Sprint Toward Data-Driven Culture Using DataOps

Our Advice

Critical Insight

• Data and analytics teams need a clear mechanism to separate data exploratory work and repetitive data insights generation. Lack of such separation is the main cause of significant delays, inefficiencies, and frustration for data initiatives.
• Access to data and exploratory data analytics is critical. However, the organization must learn to share insights and reuse analytics.
• Once analytics finds wider use in the organization, they need to adopt a disciplined approach to ensure its quality and continuous integration in the production environment.

Impact and Result

• Use a metrics-driven approach and common framework across silos to enable the rapid development of data initiatives using Agile principles.
• Implement an approach that allows business, data, and operation teams to collaboratively work together to provide a better customer experience.
• Align DataOps to an overall data management and governance program that promotes collaboration, transparency, and empathy across teams, establishes the appropriate roles and responsibilities, and ensures alignment to a common set of goals.
• Assess the current maturity of the data operations teams and implement a roadmap that considers the necessary competencies and capabilities and their dependencies in moving towards the desired DataOps target state.