- 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 Specialization
Springboard for BI Analytics success. Develop hands-on skills for building data pipelines, warehouses, reports and dashboards.
Offered By


What you will learn
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
Skills you will gain
About this Specialization
Applied Learning Project
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.
No prior experience required.
No prior experience required.
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 4 Courses in this Specialization
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?
Offered by

IBM Skills Network
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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