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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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Mage aims to be the ‘Stripe for AI;’ raises $6.3M for developer tools to build AI into apps

TechCrunch

Mage , developing an artificial intelligence tool for product developers to build and integrate AI into apps, brought in $6.3 While collaborating with product developers, Dang and Wang saw that while product developers wanted to use AI, they didn’t have the right tools in which to do it without relying on data scientists.

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What is Data Engineering: Explaining Data Pipeline, Data Warehouse, and Data Engineer Role

Altexsoft

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. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

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The Right Stuff: The Role of MLOps in AI Success

CIO

Interestingly, many companies do just that, creating a disconnect between data science teams and IT/DevOps when it comes to AI development. The biggest divide between data scientists and IT often centers around the tools necessary to develop AI models. This gap is a significant reason why AI pilot projects fail. “AI

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Survey: Execs eager to implement generative AI, but few know how

CIO

Overwhelming majorities of executives around the world are planning to spend money on generative AI this year, but very few are truly ready for the technology, according to a survey released today by the Boston Consulting Group. It forces conversations like ‘what kind of data stores do we have,’ and ‘what can we really do with them?’”

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Data Engineering is Critical to Big Data Success

Cloudera

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. Image 1: Data Engineering Skillsets.

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Cloudera Operational Database application development concepts

Cloudera

In this blog post, we’ll look at both Apache HBase and Apache Phoenix concepts relevant to developing applications for Cloudera Operational Database. But first, let’s look at the different form factors in which Cloudera Operational Database is available to developers: Public cloud: CDP Data Hub Operational Database template .