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Top Big Data Companies you need to Know in 2024

Knowledge Hut

Importance of Big Data Companies Big Data is intricate and can be challenging to access and manage because data often arrives quickly in ever-increasing amounts. Both structured and unstructured data may be present in this data. Thus, big data in big companies is used for various purposes.

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A Flexible and Efficient Storage System for Diverse Workloads

Cloudera

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. Diversity of workloads. Ranger policies.

Systems 87
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5 Generative AI Use Cases Companies Can Implement Today

Towards Data Science

Given LLMs’ capacity to understand and extract insights from unstructured data, businesses are finding value in summarizing, analyzing, searching, and surfacing insights from large amounts of internal information. Let’s explore how a few key sectors are putting gen AI to use.

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5 Generative AI Use Cases Companies Can Implement Today

Monte Carlo

Given LLMs’ capacity to understand and extract insights from unstructured data, businesses are finding value in summarizing, analyzing, searching, and surfacing insights from large amounts of internal information. Let’s explore how a few key sectors are putting gen AI to use.

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Introduction to MongoDB for Data Science

Knowledge Hut

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you. Why Use MongoDB for Data Science?

MongoDB 52
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Top Database Project Ideas to Work on 2023 [with Source Code]

Knowledge Hut

You can then create your own models within your codebase, allowing you to access and manipulate your database directly from Python when needed - whether that means fetching records or adding or updating them. Here is the source code for Online Insurance Portal, an Oracle Database Project.

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

AltexSoft

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) Dive deeper into the subject by reading our article Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation.