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A Dive into the Basics of Big Data Storage with HDFS

Analytics Vidhya

Introduction HDFS (Hadoop Distributed File System) is not a traditional database but a distributed file system designed to store and process big data. It provides high-throughput access to data and is optimized for […] The post A Dive into the Basics of Big Data Storage with HDFS appeared first on Analytics Vidhya.

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How to Design a Modern, Robust Data Ingestion Architecture

Monte Carlo

A data ingestion architecture is the technical blueprint that ensures that every pulse of your organization’s data ecosystem brings critical information to where it’s needed most. Ensuring all relevant data inputs are accounted for is crucial for a comprehensive ingestion process.

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Upgrade your Modern Data Stack

Christophe Blefari

Make your data stack take-off ( credits ) Hello, another edition of Data News. This week, we're going to take a step back and look at the current state of data platforms. What are the current trends and why are people fighting around the concept of the modern data stack. Is the modern data stack dying?

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Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

Big data in information technology is used to improve operations, provide better customer service, develop customized marketing campaigns, and take other actions to increase revenue and profits. It is especially true in the world of big data. It is especially true in the world of big data. What Are Big Data T echnologies?

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Data Science vs Cloud Computing: Differences With Examples

Knowledge Hut

Some techniques add to the development of technology in the business sectors, including Data Science and Cloud Computing, essential aspects of the technology industry. With the help of data science, one can gather all the critical analyses from vast chunks of data stored in clouds. In this model, the data is not 100% secure.

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History of Big Data

Knowledge Hut

Data handling became tedious only after huge amounts of it started to accumulate. For example, in 1880, the US Census Bureau needed to handle the 1880 Census data. They realized that compiling this data and converting it into information would take over 10 years without an efficient system.

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How Much Data Do We Need? Balancing Machine Learning with Security Considerations

Towards Data Science

For a data scientist, there’s no such thing as too much data. Photo by Trnava University on Unsplash Data Science vs Security/IT: A Battle for the Ages Acquiring and keeping data is the focus of a huge amount of our mental energy as data scientists. If you ask a data scientist “Can we solve this problem?”