This session will include a moderated Q&A featuring questions from the live audience.
Leveraging traditional analytics to address business problems is challenging, and the path to business value is often long. Successful efforts require time and resources from multiple disciplines during every stage of the analytics lifecycle. In particular, data cleansing and preparation can consume significant resources. High resource utilization and unclear time-to-value lead to increased risk.
Automation of the analytics process addresses these challenges to reduce risk and maximize value. Emerging systematic approaches address the identification of the most relevant inputs for the model, selection of the correct algorithms, and construction of the best models. These systematic approaches improve resource utilization and decrease time to value.
In this session, Deanne Larson will review DataOps and MLOps for analytics augmentation and show you how they can accelerate time to value.