Remove Business Intelligence Remove Culture Remove Data Engineering Remove Microservices
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The state of data quality in 2020

O'Reilly Media - Ideas

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. An additional 7% are data engineers.

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Data Mesh Architecture: Concept, Main Principles, and Implementation

Altexsoft

This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.

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DataOps: Adjusting DevOps for Analytics Product Development

Altexsoft

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

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Organise your engineering teams around the work by reteaming

Abhishek Tiwari

Both models work on the scale, particularly when the company's core values, priorities, and culture all three are well aligned. ERP engineering squad - supply chain planning, purchase order management, product lifecycle management, merchandise planning, etc.