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Top 14 Big Data Analytics Tools in 2024

Knowledge Hut

Real-time analytics platforms in big data apply logic and math to gain faster insights into data, resulting in a more streamlined and informed decision-making process. Some open-source technology for big data analytics are : Hadoop. Listed below are the top and the most popular tools for big data analytics : 1.

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How JPMorgan uses Hadoop to leverage Big Data Analytics?

ProjectPro

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. JP Morgan has massive amounts of data on what its customers spend and earn.

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5 Big Data and Hadoop Use Cases in Retail Analytics

ProjectPro

Below we present 5 most interesting use cases in big data and Retail Industry , which retailers implement to get the most out of data. Retail Analytics truly started with Target having figured out, quite early on – that data analytics can take the consumer buying experience to a whole other level.

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How Big Data Analysis helped increase Walmarts Sales turnover?

ProjectPro

2014 Kaggle Competition Walmart Recruiting – Predicting Store Sales using Historical Data Description of Walmart Dataset for Predicting Store Sales What kind of big data and hadoop projects you can work with using Walmart Dataset? petabytes of unstructured data from 1 million customers every hour.

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Top 20 Data Analytics Projects for Students to Practice in 2023

ProjectPro

According to Gartner , organizations can suffer a financial loss of up to 15 million dollars for the poor quality of data. As per McKinsey , 47% of organizations believe that data analytics has impacted the market in their respective industries. This number grew to 67.9% as of 2018, and is only increasing from there.

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10 Best Big Data Books in 2024 [Beginners and Advanced]

Knowledge Hut

This big data book for beginners covers the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining.