Description: Mindful data visualizations show the end users the end way in how to analyze and interpret your data. More importantly, they can then use this data they see to drive decisions and modeling going forward.

Description: Neural Networks are no longer limited to classification and regression solutions to numeric problems. CNNs add the ability to classify images, and GANs can create new images. Learn how these capabilities can provide competitive advantages to early adopters, how they work, and how to implement them.

Description: The barrier between humans and machines continues to blur, but curiously, this may have been prediction thousands of years ago in ancient myths. This article looks to how some of the early legends are becoming manifest in modern technology, particularly in the area of elder care. From automation, to humanoid assistants, to mind clones will the age of technology bring a new utopia?

Description: CMS provides ACOs with monthly claims data for members, including their medical visits and ACO program eligibility. This data can be divided into Membership and Claims tables through the ETL process. However, when calculating PMPY at specific levels of detail using these tables, issues arise due to unrelated dimensions, leading to inaccurate and understated results. This article presents a solution to this problem by utilizing Tableau's data blending capabilities.

Description: Principal component analysis is an unsupervised linear transformation mainly used for dimension reduction. Determine key numerical variables with maximum variances in a dataset, identify the correlation and removal of redundant variables are the key aspects of this exploratory data analysis.

Description: The actuarial profession is at a tipping point and a combination of disruptive technologies and external pressures are creating a unique opportunity to move from results producer to insightful adviser. For a prudent but forward-looking professional, this is exciting and scary in equal measure. The ability to process large masses of business data to make more accurate calculations has become one of the most sought-after skills for leaders across all industries, including insurance.<br><br>The presenters will introduce current data technologies used to manage, process and visualize data. They will cover solutions like Microsoft BI, Tableau, Amazon Redshift, Hadoop, Alteryx, Python, etc. and their applications in data, process improvement, automation, reporting and predictive analytics. In particular, they will explore management reporting and how it leverages data analytics to help business leaders with strategic decisions making, how to evaluate the effectiveness of management reporting structures, drivers of change and ways to improve them, and proposed steps toward entrenching this dynamic and insightful approach to management reporting in which insurance leaders can have confidence.