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Apache Kafka use cases: Driving innovation across diverse industries

IBM Journey to AI blog

Apache Kafka is an open-source , distributed streaming platform that allows developers to build real-time, event-driven applications. With Apache Kafka, developers can build applications that continuously use streaming data records and deliver real-time experiences to users. How does Apache Kafka work?

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A Comprehensive Guide to the main components of Big Data

Pickl AI

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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A Comprehensive Guide to the Main Components of Big Data

Pickl AI

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Predicting the Future of Data Science

Pickl AI

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally. The field has evolved significantly from traditional statistical analysis to include sophisticated Machine Learning algorithms and Big Data technologies.

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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. million by 2028.

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Training Models on Streaming Data [Practical Guide]

The MLOps Blog

The machine learning model is part of the Stream processing engine, and it provides the logic that helps the streaming data pipeline expose features within the stream and potentially within a historical data store. It can be used to collect, store, and process streaming data in real-time.

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How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

Data Lakes Data lakes are centralized repositories designed to store vast amounts of raw, unstructured, and structured data in their native format. They enable flexible data storage and retrieval for diverse use cases, making them highly scalable for big data applications.