The Scientist, the Engineer, and the Warehouse: Implementing Cloud Analytics

Published: 6/12/2020

The boundaries between data roles are blurring as companies look for ways to boost efficiency and cut costs.

Data science provides support that companies need for innovation, efficiency, and competitive advantages. But you need capabilities that go beyond the scope of the data scientist to use data science at scale. 

The role and the skills of the data engineer have emerged to ensure that predictive models can help companies address their new challenges. And the cloud data warehouse has developed to address new scalability, availability, and budgetary issues.

Read this white paper to learn what it takes to put cloud analytics into practice. 

  • Understand the distinct skills of the data scientist and the data engineer.
  • Find out how these roles work together with a cloud data warehouse.
  • Discover ways that expanding skill sets can help you meet changing needs.
  • Learn how Azure Synapse Analytics fits into an effective architecture.
  • See how Azure Synapse supports governance, manageability, and elasticity.
The Scientist, the Engineer, and the Warehouse: Implementing Cloud Analytics

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