How to implement and benefit from DataOps in 6 steps.

Data-centric projects are becoming bigger in both size and complexity, and companies increasingly look to analytics to drive growth strategies. More and more, data teams are responsible for supplying business partners with analytical insights quickly and effectively to provide a competitive edge and keep up with an ever-evolving marketplace. However, there is a disconnect between the speed at which marketing and sales demands evolve and the speed at which many data teams can deliver useful insights. Often times data quality is inhibited by siloed pipelines, a lack of collaboration across data functions, and manual or ungoverned processes for data delivery. This gap between what users need and what data teams can provide is a source of conflict and frustration for many businesses and can prevent an organization from taking full advantage of the strategic benefit of its data.

Data teams today need to be able to deliver reliable and relevant insights on-demand. DataOps is a next-gen vision for data quality, integration, and real-time analytics that promotes cross-team collaborations and seeks to remove obstructions from the flow of data across pipelines.

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