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BI On Hadoop: Transforming Big Data Into Big Insights

ProjectPro

Let us compare traditional data warehousing and Hadoop-based BI solutions to better understand how using BI on Hadoop proves more effective than traditional data warehousing- Point Of Comparison Traditional Data Warehousing BI On Hadoop Solutions Data Storage Structured data in relational databases.

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Apache Kafka Architecture and Its Components-The A-Z Guide

ProjectPro

A detailed introduction to Apache Kafka Architecture, one of the most popular messaging systems for distributed applications. One of the challenges was keeping track of the data coming in from many data streams in multiple formats. Spotify uses Kafka as part of its log delivery system. So why is Kafka so popular?

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Top Hadoop Projects for Beginners in 2025

ProjectPro

Hadoop Common houses the common utilities that support other modules, Hadoop Distributed File System ( HDFS ) provides high throughput access to application data, Hadoop YARN is a job scheduling framework that is responsible for cluster resource management and Hadoop MapReduce facilitates parallel processing of large data sets.

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15 Business Analyst Project Ideas and Examples for Practice

ProjectPro

Project Idea: Mercari is a community-driven electronics-shopping application in Japan. In this project, you will build an automated price recommendation system using Mercari’s dataset to suggest prices to their sellers for different products based on the information collected. Answer: NO!)

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Top Big Data Tools You Need to Know in 2023

Knowledge Hut

Can be collected from public domains like social networks and websites or voluntarily gathered through questionnaires, product purchases, electronic check-ins, personal electronics and apps. Often stored in computer databases or the cloud and is analyzed using software specifically designed to handle large, complex data sets.

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History of Big Data

Knowledge Hut

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. Thus, it is no wonder that the origin of big data is a topic many big data professionals like to explore.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more. Data integration , on the other hand, happens later in the data management flow. For this task, you need a dedicated specialist — a data engineer or ETL developer.