Use AI Via an End to End Data Lakehouse to Increase Data Lifecycle Efficiency From Ingeson to Predicon

Description: Enterprise organizations are on a transformational journey to improve time to value in their data engineering, analytics, and machine learning processes. An increase in the amount of structured and unstructured data, and the number of tools used to derive value from that has reduced productivity and profitability. Data decision makers and practitioners struggle to perform their core job functions while operating in environments that do not combine data management, analytics, data science functions and extract, transform, load ETL.