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

Altexsoft

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. However, they often forget about the fundamental work – data literacy, collection, and infrastructure – that must be done prior to building intelligent data products.

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Heartex raises $25M for its AI-focused, open source data labeling platform

TechCrunch

Heartex, a startup that bills itself as an “open source” platform for data labeling, today announced that it landed $25 million in a Series A funding round led by Redpoint Ventures. We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data.

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The 10 most in-demand IT jobs in finance

CIO

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Software engineer. Full-stack software engineer.

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The 10 most in-demand IT jobs in finance

CIO

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Software engineer. Full-stack software engineer.

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The 10 most in-demand tech jobs for 2023 — and how to hire for them

CIO

For some that means getting a head start in filling this year’s most in-demand roles, which range from data-focused to security-related positions, according to Robert Half Technology’s 2023 IT salary report. The ongoing tight IT job market has companies doing whatever they can to attract top tech talent.

LAN 358
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Forget the Rules, Listen to the Data

Hu's Place - HitachiVantara

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

Data 90
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Data Mesh Architecture: Concept, Main Principles, and Implementation

Altexsoft

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What is a data mesh?