Azure Data Engineering Technical Advisors 
CIO
APRIL 2, 2025
They have to take into account not only the technical but also the strategic and organizational requirements while at the same time being familiar with the latest trends, innovations and possibilities in the fast-paced world of AI. However, the definition of AI consulting goes beyond the purely technical perspective.
CIO
JUNE 3, 2024
Companies should be proactive about acquiring AI talent, using both training programs with their current employees and hiring programs to attract outside experts, he advises. That mix of technical and soft skills is another factor shaping the shift toward reskilling for AI. Reskilling employees is a crucial step, he adds. “In
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CIO
AUGUST 18, 2022
To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We You can intuitively query the data from the data lake. Users coming from a data warehouse environment shouldn’t care where the data resides,” says Angelo Slawik, data engineer at Moonfare.
Apiumhub
AUGUST 12, 2021
His main work is software development consulting, which combines actually writing code with advising clients on how to do that better. His current technical expertise focuses on integration platform implementations, Azure DevOps, and Cloud Solution Architectures. Currently, he is the T. Twitter: ??
Mobilunity
DECEMBER 9, 2024
Google Professional Machine Learning Engineer implies developers knowledge of design, building, and deployment of ML models using Google Cloud tools. It includes subjects like data engineering, model optimization, and deployment in real-world conditions. AI consultant. AI solutions architect.
Mobilunity
NOVEMBER 11, 2024
With an advanced LLM, businesses can assemble personalized training data or deliver round-the-clock assistance within internal systems to guide employees through tasks and processes. The technical side of LLM engineering Now, let’s identify what LLM engineering means in general and take a look at its inner workings.
Existek
SEPTEMBER 28, 2023
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. It covers a dynamic process where everyone works towards achieving set goals and objectives.
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