Data Center Data Engineering IoT Machine Learning 
CIO
SEPTEMBER 12, 2022
The chief information and digital officer for the transportation agency moved the stack in his data centers to a best-of-breed multicloud platform approach and has been on a mission to squeeze as much data out of that platform as possible to create the best possible business outcomes. Data engine on wheels’.
CIO
OCTOBER 20, 2023
Certifications are offered in a variety of topics such as collaboration, CyberOps, data centers, DevNet and automation, design, enterprise networking, and security. Microsoft also offers certifications focused on fundamentals, specific job roles, or specialty use cases.
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Altexsoft
JUNE 25, 2019
Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering.
CIO
DECEMBER 1, 2022
Tapped to guide the company’s digital journey, as she had for firms such as P&G and Adidas, Kanioura has roughly 1,000 data engineers, software engineers, and data scientists working on a “human-centered model” to transform PepsiCo into a next-generation company.
Hu's Place - HitachiVantara
JANUARY 3, 2019
Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. Building an AI or machine learning model is not a one-time effort.
Cloudera
DECEMBER 20, 2022
McKinsey estimates that the use of data-driven technologies can drive operating and maintenance cost savings of more than 12%. For example, predictive maintenance, based on machine learning, will enable utility companies to take preventative action that avoids large-scale power outages and costs.
DataRobot
MARCH 10, 2022
This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. High-level example of a common machine learning lifecycle.
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