DataOps: an Agile Methodology for Data-Driven Organizations
Learn how companies using a DataOps approach are putting data science projects into production faster.
DataOps is an agile methodology for developing and deploying data-intensive applications, including data science and machine learning models. In this white paper, coauthored by DataScience.com partner MapR, find out how implementing a DataOps workflow can help your company achieve a faster time to value on data science projects and foster collaboration between data scientists and engineers.
27% of firms will invest more than $50 million in big data by the end of 2017
A DataOps workflow supports collaboration and fast time to value
Only 11% of companies can iterate on models currently in production
A DataOps process ensures IT is not a bottleneck to productivity