Eliminate Your Analytics Development Bottlenecks With DataOps
Business users often have no concept of what it takes to design and deploy robust data analytics. The gap between expectations and execution is one of the main obstacles holding the analytics team back from delighting its users. Managers may ask for a simple change to a report. They don’t expect it to take weeks or months.
Analytics teams need to move faster, but cutting corners invites problems in quality and governance. How can you reduce cycle time to create and deploy new data analytics (data, models, transformation, visualizations, etc.) without introducing errors? The answer relates to finding and eliminating the bottlenecks that slow down analytics development.
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