Creating Optimized Thematic Portfolios with Bloomberg Enterprise Data
OVERVIEW
EXPERIENCE | In Person |
---|---|
TYPE | Breakout |
TRACK | Data Science and Machine Learning |
INDUSTRY | Financial Services |
TECHNOLOGIES | AI/Machine Learning, Apache Spark |
SKILL LEVEL | Intermediate |
DURATION | 40 min |
DOWNLOAD SESSION SLIDES |
Join this session to learn more about how portfolio managers can use market data and powerful analytics to create custom thematic investing tools on the Databricks Platform using Bloomberg data. We will walk the audience through the benefits of accessing and structuring data on the cloud, followed by a step-by-step tutorial on how to build their own thematic investing portfolio using Machine Learning and Visualizations powered by Databricks. In November, Bloomberg and Databricks announced a strategic collaboration allowing mutual customers to seamlessly access Bloomberg’s extensive data offerings via Data License and cloud-based data management solution Data License Plus (DL+). These solutions have been designed to facilitate seamless data integration, setting the stage for data analysis acceleration, insights generation and unified governance for structured and unstructured data, as well as artificial intelligence (AI) and machine learning (ML) on any cloud or platform.
SESSION SPEAKERS
Michael Beal
/Head of Data Science - North America
Bloomberg
Katherine Laue
/Cloud Integration Product Manager
Bloomberg L.P.