Remove Business Intelligence Remove Continuous Delivery Remove Data Engineering Remove DevOps
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Data Science on Steroids: Productionised Machine Learning as a Value Driver for Business

OpenCredo

Machine Learning, alongside a mature Data Science, will help to bring IT and business closer together. By leveraging data for actionable insights, IT will increasingly drive business value. Typically, these will be Business Intelligence analysts, Data Scientists, and Machine Learning Engineers.

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DataOps: Adjusting DevOps for Analytics Product Development

Altexsoft

New approaches arise to speed up the transformation of raw data into useful insights. Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. How DataOps relates to Agile, DevOps, and MLOps.

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Analytics Engineer: Job Description, Skills, and Responsibilities

Altexsoft

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

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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.