In-Memory Computing Best Practices for Real-Time Analytics, HTAP, and Automation
This in-memory computing best practices webinar explains how companies add in-process Hybrid Transactional/Analytical Processing (HTAP) architectures for real-time data access, analytics, and decision automation to their existing applications and analytics systems.
In this webinar, you will learn:
- What common types of projects benefit from in-process HTAP, and how to plan ahead so that these projects succeed in implementing HTAP.
- A good reference architecture for in-process HTAP that supports both existing and new applications and analytics.
- What technologies are needed for in-process HTAP, including machine and deep learning.
- The best practices for how to, and when to, implement real-time data integration, management, and governance for analytics and data science.
Over the last decade, it has become impossible to support the currents needs for real-time analytics and automation with traditional ETL, data warehousing, and other business intelligence technologies. Data needs to be up to date and accessible in real-time, and analytics and automation now increasingly need to run within a transaction or interaction to achieve their goal. Real-time analytics, HTAP, and automation help companies make better business decisions and improve the customer experience.
Join GridGain’s VP of Outbound Product Management Rob Meyer for this webinar on August 21st at 10:00am PDT/1:00pm EDT to learn more about in-memory computing best practices for real-time analytics, HTAP, and automation.