BI Foundations with SQL, ETL and Data Warehousing Specialization

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.

Instructors: IBM Skills Network Team

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5 course series

Get in-depth knowledge of a subject

4.6

(387 reviews)

Beginner level

No prior experience required

2 months to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 course series

Get in-depth knowledge of a subject

4.6

(387 reviews)

Beginner level

No prior experience required

2 months to complete

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

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

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Specialization - 5 course series

The job market for business intelligence (BI) analysts is expected to grow by23 percent from 2021 to 2031 (US Bureau of Labor Statistics). This IBM specialization gives you sought-after skills employers look for when recruiting for a BI analyst.

BI analysts gather, clean, and analyze key business data to find patterns and insights that aid business decision-making.

During this specialization, you’ll learn the basics of SQL, focusing on how to query relational databases using this popular and powerful language. You’ll use essential Linux commands to create basic shell scripts. Plus, you’ll learn how to build and automate ETL, ELT, and data pipelines using BASH scripts, Apache Airflow, and Apache Kafka.

You’ll discover why companies use data lakes and data marts, and work with adata warehouse. Plus, you’ll dive into the rewarding aspect of BI, creating interactive reports and dashboards so you can derive insights from data in your warehouse.

Additionally, you’ll gain valuable hands-on practice employing real-world tools used by data professionals. Each course has numerous hands-on labs and includes a project, which gives you plenty to talk about in interviews.

When you complete the full program, you’ll have a shareableportfolio of projects and a Specialization certificate for your resume and LinkedIn profile.

Get started on an in-demand business intelligence role. Enroll today.

Applied Learning Project

Using hands-on labs and course projects hosted in cloud-based environments, you’ll gain job-ready experience with the following real-world tools and tasks:

Writing SQL queries and creating joins using PostgreSQL, MySQL, and DB2 databases
Running Linux commands and pipes, creating shell scripts
Scheduling jobs using cron, building ETL and data pipelines, creating & monitoring Airflow DAGs, working with streaming data using Kafka
Designing data warehouses using star and snowflake schemas
Verifying data quality, loading staging, and production warehouses
Developing cubes, rollups, and materialized views/tables
Creating interactive reports and dashboards
Analyzing warehouse data using BI tools such as Cognos Analytics

Hands-on Introduction to Linux Commands and Shell Scripting

Course 114 hours

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: Shell Script

Category: Bash (Scripting Language)

Category: Operating Systems

Category: OS Process Management

Category: File Management

Category: Software Installation

Category: Linux Commands

Category: Network Protocols

Category: Linux Servers

Category: Automation

Category: Unix Commands

Category: Linux

Category: Unix Shell

Category: Scripting Languages

Category: Unix

Databases and SQL for Data Science with Python

Course 218 hours

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: Shell Script

Category: Performance Tuning

Category: Data Pipelines

Category: Real Time Data

Category: Data Processing

Category: Data Warehousing

Category: Data Migration

Category: Scalability

Category: Extract, Transform, Load

Category: Data Cleansing

Category: Apache Kafka

Category: Data Transformation

Category: Big Data

Category: Data Integration

Category: Apache Airflow

ETL and Data Pipelines with Shell, Airflow and Kafka

Course 317 hours

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: Jupyter

Category: Data Analysis

Category: Pandas (Python Package)

Category: Data Manipulation

Category: Query Languages

Category: Relational Databases

Category: Stored Procedure

Category: Python Programming

Category: SQL

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: Analytics

Category: Data Presentation

Category: IBM Cognos Analytics

Category: Business Intelligence Software

Category: Interactive Data Visualization

Category: Looker (Software)

Category: Data Visualization

Category: Business Intelligence

Category: Dashboard

Category: Data Visualization Software

BI Dashboards with IBM Cognos Analytics and Google Looker

Course 511 hours

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: Data Validation

Category: Query Languages

Category: Data Warehousing

Category: Data Architecture

Category: Extract, Transform, Load

Category: SQL

Category: Star Schema

Category: Data Cleansing

Category: Database Design

Category: Data Mart

Category: Data Quality

Category: IBM DB2

Category: Data Lakes

Category: PostgreSQL

Category: Data Modeling

Category: Data Integration

Category: Snowflake Schema

Category: Database Systems

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

IBM Skills Network Team

IBM

84 Courses1,315,654 learners

Shubhra Das

7 Courses31,307 learners

Offered by

IBM

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Frequently asked questions

The specialization is self-paced and requires 36-48 hours of effort to complete. Learners taking the course part-time e.g. 3-4 hours per week can complete in 3-4 months. Learners taking the courses full-time can complete considerably faster.

Basic computer literacy, some data literacy, and a passion to self-learn online are the only pre-requisites. No prior database or data warehouse skills required although some learners may benefit from a little programming experience.

It is highly recommended the courses be taken in the order they are listed as later courses build on concepts taught in previous ones.

Upon completing this specialization you will be able to:

List and execute commonly used Linux/Unix commands
Create pipes, shell scripts and schedule cron jobs
Query relational databases using SQL and perform CRUD operations
Filter, ORDER, aggregate and JOIN data in tables
Automate ETL and ELT tasks using BASH scripts
Build batch and streaming data pipelines with Apache Airflow and Kafka
Differentiate between Data Lakes, Data Marts and Enterprise Data Warehouses (EDW)
Design Data Warehouses, load staging areas, verify data quality
Create cubes, rollups and summary/materialized views/MQTs
Analyze warehouse data using reports and interactive dashboards
Work hands-on with real tools including Linux, Db2, MySQL, PostgreSQL, Airflow, Kafka, Cognos Analytics

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.