Data enrichment and machine learning: Maximizing the value of your data insights
Data enrichment and machine learning are two techniques that can enhance the ability of your customer data to drive personalized experiences. While there is some overlap in the end goal of both approaches to enhancing data value, there are significant differences in the time, resources, and overhead they each require.
How to harness the power of a CDP for machine learning: Part 3
Learn how you can activate machine learning insights across analytics and customer engagement platforms in part three of this three-part series.
Meet your marketing goals with customer data
Your marketing campaigns will only be as effective as the customer data that you use to power them, especially if leveraging AI/ML. Check out these tips and tricks to get your customer data in the best shape possible and begin accelerating your marketing strategy.
Generate in-warehouse predictive audiences
Learn how Jayant Subramanian, data science intern, developed a proof-of-concept machine learning pipeline for predicting user behaviors from data pre-processing to model training and beyond using Snowflake and Apache Airflow.
Money20/20: Innovation, AI, and data management
A recap of the need-to-know themes from Money20/20’s annual gathering of FinTech experts.
Improve products with AI and Machine Learning
Traditional digital marketing can’t keep up with machine learning and AI marketing solutions. Learn exactly how these powerful point-and-click tools work and how they can help your team experiment at scale.
Hyperloglog Algorithm: A must-know for data scientists
Hyperloglog (HLL), a powerful streaming algorithm, helps mParticle deliver real-time analytics products. Learn why it's a must-know for data scientists.