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Summary
In today's data-driven world, the ability to structure and enrich data has become crucial for organizations seeking to gain valuable insights, make informed decisions and drive innovation. Join us as we dive deep into the world of structuring data, enrichment techniques and applicable use cases.
Enriching data goes beyond organizing it; it involves enhancing data with additional information, context, and insights to unlock its true potential. We will explore different data enrichment techniques, such as entity linking, topic identification, text classification and sentiment analysis. Learn how to leverage these techniques to improve data quality, accuracy, and completeness.
Key Takeaways:
- Best practices for structuring and enriching data
- Real-world use cases and success stories
- A solid understanding of data structuring, enrichment techniques
- How to be equipped with the knowledge to supercharge your data
Whether you are a data analyst, data scientist, business intelligence professional, or simply interested in leveraging data for informed decision-making, this webinar will provide valuable insights to help you excel in your data journey. Join us and unlock the true potential of your data!
Moderator
Christian Arellano
Senior Sales Manager – Corporates
Christian Arellano is a dynamic and progressive business leader who puts his people first and creates winning team cultures. He currently leads a Corporates Sales team at S&P Global Market Intelligence selling into the largest technology and professional services firms in the world.
Speakers
S&P Global Market Intelligence
Kevin Zacharuk
Product Manager, Textual Data
Kevin Zacharuk is a Manager of Product Management within the Data, Valuation, Analytics (DVA) group at Market Intelligence. He oversees the management and development of text-based data feeds for machine readable use cases.
Zak Brown
Machine Learning Engineering Manager
Zak Brown, Phd is currently a Machine Learning Engineering Manager at Kensho Technologies, an innovation hub for S&P Global. His career has mainly focused on natural language processing, deep learning, and developing architectures for scaling compute-intensive workloads.
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