powerful, and automated solution to operationalize all types of analytics at scale and learn how to create a clear, defined path to put analytics into action while providing model governance and data scalability to drive real results.
This session is sponsored by SAS.
What you'll learn
- Learn how to use an automated solution to operationalize analytics at scale
Diana Shaw is a manager of the Americas artificial intelligence team at SAS. She’s an analytics expert and thought leader and heads a team of data scientists in creating practical, effective AI applications. She focuses on helping customers apply advanced analytics, machine learning, natural language processing, and forecasting to solve their most complex problems. Over the past 19 years, Diana honed her skills mining data, troubleshooting problems, and developing technical solutions, including streaming IoT solutions. Diana regularly leads discussions with executives, business analysts, and data scientists around the globe, consulting on analytics strategies and broader technology objectives. She has a bachelor’s in metallurgical engineering and an MBA and a master’s in analytics. Her experience spans steelmaking, banking, automotive manufacturing, bridge construction, and building controls. She’s passionate about getting more girls to code and pursue careers in STEM.
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