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What is a data architect? Skills, salaries, and how to become a data framework master

CIO

Information/data governance architect: These individuals establish and enforce data governance policies and procedures. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

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Predibase exits stealth with a low-code platform for building AI models

TechCrunch

Data science teams are stymied by disorganization at their companies, impacting efforts to deploy timely AI and analytics projects. In a recent survey of “data executives” at U.S.-based and low-code data engineering platform Prophecy (not to mention SageMaker and Vertex AI ). healthcare company.”

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Why Are We Excited About the REAN Cloud Acquisition?

Hu's Place - HitachiVantara

Forbes notes that a full transition to the cloud has proved more challenging than anticipated and many companies will use hybrid cloud solutions to transition to the cloud at their own pace and at a lower risk and cost. This will be a blend of private and public hyperscale clouds like AWS, Azure, and Google Cloud Platform.

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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps.

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How to Hire AI Developers?

Existek

Monitoring and maintenance: After deployment, AI software developers monitor the performance of the AI system, address arising issues, and update the model as needed to adapt to changing data distributions or business requirements. For example, healthcare AI developers should understand medical terminology and practices.

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What is Streaming Analytics: Data Streaming, Stream Processing, and Real-time Analytics

Altexsoft

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

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The rise of the data lakehouse: A new era of data value

CIO

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. You can intuitively query the data from the data lake.

Data 350