CIO

FEBRUARY 6, 2023

When the pandemic hit, Aflac CIO Rich Gilbert felt like the firm’s insurance agent business could be a dead duck. Yet Gilbert tapped the company’s Hatch Innovation Lab to build a new virtual enrollment system that had its origin in the data center but was quickly redesigned for the cloud amid the pandemic.

Insurance 331

Insurance Artificial Inteligence Machine Learning Virtualization 331

CIO

SEPTEMBER 18, 2023

The 300-person shop doesn’t focus on the classic network or data center support roles — those are outsourced to service providers. The company, a Google Cloud Platform shop, came face-to-face with that reality when it became difficult to find specialists, shifting its emphasis to growing its own talent.

Technical Review 340

Technical Review Pharmaceuticals Security Training 340

Xebia

JANUARY 19, 2023

– Jesse Anderson The data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering. Lastly, do not forget to back up your data. Data disappears.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Altexsoft

JANUARY 22, 2020

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. A complete guide to business intelligence and analytics. The role of business intelligence developer.

Analytics 20

Analytics Data IoT Analysis 20

Protera

MAY 23, 2023

The public cloud is the future of business — Gartner reports that by 2025 more than 95% of new digital workloads will be cloud native, and 80% of companies say that they will close their on-premise data centers by the same year (compared to only 10% in 2020). But not as many are doing it successfully.

Cloud 52

Cloud Testing Data Center Systems Review 52

DataRobot

SEPTEMBER 6, 2022

Data science teams cannot create a model and “throw it over the fence” to another team. Everyone needs to work together to achieve value, from business intelligence experts, data scientists, and process modelers to machine learning engineers, software engineers, business analysts, and end users. Request a Demo.

Artificial Inteligence 52

Artificial Inteligence Analytics Data Machine Learning 52

DataRobot

SEPTEMBER 14, 2021

Now, data scientists , analytics experts , business users , and IT teams can collaborate in a single, unified platform. Now, all data from all sources can come together in a single system of record. Now, you can deploy AI anywhere, across multiple clouds, the data center, and the edge.

Data Center 52

Data Center Cloud Google Cloud Analytics 52