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Data Engineering Weekly #161

Data Engineering Weekly

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Editor’s Note: Chennai, India Meetup - March-08 Update We are thankful to Ideas2IT to host our first Data Hero’s meetup.

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5 Skills Data Engineers Should Master to Keep Pace with GenAI

Monte Carlo

If you’re a data engineer experiencing GenAI-induced whiplash, you’re not alone. On one hand, everyone’s talking about whether GenAI’s not-insignificant data engineering skills are going to automate away their jobs. They need robust data pipelines, high-quality data, well-guarded privacy, and cost-effective scalability.

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The Symbiotic Relationship Between AI and Data Engineering

Ascend.io

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

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Intrinsic Data Quality: 6 Essential Tactics Every Data Engineer Needs to Know

Monte Carlo

What happens when you strip away all the noise of queries and pipelines and focus on the data itself? You get down to the intrinsic data quality. What’s the difference between intrinsic and extrinsic data quality? Intrinsic data quality is the quality of data assessed independently of its use case.

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Enterprise Data Quality: 3 Quick Tips from Data Leaders

Monte Carlo

It’s 2024, and the data estate has changed. Data systems are more diverse. But even though the data landscape is evolving, many enterprise data organizations are still managing data quality the “old” way: with simple data quality monitoring. Architectures are more complex.

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How to become Azure Data Engineer I Edureka

Edureka

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

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7 Essential Data Cleaning Best Practices

Monte Carlo

But, for data engineers, there’s something else that comes pretty close to the top of that list: clean data. Data cleaning is an essential step to ensure your data is safe from the adage “garbage in, garbage out.” Define Clear Data Quality Standards 2. Implement Routine Data Audits 3.