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Data Analysis

Apache Flink with Silicon Valley Engineers

Real-time data processing is now essential, not optional! Learn to handle real-time streaming smartly with Apache Flink. Batch? Streaming? Even complex concepts can be understood easily and quickly. Hands-on practice configuration where you'll get the hang of it by directly working with Kafka and DB integration! In a world driven by data, start first with Flink.

67 learners are taking this course

  • altoformula
백엔드이해하기
데이타정제
빅데이타
flink
Big Data
Data Engineering
data-analysis
data-transformation

What you will learn!

  • Conceptual Differences Between Real-time Data Streaming and Batch Processing

  • Understanding Flink's Core Components and Architecture

  • Kafka, File System, Flink Integration Practice

  • Windows, state management, checkpoints, and other features frequently used in practice

🚀 The Core of Real-time Data Processing, Apache Flink 2.x Introduction

  • In an era of data deluge, 'real-time processing' is no longer an option but a necessity!

  • Apache Flink is the ultimate solution for real-time data processing that global companies like Netflix, Uber, and Alibaba are already using.


  • 🧠 What is Flink?
    Not micro-batch, but real real-time! I'll explain Flink architecture and core concepts in an easy way.

  • Real-time vs Batch: Let's Settle This Once and For All
    Let's compare the differences and pros and cons of these two approaches with real examples to see what to use in which situations.

  • 💬 Perfect match with Kafka
    "Kafka sends the data, and Flink processes it in real-time!" This combination is really widely used in practice.

  • 🌡 Hands-on Practice: IoT Sensor Data Average Calculation Project
    Let's create a project that calculates average temperature in real-time using actual data.
    → You'll get a clear sense of how Flink is used in real-world scenarios.

flink, big data, data engineering, data-analysis, data transformation

Level up with Apache Flink! Start your practical streaming course now! 💪

🙌 Recommended for these people

📊I have a lot of data, but I don't know what to do or how to handle it

Developers who want to grasp the flow of real-time data streaming from start to finish

I understand Kafka, but let's go all the way to real-time processing!

Someone who is receiving data through Kafka and wants to process it in real-time

🔥Data Engineering, Should I Give It a Serious Try?

A development beginner who has basic knowledge of Python and Java but still lacks practical work experience

🎉 Here's how you'll change after taking the course!

  • The entire flow of real-time data processing is visible


    • We'll directly implement the entire flow of receiving data from Kafka, performing real-time analysis with Flink, and exporting results to external systems. Now real-time pipelines will be understood as a tangible structure rather than something abstract.

  • Event time-based processing concepts become clear

    • Concepts like Event Time, Watermark, and Window can be confusing at first. In this lecture, you'll process actual data based on time and experience firsthand how time concepts affect streaming processing.

  • You will obtain practical project results that can be included in your portfolio


    • 📌"Real-time IoT Sensor Data Analysis Dashboard"

      • Receiving sensor data with Kafka

      • Calculate Average Temperature with Flink

      • Output and save results in real-time

📚Here's what you'll learn

Understanding the Core Concepts and Structure of Real-time Data Streaming

  • Apache Flink 2.x Basic Architecture and Operating Principles

  • Differences Between Batch and Streaming Processing Methods

  • Event Time, Window, Watermark and other key concepts for real-time processing

  • State Management and Fault Tolerance through Checkpoints

Building Real-world Streaming Pipelines with Kafka Integration

  • Hands-on practice of the complete flow: Data reception from Kafka → Processing in Flink → Output to external systems

  • IoT Sensor Data-Based Average Temperature Calculation Project

🤔 Do you have any questions?

Q1. I'm hearing about Flink for the first time - is it okay for complete beginners to take this course?

A. Yes! This course is structured so that even those who have never used Flink before can easily follow along.
We start by slowly explaining Flink's basic structure and concepts, and the process of integrating with Kafka is also guided through hands-on practice that you can follow directly.
We build up from the fundamentals, so don't worry!

Q2. I don't know much about Kafka either - will that be okay?

A. Don't worry! We'll explain only the necessary parts of Kafka in an easy way within the flow of the lecture.
While this isn't a course that deeply dives into Kafka itself, it's structured so you can learn the concepts and configurations needed to understand real-time data flow.
By actually working with the "Kafka + Flink combination," you'll naturally understand how to connect these two technologies.

Q3. Can I apply what I learn from the lectures directly to real work?

A. Yes, it's composed of examples and exercises that can be directly applied to real work.
For example, we'll build a project together that receives IoT sensor data and calculates average temperature in real-time. This isn't just a simple exercise,
but a structure that can be extended and applied to log analysis, monitoring, and alert systems in actual business environments.
After completing the course, you'll be able to see "how we can apply this to our service."

Pre-enrollment Reference Information

Practice Environment

  • Operating System and Version (OS): OS types and versions such as macOS, Linux, Ubuntu, etc.

  • Tools Used: Docker

  • Languages used: Python, Java

Learning Materials

  • PDF lecture materials (refer to each video learning material) and code materials are provided.

Prerequisites and Important Notes

  • This course is structured around hands-on practice and runs Apache Flink and Kafka in a Docker environment. Therefore, having the following foundational knowledge will help you take the course more smoothly:

    • Java's Basic Syntax and Usage

    • Python's basic syntax and usage

    • (Optional) Apache Spark Basic Information

    • How to Use Docker and Docker Compose

  • If you're not familiar with Docker, I recommend my free Docker beginner course.
    👉Go to free Docker course

  • The grammar is explained using version 2.X, which was the latest version at the time the course was opened (differs from 1.X grammar).

  • If you have trouble understanding something during the lecture or have any questions, please feel free to leave a comment with your question anytime!
    I live on the US West Coast, so please understand that my responses may be delayed due to the time difference.
    I'll help you as quickly and accurately as possible 😊

Recommended for
these people

Who is this course right for?

  • Backend developers who want to work with real-time data processing such as logs, traffic, and sensor data

  • Data engineers who want to introduce streaming-based technologies like Flink and Kafka into practical work

  • Someone who is on a team/company looking to transition from batch processing-centered data pipelines to streaming

  • A developer who has used Spark but wants to experience real real-time processing

  • Someone interested in cloud-based real-time analytics systems

Need to know before starting?

  • Java Basic Syntax

  • Basic concepts of Kafka and message queues

  • Linux basic commands and Docker usage experience (optional)

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Curriculum

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29 lectures ∙ (2hr 54min)

Course Materials:

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