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Data News — Week 22.45

Christophe Blefari

Kovid wrote an article that tries to explain what are the ingredients of a data warehouse. A data warehouse is a piece of technology that acts on 3 ideas: the data modeling, the data storage and processing engine. Modeling is often lead by the dimensional modeling but you can also do 3NF or data vault.

BI 130
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A Guide to Data Pipelines (And How to Design One From Scratch)

Striim

Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures. Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets.

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Implementing the Netflix Media Database

Netflix Tech

under varying load conditions as well as a wide variety of access patterns; (b) scalability?—?persisting data access semantics that guarantee repeatable data read behavior for client applications. MDVS also serves as the storehouse and the manager for the data schema itself.

Media 97
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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

You can produce code, discover the data schema, and modify it. Smooth Integration with other AWS tools AWS Glue is relatively simple to integrate with data sources and targets like Amazon Kinesis, Amazon Redshift, Amazon S3, and Amazon MSK. Developers get access to developer endpoints that they can use to work with the code.

AWS 98
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What is ELT (Extract, Load, Transform)? A Beginner’s Guide [SQ]

Databand.ai

This dispersed data environment creates a challenge for businesses that need to access and analyze their data. ELT offers a solution to this challenge by allowing companies to extract data from various sources, load it into a central location, and then transform it for analysis.

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Comparing Performance of Big Data File Formats: A Practical Guide

Towards Data Science

Parquet vs ORC vs Avro vs Delta Lake Photo by Viktor Talashuk on Unsplash The big data world is full of various storage systems, heavily influenced by different file formats. These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction.

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The Pros and Cons of Leading Data Management and Storage Solutions

The Modern Data Company

And by leveraging distributed storage and open-source technologies, they offer a cost-effective solution for handling large data volumes. In other words, the data is stored in its raw, unprocessed form, and the structure is imposed when a user or an application queries the data for analysis or processing.