Tag - real time analytics
06Feb

Unlocking the Power of Patterns in Event Stream Processing (ESP): The Critical Role of Apache Flink’s FlinkCEP Library

We call this an event when a button is pressed, a sensor detects a temperature change or a transaction flows through. An event is an action or state change that is important to an application. Event stream processing (ESP) refers to a method or technique to stream the data in real-time as it passes through a system. The main objective of  ESP is to focus on the key goal of taking action on the data as it arrives. This enables real-time analytics...

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23Jan

Real-Time Redefined: Apache Flink and Apache Paimon Influence Data Streaming’s Future

    Apache Paimon is made to function well with constantly flowing data, which is typical of contemporary systems like financial markets, e-commerce sites, and Internet of Things devices. It is a data storage system made to effectively manage massive volumes of data, particularly for systems that deal to analyze data continuously such as streaming data or with changes over time like database updates or deletions. To put it briefly, Apache Paimon functions similarly to a sophisticated librarian for our data....

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Kafka with Flink
13Feb

Why Apache Kafka and Apache Flink work incredibly well together to boost real-time data analytics

When data is analyzed and processed in real-time, it can yield insights and actionable information either instantly or with very little delay from the time the data is collected. The capacity to collect, handle, and retain user-generated data in real-time is crucial for many applications in today’s data-driven environment. There are various ways to emphasize the significance of real-time data analytics like timely decision-making,  IoT and sensor data processing, enhanced customer experience, proactive problem resolution, fraud detection and security,...

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