5 Reasons Data Scientists Should Adopt DevOps Practices

Enterprise software development teams have historically had trouble ensuring the code that runs well on a developer's machine also runs well in production. DevOps has promoted more collaboration between developers and IT operations. Data scientists and data science teams face similar challenges, which DevOps concepts can help address. As the pace of business continues to accelerate, software and data science teams find themselves under pressure to deliver more business value in less time. Software publishers and enterprise development teams have attempted to address the issue with Agile development practices which are cross-functional in nature, although Agile practices do not guarantee that the code running on a developer's machine will work the same way in production.