Empowering Your Data Science with Data Enrichment
Whether your organization wants to become more sophisticated in your data science efforts, or you’re just trying to figure out how to get started, using internal structured data alone for analysis is not enough. It is important to enrich your data.
Integrating new data, such as demographic, geographic, and other external data sources, with your existing data can improve data science outcomes. Vendors are now making it easier to obtain and utilize new, up-to-date, high-quality data sources via cloud-based data marketplaces, and there are steps enterprises can take to quickly realize the value of data enrichment.
In this thought-provoking roundtable discussion, Fern Halper, Ph.D., TDWI’s VP of research and senior director for advanced analytics, Pam Askar, Ph.D., Ironside’s director of advanced analytics, and Mike Ashmore, Precisely’s director of location intelligence products, discuss the value of data enrichment for data science and best practices for getting started.
Attendees will learn:
- Why starting with the business objective is important for the application of advanced analytics
- How location intelligence capabilities and data sets can enrich business data for machine learning
- How data science-as-a-service can help overcome adoption hurdles and assess data enrichment’s business impact