Data Engineering Engineering Management Presentation 
Cloudera
SEPTEMBER 17, 2020
For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. Resource isolation and centralized GUI-based job management.
TechCrunch
DECEMBER 10, 2020
” It currently has a database of some 180,000 engineers covering around 100 or so engineering skills, including React, Node, Python, Agular, Swift, Android, Java, Rails, Golang, PHP, Vue, DevOps, machine learning, data engineering and more.
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Cloudera
AUGUST 20, 2020
Data from the US Treasury website show which companies received PPP loans and how many jobs were retained. Analysis of this data presents three challenges. First, the size of the data is significant. The amount of time to pull, curate, transform, retrieve and report on that data is time intensive. Objective.
Altexsoft
NOVEMBER 28, 2019
In the scope of business intelligence project, a BI developer takes engineering, management, and strategic planning responsibilities. The project scope defines the degree of involvement for a certain role, as engineers with similar technology stacks and domain knowledge can be interchangeable. Data engineer.
Apiumhub
APRIL 5, 2022
With over 1000 practical case studies presented on the past 6 editions and with new geo events in the MEA and the APAC region, the event is a worldwide movement, ushering the community of data, analytics and AI practitioners across functions, companies, industries, sectors, countries and regions to collaborate, benchmark, share and innovate.
Netflix Tech
NOVEMBER 22, 2019
4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. Thursday?—?December
O'Reilly Media - Ideas
JUNE 19, 2019
First, the machine learning community has conducted groundbreaking research in many areas of interest to companies, and much of this research has been conducted out in the open via preprints and conference presentations. Discussions around machine learning tend to revolve around the work of data scientists and model building experts.
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