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Apache Kafka and Apache Flink: An open-source match made in heaven

IBM Journey to AI blog

It allows your business to ingest continuous data streams as they happen and bring them to the forefront for analysis, enabling you to keep up with constant changes. Apache Kafka boasts many strong capabilities, such as delivering a high throughput and maintaining a high fault tolerance in the case of application failure.

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Best Data Engineering Tools Every Engineer Should Know

Pickl AI

Python, SQL, and Apache Spark are essential for data engineering workflows. Real-time data processing with Apache Kafka enables faster decision-making. offers Data Science courses covering essential data tools with a job guarantee. What Does a Data Engineer Do?

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Top Big Data Tools Every Data Professional Should Know

Pickl AI

Introduction to Big Data Tools In todays data-driven world, organisations are inundated with vast amounts of information generated from various sources, including social media, IoT devices, transactions, and more. Big Data tools are essential for effectively managing and analysing this wealth of information.

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Navigating the Big Data Frontier: A Guide to Efficient Handling

Women in Big Data

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

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How Thomson Reuters delivers personalized content subscription plans at scale using Amazon Personalize

AWS Machine Learning Blog

Thomson Reuters (TR) is one of the world’s most trusted information organizations for businesses and professionals. TR has a wealth of data that could be used for personalization that has been collected from customer interactions and stored within a centralized data warehouse.

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What is Data Ingestion? Understanding the Basics

Pickl AI

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making.

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How Netflix Applies Big Data Across Business Verticals: Insights and Strategies

Pickl AI

The architecture is divided into two main categories: data at rest and data in motion. Data at Rest This includes storage solutions such as S3 Data Warehouse and Cassandra. These systems handle the storage costs associated with keeping vast amounts of content and user data.