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Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

This article will discuss big data analytics technologies, technologies used in big data, and new big data technologies. Check out the Big Data courses online to develop a strong skill set while working with the most powerful Big Data tools and technologies.

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Deciphering the Data Enigma: Big Data vs Small Data

Knowledge Hut

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques.

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Top 10 Hadoop Tools to Learn in Big Data Career 2024

Knowledge Hut

With the help of these tools, analysts can discover new insights into the data. Hadoop helps in data mining, predictive analytics, and ML applications. Why are Hadoop Big Data Tools Needed? They can make optimum use of data of all kinds, be it real-time or historical, structured or unstructured.

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Spark vs Hive - What's the Difference

ProjectPro

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Hive uses HQL, while Spark uses SQL as the language for querying the data.

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History of Big Data

Knowledge Hut

For example, talking about the history of big data in healthcare, hospitals faced many problems earlier in patient data management, security, and privacy. A hospital’s performance depends largely on how patient data is handled, including accessing and retrieving it for various purposes.

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Top 16 Data Science Job Roles To Pursue in 2024

Knowledge Hut

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. The dataset can be either structured or unstructured or both.

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Data Engineer Learning Path, Career Track & Roadmap for 2023

ProjectPro

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Independently create data-driven solutions that are accurate and informative.