This webinar discusses data science and how it is driving new approaches and solutions to business analytics.
Financial institutions are under pressure to maximize the insight they can derive from their data. With data spread across multiple silos and stored in structured and unstructured formats, embedding analytics into business processes can be difficult and calls for new approaches to data management.
Open-source database and data processing technologies and machine learning techniques, including Natural Language Processing (NLP), provide new approaches to advanced analytics. Metadata management, knowledge graphs, data discovery, quality metrics, and data visualization tools are also useful for adding context to data and providing insight. However, winning buy-in and business ownership for new tools is an ongoing challenge.
Managing data privacy, content license restrictions, and security is a critical concern when using data for analytics and must be addressed in the early stages of any analytics project.
Watch this webinar to find out:
- How data science is developing
- How to incorporate additional data sources into workflows
- The role of the data scientist in analytics
- How to gain insight from data and more closely integrate quality data with analytics
- Necessary tools and technologies
- How to manage data privacy and security
- The business benefits of data science and analytics
The Panel
- Stef Nielen, Director of Strategic Business Development, Alveo
- Arijit Bhattacharya, Executive Director, Analytics, UBS
- James Corcoran, CTO Enterprise Solutions, Kx Systems
- Moderator: Sarah Underwood, Editor, A-Team Group
