Altexsoft
JULY 23, 2020
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.
Hu's Place - HitachiVantara
APRIL 11, 2019
Data breaches are common, rogue data sets propagate in silos, and companies’ data technology often isn’t up to the demands put on it." That was in a report back in 2017. Businesses are looking to DataOps, to speed up the process of turning data into business out comes. What has changed since then?
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Apiumhub
AUGUST 12, 2021
This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.
Datavail
SEPTEMBER 8, 2022
According to Statista , in 2021 companies used an average of 110 software as a service (SaaS) applications in their IT environment, which is a sevenfold increase from just 16 applications in 2017. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers.
O'Reilly Media - Ideas
JANUARY 25, 2024
But Stack Overflow shows a broad peak in questions from 2014 to 2017, with a sharp decline afterward; the number of questions in 2023 is barely 50% of the peak, and the 20% decline from the January 2023 report to the July report is only somewhat sharper than the previous drops. Interest in data warehouses saw an 18% drop from 2022 to 2023.
d2iq
FEBRUARY 19, 2021
Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.
O'Reilly Media - Ideas
FEBRUARY 18, 2020
Also: infrastructure and operations is trending up, while DevOps is trending down. Up until 2017, the ML+AI topic had been amongst the fastest growing topics on the platform. After several years of steady climbing—and after outstripping Java in 2017—Python-related interactions now comprise almost 10% of all usage. Coincidence?
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