IBM
BI Foundations with SQL, ETL and Data Warehousing Specialization
IBM

BI Foundations with SQL, ETL and Data Warehousing Specialization

Get job-ready for your first role in BI. Build the in-demand skills you need to get started in business intelligence (BI) in just 2 months. No degree or prior experience required.

IBM Skills Network Team
Shubhra Das
Rav Ahuja

Instructors: IBM Skills Network Team

10,923 already enrolled

Included with Coursera Plus

Get in-depth knowledge of a subject
4.6

(375 reviews)

Beginner level
No prior experience required
2 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.6

(375 reviews)

Beginner level
No prior experience required
2 months
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Sought-after business intelligence skills that will help you get your first job in BI

  • How to run frequently used SQL queries to work with RDBMS and automate ETL jobs and data pipelines using BASH scripts, Apache Airflow & Kafka

  • How to design data warehouses using STAR and snowflake schemas, load/verify data in staging areas, build cubes, rollups, & materialized views/tables

  • How to analyze data in warehouses for interactive reports and create dashboards using BI tools such as Cognos Analytics and Google Looker

Details to know

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Taught in English

Specialization - 5 course series

What you'll learn

  • Describe the Linux architecture and common Linux distributions and update and install software on a Linux system.

  • Perform common informational, file, content, navigational, compression, and networking commands in Bash shell.

  • Develop shell scripts using Linux commands, environment variables, pipes, and filters.

  • Schedule cron jobs in Linux with crontab and explain the cron syntax. 

Skills you'll gain

Category: Command-Line Interface
Category: Extract Transform and Load (ETL)
Category: Shell Script
Category: Bash (Scripting Language)
Category: Operating Systems
Category: OS Process Management
Category: File Management
Category: Linux Commands
Category: Network Protocols
Category: Bash (Unix Shell)
Category: Linux Servers
Category: Automation
Category: Linux Administration
Category: Unix Commands
Category: Linux
Category: Unix Shell
Category: Scripting Languages
Category: Unix

What you'll learn

  • Analyze data within a database using SQL and Python.

  • Create a relational database and work with multiple tables using DDL commands.

  • Construct basic to intermediate level SQL queries using DML commands.

  • Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.

Skills you'll gain

Category: Web Scraping
Category: Extract Transform and Load (ETL)
Category: Shell Script
Category: Databases
Category: Performance Tuning
Category: Data Pipelines
Category: Real Time Data
Category: Data Engineer
Category: Data Warehousing
Category: Data Migration
Category: Scalability
Category: Extract, Transform, Load
Category: Data Mart
Category: Apache Kafka
Category: Data Transformation
Category: Big Data
Category: Data Integration
Category: Apache Airflow

What you'll learn

  • Describe and contrast Extract, Transform, Load (ETL) processes and Extract, Load, Transform (ELT) processes.

  • Explain batch vs concurrent modes of execution.

  • Implement ETL workflow through bash and Python functions.

  • Describe data pipeline components, processes, tools, and technologies.

Skills you'll gain

Category: Transaction Processing
Category: Databases
Category: Data Analysis
Category: Data Manipulation
Category: Cloud Databases
Category: Query Languages
Category: Relational Databases
Category: SQL
Category: Database Design
Category: Database Management
Category: Relational Database Management System (RDBMS)
Category: Jupyter
Category: Pandas (Python Package)
Category: Jupyter notebooks
Category: Stored Procedure
Category: Python Programming
Data Warehouse Fundamentals

Data Warehouse Fundamentals

Course 415 hours

What you'll learn

  • Job-ready data warehousing skills in just 6 weeks, supported by practical experience and an IBM credential.

  • Design and populate a data warehouse, and model and query data using CUBE, ROLLUP, and materialized views.

  • Identify popular data analytics and business intelligence tools and vendors and create data visualizations using IBM Cognos Analytics.

  • How to design and load data into a data warehouse, write aggregation queries, create materialized query tables, and create an analytics dashboard.

Skills you'll gain

Category: Data Analysis
Category: IBM Cognos Analytics
Category: Looker (Software)
Category: Dashboards
Category: Business Intelligence
Category: Analytics
Category: Data Presentation
Category: Google Looker Studio
Category: Business Intelligence Software
Category: Interactive Data Visualization
Category: Data Visualization
Category: Dashboard
Category: Data Visualization Software

What you'll learn

  • Explore the purpose of analytics and Business Intelligence (BI) tools

  • Discover the capabilities of IBM Cognos Analytics and Google Looker Studio

  • Showcase your proficiency in analyzing DB2 data with IBM Cognos Analytics

  • Create and share interactive dashboards using IBM Cognos Analytics and Google Looker Studio

Skills you'll gain

Category: Star Schemas
Category: Data Validation
Category: Snowflake Schemas
Category: Query Languages
Category: Data Warehousing
Category: Data Architecture
Category: Data Marts
Category: Extract, Transform, Load
Category: Rollups
Category: SQL
Category: Star Schema
Category: Data Cleansing
Category: Database Design
Category: Data Mart
Category: Data Quality
Category: IBM DB2
Category: Data Lakes
Category: Data Modeling
Category: PostgreSQL
Category: Cubes
Category: Data Integration
Category: Snowflake Schema

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Instructors

IBM Skills Network Team
IBM
67 Courses1,232,858 learners
Shubhra Das
7 Courses22,923 learners

Offered by

IBM

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Frequently asked questions

¹ Median salary and job opening data are sourced from Lightcast™ Job Postings Report. Content Creator, Machine Learning Engineer and Salesforce Development Representative (1/1/2024 - 12/31/2024) All other job roles (4/1/2024 - 4/1/2025)