- Enterprise Data Warehouse (EDW)
- Data Science
- Extract Transform Load (ETL)
- Postgresql
- Database Architecture
- Business Intelligence (BI)
- Relational Database (RDBMS)
- SQL
- NoSQL
- MySQL
- Database (DBMS)
- database (DB) design
January 19, 2022
Approximately 3 months at 10 hours a week to completeSHANSHAN WANG's account is verified. Coursera certifies their successful completion of IBM IBM Data Warehouse Engineer Specialization.
Course Certificates Completed
Introduction to Relational Databases (RDBMS)
Getting Started with Data Warehousing and BI Analytics
Introduction to Data Engineering
ETL and Data Pipelines with Shell, Airflow and Kafka
Databases and SQL for Data Science with Python
Hands-on Introduction to Linux Commands and Shell Scripting
Master the most up-to-date practical skills and knowledge data warehouse engineers use in their daily roles
Learn how to deploy, manage, secure, operationalize, monitor and optimize relational database systems like MySQL, PostgreSQL, and BD2
Develop working knowledge of various types of SQL and queries to access and manipulate data in databases
Design and populate data warehouses and analyze the data with Business Intelligence (BI) tools like Cognos Analytics
Earned after completing each course in the Specialization
IBM
Taught by: Rav Ahuja & Sandip Saha Joy
Completed by: SHANSHAN WANG by January 9, 2022
4 weeks of study, 2-4 hours/week
IBM
Taught by: Ramesh Sannareddy & Rav Ahuja
Completed by: SHANSHAN WANG by December 28, 2021
4 weeks of study, 2-4 hours / week
IBM
Taught by: Rav Ahuja & Priya Kapoor
Completed by: SHANSHAN WANG by January 3, 2022
IBM
Taught by: Yan Luo, Jeff Grossman, Sabrina Spillner & Ramesh Sannareddy
Completed by: SHANSHAN WANG by December 20, 2021
5 weeks of study, 2-4 hours / week
IBM
Taught by: Rav Ahuja & Hima Vasudevan
Completed by: SHANSHAN WANG by December 30, 2020
6 weeks of study, 2-4 hours/week.
IBM
Taught by: Rav Ahuja, Sam Prokopchuk & Ramesh Sannareddy
Completed by: SHANSHAN WANG by December 14, 2021
4 week of study, 2-3 hours / week