Watch this free webinar, featuring Splice Machine Chief Architect, Daniel Gómez-Ferro, to learn about Splice Machine's state-of-the-art distributed transactional processing model and how it enables speed and performance at petabyte scale.
Many companies in the corporate world have attempted to set up their first data lake. Maybe they bought a Hadoop distribution, and perhaps they spent significant time, money and effort connecting their CRM, HR, ERP and marketing systems to it. And now that these companies have well-crafted, centralized data repositories, in many cases…they just sit there.
But maybe data lakes fall into disuse because they’re not being looked at for what they are. Most companies see data lakes as auxiliary data warehouses. And, sure, you can use any number of query technologies against the data in your lake to gain business insights. But consider that data lakes can – and should – also serve as the foundation for operational, real-time corporate applications that embed AI and predictive analytics.
These two uses of data lakes — for (a) operational applications as well as for (b) insights and predictive analysis — aren’t mutually exclusive, either. With the right architecture, one can dovetail gracefully into the other. But what database technologies can query and analyze, build machine learning models, and power microservices and applications directly on the data lake?
Sign up today to watch this webinar, featuring GigaOm analyst Andrew Brust, and Splice Machine CEO and Co-Founder, Monte Zweben. The discussion explores how to leverage data lakes as the underpinning of application platforms, driving efficient operations, and predictive analytics that support real-time decisions.
In this 1-hour webinar, you will discover: