This was a very helpful lecture! It's great to be able to review it again during the remaining period.

wong4709556037

You will learn about the four stages of big data processing [data collection ▶ data storage ▶ data analysis ▶ expression] in a more fun and systematic way through a code lab method consisting of 30% theory + 70% practice 🧑🏻‍🏫

jphil

Big Data Pipeline Master; Tools and Techniques for Success

Hello, Kim Soo-hyun,

Thank you for your valuable review, and I hope my lectures will be of great help to you in the future.

Happy New Year :)

빅데이터

데이터처리

데이터분석

elasticsearch

입문

초급

중급이상

Big Data

일래스틱서치

Elasticsearch

아파치 스파크

Apache Spark

키바나

Kibana

아파치 하둡

Hadoop

Introduction to Big Data

Data Acquisition [Basic]

Data Acquisition [Advanced]

[Session] Git and Github

Data Storage [S3]

Data Storage [HDFS] Theory

Data Storage [HDFS] Practice

Data Analysis [Spark Basic]

Data Analysis [Explore Dataframe]

Data Analysis [Spark Advanced]

Data Visualization [NODE JS] Theory

Data Visualization [NODE JS] Practice

[Session] ELK 1, Elasticsearch

[Session] ELK 2, Kibana and Logstash

Special Lecture

Special Lecture <Docker>