Analytics Business Intelligence Data Engineering Quality Assurance 
CIO
JANUARY 10, 2023
Thomas Vick, regional director for Robert Half’s technology practice group, says that, in particular, demand has dropped for quality assurance engineers and level 1 help desk work. “On On the flip side, we have seen AI and digitalization create new jobs that didn’t exist before,” Vick says. “In
TIBCO - Connected Intelligence
DECEMBER 16, 2020
Imagine you’re a data engineer at a Fortune 1000 company. Your company has thousands of databases and 14,000 business intelligence users. You use data virtualization to create data views, configure security, and share data. One: Streaming Data Virtualization. All this data is in motion.
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Altexsoft
AUGUST 29, 2023
In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.
Altexsoft
SEPTEMBER 9, 2022
In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Metadata quality assurance. Types of metadata.
Mobilunity
NOVEMBER 24, 2021
The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Who Is an ETL Engineer?
Altexsoft
JULY 19, 2022
She formulated the thesis in 2018 and published her first article “How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh” in 2019. So, to avoid any confusion, please be aware that data mesh is NOT. Some organizational approaches to analytics ownership are explained in our article about data science teams.
Altexsoft
OCTOBER 8, 2021
But here’s the thing, even though you receive all customer data you need, it exists in a bunch of disjointed sources such as CRMs, customer-facing apps, websites, and others. With data integration, you have all information available in a single interface resulting in more efficient, faster querying and analytics. Source: G2.
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