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Data Warehouses vs. Data Lakes vs. Data Marts: Need Help Deciding?

KDnuggets

A comparative overview of data warehouses, data lakes, and data marts to help you make informed decisions on data storage solutions for your data architecture.

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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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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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Open-Source Data Warehousing – Druid, Apache Airflow & Superset

Simon Späti

However, this is still not common in the Data Warehouse (DWH) field. In my recent blog, I researched OLAP technologies, for this post I chose some open-source technologies and used them together to build a full data architecture for a Data Warehouse system. Why is this?

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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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Thoughts on Amazon Express One and its impact in Data Infrastructure

Data Engineering Weekly

Revisiting The Current State of Data Infrastructure Let’s revisit the current state of the data infrastructure before discussing the S3 Express. There are two critical properties of data warehouse access patterns. Data freshness matters a lot—the more recent the data, the more frequently it is accessed.

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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.