From TechTarget: Our CEO, Ryohei Fujimaki, Ph.D., comments on how automation will maximize their current data science team. Read the full article at 5 Ways Enterprises Adapt to the Data Scientist Shortage.
Because of the shortage of data scientists, organizations are taking different approaches to hire, train, and retain data professionals. Data scientists typically do operational tasks to improve data quality, but this is changing. Automation can significantly simplify model development and operationalization and help companies maximize their AI and ML investments. Just-in-time data engineering is a promising development in data science automation that data science teams can automate. The data scientists shortage is being dealt with by adding data management, modeling automation, and democratizing data resources via self-service analytics.
To get more out of their limited data experts, companies are exploring new team strategies. Many companies respond to the scarcity of data scientists by hiring external consultants or creating cross-functional data science teams. Cross-functional teams can help solve data silos and help companies manage the data science projects that currently look unmanageable. Read more about this at TechTarget
