The session includes real-world case studies and success stories, showcasing organizations that have leveraged DataOps with Databricks to streamline their data pipelines, reduce time-to-insight, and enhance data quality. We will explore practical examples of version-controlled workflows, automated testing, and continuous integration/continuous delivery (CI/CD) pipelines, demonstrating how these practices contribute to a more efficient and reliable data ecosystem.
The pros and cons of each example is explored.Target audience is intermediate - expert technical, but there is opportunity for learning from beginners in the world of Databricks and Datalakes. This is industry independent.
Eric Nosal, Technology Principal Advanced Analytics at Arcurve - Eric has been working with big data, analytics, statistics, and machine learning/AI for over 20 years. With a BSc Hons. in Computer Science (concentration in Scientific Computing) and a BSc Hons. in Applied Mathematics, his focus has been on the marriage of technology, programming and advanced algorithms (AI/ML).
Eric has experience in the full software development life cycle using established and emergent technologies coupled with an in-depth knowledge of the inner workings of ML/AI algorithms. With this knowledge he excels in designing, architecting, and implementing leading edge enterprise level AI/ML software solutions both on cloud and on prem. Being a native Calgarian, Eric spends his free time with his family in the mountains - camping, fishing, hiking, biking, and skiing.