Data Collab Lab | Building Delta Lake with Images on Lakehouse

Let's kick off the new year with an episode of data collab lab with hosts Lee Blackwell and Franco Patano!

Details: Deep learning has come a long way over the past few years, with advances in cloud computing, frameworks, and open source tooling, working with images has gotten simpler over time. Delta Lake has been amazing at creating a tabular structured transactional layer on object storage, but what about images? Would you like to know how to gain a 45x improvement in your image processing pipeline? Join Jason and Rohit on data collab lab as we find out!

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Guests

Rohit Gopal is a Solutions Architect at Databricks, where he helps customers build data science, machine learning and data engineering applications. Previously, Rohit worked as a Data Scientist at IBM helping companies in CPG and retail industries leverage data to predict HR attrition, forecast demand, optimize manufacturing production schedules, and optimize trade promotions. He also has experience in healthcare analytics helping companies comply with federal sunshine act, detect anomalies, and customer segmentation.

Jason Robey is a Senior Solutions Architect at Databricks leading the Enterprise Platform SME group at Databricks. Jason has been leading and supporting technology teams for over 20 years in software development, artificial intelligence, and data analysis for telecommunications, retail, defense, healthcare, and manufacturing organizations.

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Hosts

Lee Blackwell is a Solutions Architect at Databricks where she enables other Engineers, Analysts, and Data Scientists to build scalable and reliable data systems. She has focused her career around Data Engineering, having built production pipelines across many sectors including Finance, AdTech, Retail, and Healthcare. Lee studied Data Science in school and quickly recognized the need for high quality, curated data once she joined the workforce. She enjoys being able to bring her bubbly personality and over 10 years of deep yet diverse experience to the table.

Franco Patano is a Solutions Architect at Databricks, where he brings over 10 years of industry experience in data engineering and analytics. He has architected, managed, and analyzed data applications both big and small, with open source and proprietary software, utilizing SQL, Python, Scala, Java, and Apache Spark, as well as experimenting with data science. Prior to Databricks, Franco worked as a Data Architect and Analyst in the Commercial Real Estate, Banking, and Education industries for organizations large and small.