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Identifying budding big data talent in your company

O'Reilly Media - Data

Big data is often called one of the most important skill sets in the 21st century, and it’s experiencing enormous demand in the job market. Hiring data scientists and other big data professionals is a major challenge for large enterprises, leading many to shift their efforts to training existing staff. Statistics.

Big Data 203
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Tonic is betting that synthetic data is the new big data to solve scalability and security

TechCrunch

Big data is a sham. There is just one problem with big data though: it’s honking huge. Processing petabytes of data to generate business insights is expensive and time consuming. Processing petabytes of data to generate business insights is expensive and time consuming. What should a company do?

Big Data 267
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IT leaders: What’s the gameplan as tech badly outpaces talent?

CIO

Instead of hiring AI experts from the outside, it looked for existing software engineering staff who were interested in learning the new technology. Now the company is building its own internal program to train AI engineers. Gen AI in particular is rapidly being integrated into all types of software applications.

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Forward Thinking Tech Leaders at IO Seeking Big Data Engineer

CTOvision

Senior Software EngineerBig Data. IO is the global leader in software-defined data centers. IO has pioneered the next-generation of data center infrastructure technology and Intelligent Control, which lowers the total cost of data center ownership for enterprises, governments, and service providers.

Big Data 107
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Federal Big Data Community Convenes 6 Feb at Apache Hadoop Forum

CTOvision

By Bob Gourley If you are an analyst or executive or architect engaged in the analysis of big data, this is a “must attend” event. Registration is now open for the third annual Federal Big Data Apache Hadoop Forum! 6, as leaders from government and industry convene to share Big Data best practices.

Big Data 113
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Data engineers vs. data scientists

O'Reilly Media - Data

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

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The Advent of Intelligent Software Engineering 

DevOps.com

The post The Advent of Intelligent Software Engineering appeared first on DevOps.com. At the same time, deployment releases and operations are getting complex, debugging and traceability in production are increasingly […].