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DataOps For Business Analytics Teams

DataKitchen

Business analysts often find themselves in a no-win situation with constraints imposed from all sides. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. The business analyst is embedded in the business unit. Some IT teams are fantastic.

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Implementing a Pharma Data Mesh using DataOps

DataKitchen

Below is a discussion of a data mesh implementation in the pharmaceutical space. For those embarking on the data mesh journey, it may be helpful to discuss a real-world example and the lessons learned from an actual data mesh implementation. Figure 1: Data requirements for phases of the drug product lifecycle.

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Webinar Summary: Driving Data Analytic Team Excellence Through Agility, Efficiency, and Aphorisms

DataKitchen

Using humor and wisdom, James shared his experiences with various data professionals, from data engineers and data scientists to analysts. Summary James started by reminiscing about his early days as an analyst, when he spent 80% of his time on data cleaning and organizing, with very little time left for actual analytics.

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What is a DataOps Engineer?

DataKitchen

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. While car companies lowered costs using mass production, companies in 2021 put data engineers and data scientists on the assembly line. A more technical discussion will follow in the next edition of this blog series.

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Webinar Summary: Data Mesh and Data Products

DataKitchen

Webinar Summary: DataOps and Data Mesh Chris Bergh, CEO of DataKitchen, delivered a webinar on two themes – Data Products and Data Mesh. Bergh started by discussing the complexity within data and analytics teams, stating that complexity makes everything more complicated and, in the long run, it kills productivity.

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Do You Need a DataOps Dojo?

DataKitchen

Centralizing analytics brings it under control but granting analysts free reign is necessary to foster innovation and stay competitive. Below we’ll discuss some standard DataOps technical services that could be developed and supported by a centralized team. Deploy to production. Product monitoring. Development sandboxes

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Start DataOps Today with ‘Lean DataOps’

DataKitchen

Lean DataOps delivers “ bang for the buck” by prioritizing activities that will most impact the productivity of the individual or team. As productivity improves, you can widen the DataOps circle and carefully invest in strategic process change that serves as the foundation for further improvements in team velocity. Production DataOps.

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