At Data Summit 2019, Matthew Deyette, chief customer officer, presented a keynote titled The Evolution of Big Data Analytics, Data Summit 2019.
Data availability for AI, regardless of what the goal is, is a critical problem, said Deyette.
The AI-driven economy needs data diversity, but what we have now is a state of chaos, he said. It is not that there is no order, but that the order is segmented in silos, and ETL processes are slow and difficult to scale.
“We are not going to get rid of silos and individual technologies,” said Deyette, since many of these silos have been built up over years, and users have preferences for tools and technologies, and the result is that less than half of data collected is used and 90% of data lakes are delayed or over-budget.
Access to data quality is the number-one roadblock for AI, said Deyette.
Gemini eliminates the barriers between data silos to feed AI/ML algorithms, and enables data availability across the enterprise data without legacy approaches, data platform lock-in or complex learning curves. This allows organizations to deliver AI to the far reaches of the enterprise.
There will always be a new silo, new ones will always be created, said Deyette, noting a new approach is needed that accepts this as a fact and allows users to extract information from all of them.
Marinelli and many other presenters are making their slide decks available on the Data Summit 2019 website at www.dbta.com/DataSummit/2019/Presentations.aspx.