Session: Operationalizing AI at Scale
Artificial Intelligence (AI) drives competitive advantage and is a catalyst for transformation and is rapidly making an impact across every industry, every day. The path to MLOps and more effective ML development and deployment hinges on selecting the right people, processes, technologies, and operating models with a clear linkage to business issues and outcomes. To be effective, organizations must strike a balance between accelerating the use of AI and having the right AI infrastructure in place to operationalize and drive sustainable outcomes.
- Streamlined ML Ops lifecycle (ideation, procuring data, modelling, operationalize)
- Simplified technology landscape
- Removing bias in AI by having a diverse team to bring more value to the business
Sandra has over 20 years of project experience as an Analytics business leader and most recently led Big Data implementations in the financial sector. She is currently serving as a Partner at Deloitte helping clients switch to the Cloud and Modernize their Data Management for the Future. Her expertise include the analysis of business processes and definition of customer requirements of information Solutions, End-To-End from Analytics Strategy, Blueprinting & Design of the Solutions to Implementation and Support with Big Data and Advanced Analytics Solutions. She also serves as a mentor to a few women who would like to advance their career in the AI & Data field.