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Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB. Each of these technologies has its own strengths and weaknesses, but all of them can be used to gain insights from large data sets. The most popular NoSQL database systems include MongoDB, Cassandra, and HBase.

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Top Database Project Ideas to Work on 2023 [with Source Code]

Knowledge Hut

It is also one of the most important database projects for students. Top Database Project Ideas Using MongoDB MongoDB is a popular NoSQL database management system that is widely used for web-based applications. Plus, MongoDB also enables efficient indexing, which facilitates quick query execution at scale.

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RDBMS vs NoSQL: Key Differences and Similarities

Knowledge Hut

Making decisions in the database space requires deciding between RDBMS (Relational Database Management System) and NoSQL, each of which has unique features. RDBMS uses SQL to organize data into structured tables, whereas NoSQL is more flexible and can handle a wider range of data types because of its dynamic schemas.

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The Role of Database Applications in Modern Business Environments

Knowledge Hut

Database Software- Document Store (e.g.-MongoDB): MongoDB): MongoDB is a prominent database software that comes under the category of "document store" databases. Document store databases, such as MongoDB, are intended to store and manage data that is unstructured or semi-structured, such as documents.

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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

Unlike structured data, which is organized into neat rows and columns within a database, unstructured data is an unsorted and vast information collection. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc. Social media posts.

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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Variety is the vector showing the diversity of Big Data.

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

AltexSoft

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. They can be accumulated in NoSQL databases like MongoDB or Cassandra.