How to Orchestrate Data Workflows with the BMC Helix Control-M Python Client

Data science and engineering teams use many tools today and spend a lot of time wrangling data and managing data pipelines. In fact, data scientists spend more of their time on data preparation (22%) than any other task, plus another 17% on data cleansing according to the Anaconda State of DataOps report.1After these front-end activities are completed and data teams finally get to develop, deployment takes up another 11% of their time. That adds up to data scientists and engineers spending half their time on data and development pipeline activities. Imagine what these teams could do if they could focus on delivering data-driven insights one hundred percent of their time.

Now enterprises that use BMC Helix Control-M for application and data workflow orchestration can use Python as the bridge to faster workflow promotion, smoother execution in production, and for enabling data development scalability. BMC’s new Helix Control-M Python client enables data engineers and developers to easily build automated execution into their workflows as they develop them with Python and their other preferred development tools and environments.

Python has clearly emerged as the favorite development language – according to Anaconda’s State of Data Science report, 34% of respondents said they always used Python.2 Plus, 63% say they always or frequently use Python, which compares to 27% for R (which ranked second).

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