Update flink@o6GQ3-8DgDtHzdX6yeg1w.md (#7115)

* Update spark@UljuqA89_SlCSDWWMD_C_.md

* Update src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md

* Update flink@o6GQ3-8DgDtHzdX6yeg1w.md

---------

Co-authored-by: Arik Chakma <arikchangma@gmail.com>

src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md

@@ -1,8 +1,9 @@
 # Flink
 
-Apache Flink is a distributed stream processing framework that is used to process large amounts of data in real-time. It is designed to be highly scalable and fault-tolerant. Flink is built on top of the Apache Kafka messaging system and is used to process data streams in real-time.
+Apache Flink is an open-source stream processing framework designed for real-time and batch data processing with low latency and high throughput. It supports event time processing, fault tolerance, and stateful operations, making it ideal for applications like real-time analytics, fraud detection, and event-driven systems. Flink is highly scalable, integrates with various data systems, and is widely used in industries for large-scale, real-time data processing tasks.
 
 Visit the following resources to learn more:
 
 - [@article@Apache Flink Documentation](https://flink.apache.org/)
 - [@feed@Explore top posts about Apache Flink](https://app.daily.dev/tags/apache-flink?ref=roadmapsh)
+-[@reference@Apache Flink Tutorialpoint](https://www.tutorialspoint.com/apache_flink/apache_flink_introduction.htm)