In this article for AiThority, GRAX CEO Joe Gaska reveals how to turn artificial intelligence (AI) and machine learning (ML) from a disappointment to a success story.
Cloud applications like Salesforce represent the frontlines of cause-and-effect patterns of change sweeping across your business. Their data represents ideal ML/AI training sets — but often goes untapped. Joe explains why organizations who understand the value of their cloud app data will begin to obsessively preserve, ingest and mine its historical changes for competitive advantage.
- Historical SaaS application data is the missing ingredient standing between theory and practice, both in analytics and AI/ML.
- The more historical change data you feed into AI and ML, the better they get at predicting outcomes and the closer they get to delivering on their original promise.
- With the SaaS application backup tools on the market today, you could easily capture every single data change across every one of your cloud applications, feed them into your algorithms and correlate them all against each other, enhancing your AI/ML outcomes.
Read more in this AiThority article, “Historical SaaS App Data as the Ultimate Training Set for AI/ML.”
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