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What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

Monte Carlo

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Data Storage Solutions As we all know, data can be stored in a variety of ways.

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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Though basic and easy to use, traditional table storage formats struggle to keep up. Track data files within the table along with their column statistics.

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Cloudera Open Data Lakehouse Named a Finalist in the CRN Tech Innovator Awards

Cloudera

The Awards showcase IT vendor offerings that provide significant technology advances – and partner growth opportunities – across technology categories including AI and AI infrastructure, cloud management tools, IT infrastructure and monitoring, networking, data storage, and cybersecurity.

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A Guide to Data Pipelines (And How to Design One From Scratch)

Striim

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures.

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The State of Data Engineering in 2024: Key Insights and Trends

Data Engineering Weekly

The Battle for Catalog Supremacy 2024 witnessed intense competition in the catalog space, highlighting the strategic importance of metadata management in modern data architectures. These innovations enable faster document parsing and reduce processing overhead, ensuring pipelines can scale without performance bottlenecks.

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Data Engineering Weekly #161

Data Engineering Weekly

The migration enhanced data quality, lineage visibility, performance improvements, cost reductions, and better reliability and scalability, setting a robust foundation for future expansions and onboarding.