3 ways to apply agile to data science and dataops
Just about every organization is trying to become more data-driven, hoping to leverage data visualizations, analytics, and machine learning for competitive advantages. Providing actionable insights through analytics requires a strong dataops program for integrating data and a proactive data governance program to address data quality, privacy, policies, and security.
Delivering dataops, analytics, and governance is a significant scope that requires aligning stakeholders on priorities, implementing multiple technologies, and gathering people with diverse backgrounds and skills. Agile methodologies can form the working process to help multidisciplinary teams prioritize, plan, and successfully deliver incremental business value.