Analytics encompasses many skills and disciplines. Identifying the problem, choosing the modeling approach, selecting the correct features to model, and evaluating the result are at the heart of analytics. The tendency, however, is to focus primarily on the technology rather than the process. Join us for a problem-focused, applied experience where you learn to apply the analytics process to produce meaningful and valuable insights.

Why is content personalization important? OTT (Over the Top) platforms are transforming the global entertainment scene. The critical players, like Hulu, Netflix, and Disney, are competing in terms of viewership and revenues. With the increasing overlap of content across all these platforms, it is crucial for these services to improve the consumer experience by delivering relevant and engaging content to prevent audience churn. Content personalization is, therefore, vital to acquire more viewing time and improve market share.

There is only one answer and that is asset performance visibility.Management thinker Peter Drucker once said, "you can't manage what you can't measure." You can't improve reliability or performance unless you have complete visibility with respect to asset performance. In the past, industry professionals spoke about asset visibility more in terms of tracking the physical location of critical assets. But in the digital age, it is possible to monitor location, status, and performance in real time.The business benefits of the asset visibility program are not limited to productivity and safety; they are more about reliability and profitability. The benefits could be as high as a 7% improvement in return on assets (ROA) and 11 % improvement in overall equipment effectiveness (OEE).

The manufacturing industry is overwhelmed with the advent of machines, technology, and the internet. The fourth industrial revolution is set to make manufacturing more digital, and only intelligent machines can make this happen. With the rise of machines, robotics, more automation, agile manufacturing, and increasing customization, manufacturing operations have become very complex. This demands better performance and reliability, especially for asset-heavy industries, where the reliability of industrial assets is mission-critical. At the same time, industry is experiencing revenue and profitability challenges that call for enhanced operational reliability and lower maintenance costs.

This Domino Data Science Field Note provides highlights and video clips from Addhyan Pandey's Domino Data Pop-Up talk, "Leveraging Data Science in the Automotive Industry". Highlights covered in this blog post include Pandey using word2vec to identify duplicate vehicles on the platform, how his data science team refers to predictive models as "data products", and the company's overall approach to data science. While this post covers highlights and video excerpts, the full video of his talk is available. If this type of content interests you, visit the Domino Data Science Pop-Up Playlist or consider attending Rev. Addhyan Pandey, Principal Data Scientist at Cars.com, explored how data science is implemented across the company and how data science is more than machine learning in his talk, "Leveraging Data Science in the Automotive Industry". Pandey launched his talk with discussing how Cars.com revenue streams include subscription and advertising models.