- Shell Script
- Bash (Unix Shell)
- Linux
- Cloud Databases
- Python Programming
- Ipython
- Relational Database Management System (RDBMS)
- SQL
- Extraction, Transformation And Loading (ETL)
- Apache Kafka
- Apache Airflow
- Data Pipelines
BI Foundations with SQL, ETL and Data Warehousing 특화 과정
Springboard for BI Analytics success. Develop hands-on skills for building data pipelines, warehouses, reports and dashboards.
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배울 내용
Write SQL queries to work with relational databases including CREATE TABLE, SELECT, INSERT, UPDATE, DELETE, ORDER, JOIN, Functions, etc.
Execute commonly used Linux commands; Automate Extract, Transform and Load (ETL) jobs and data pipelines using BASH scripts, Apache Airflow & Kafka
Design Data Warehouses using star and snowflake schemas, loading and verify data in staging areas, build cubes, rollups and materialized views/tables
Analyze data in warehouses using interactive reports and dashboards using BI tools such as Cognos Analytics
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이 전문 분야 정보
응용 학습 프로젝트
Each course provides lots of practice using hands-on labs and projects on cloud-based environments with real tools. Hands-on exercises include: running Linux commands and pipes, in creating shell scripts, scheduling jobs using cron, building ETL and data pipelines, creating & monitoring Airflow DAGs, working with streaming data using Kafka, designing a data warehouses with star and snowflake schemas, verifying data quality, loading staging and production warehouses, writing SQL queries and joins with PostgreSQL, MySQL & DB2 databases, developing cubes, rollups and materialized views/tables, creating interactive reports & dashboards, and analyzing warehouse data using BI tools like Cognos Analytics.
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사전 경험이 필요하지 않습니다.
특화 과정 이용 방법
강좌 수강
Coursera 특화 과정은 한 가지 기술을 완벽하게 습득하는 데 도움이 되는 일련의 강좌입니다. 시작하려면 특화 과정에 직접 등록하거나 강좌를 둘러보고 원하는 강좌를 선택하세요. 특화 과정에 속하는 강좌에 등록하면 해당 특화 과정 전체에 자동으로 등록됩니다. 단 하나의 강좌만 수료할 수도 있으며, 학습을 일시 중지하거나 언제든 구독을 종료할 수 있습니다. 학습자 대시보드를 방문하여 강좌 등록 상태와 진도를 추적해 보세요.
실습 프로젝트
모든 특화 과정에는 실습 프로젝트가 포함되어 있습니다. 특화 과정을 완료하고 수료증을 받으려면 프로젝트를 성공적으로 마쳐야 합니다. 특화 과정에 별도의 실습 프로젝트 강좌가 포함되어 있는 경우, 다른 모든 강좌를 완료해야 프로젝트 강좌를 시작할 수 있습니다.
수료증 취득
모든 강좌를 마치고 실습 프로젝트를 완료하면 취업할 때나 전문가 네트워크에 진입할 때 제시할 수 있는 수료증을 취득할 수 있습니다.

이 전문 분야에는 4개의 강좌가 있습니다.
Hands-on Introduction to Linux Commands and Shell Scripting
This course provides a practical introduction to Linux and commonly used Linux / UNIX shell commands. It teaches you the basics of Bash shell scripting to automate a variety of tasks. The course includes both video-based lectures as well as hands-on labs to practice and apply what you learn. You will have no-charge access to a virtual Linux server that you can access through your web browser, so you don't need to download and install anything to perform the labs.
Databases and SQL for Data Science with Python
Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist.
ETL and Data Pipelines with Shell, Airflow and Kafka
After taking this course, you will be able to describe two different approaches to converting raw data into analytics-ready data. One approach is the Extract, Transform, Load (ETL) process. The other contrasting approach is the Extract, Load, and Transform (ELT) process. ETL processes apply to data warehouses and data marts. ELT processes apply to data lakes, where the data is transformed on demand by the requesting/calling application.
Getting Started with Data Warehousing and BI Analytics
Data is one of an organization’s most valuable commodities. But how can organizations best use their data? And how does the organization determine which data is the most recent, accurate, and useful for business decision making at the highest level?
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IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
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전문 분야를 완료하는 데 얼마나 걸리나요?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
전문 분야를 완료하면 대학 학점을 받을 수 있나요?
What will I be able to do upon completing the Specialization?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.