BI Foundations with SQL, ETL and Data Warehousing Specialization

BI Foundations with SQL, ETL and Data Warehousing Specialization

Name: BI Foundations with SQL, ETL and Data Warehousing
Rating: 4.625 (333 reviews)

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

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

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Taught in English

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Master a subject or tool with hands-on projects
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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 hours4.7 (1,334 ratings)

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.

Databases and SQL for Data Science with Python

Course 220 hours4.7 (20,534 ratings)

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.

ETL and Data Pipelines with Shell, Airflow and Kafka

Course 317 hours4.5 (359 ratings)

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.

Data Warehouse Fundamentals

Course 415 hours4.4 (187 ratings)

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.

BI Dashboards with IBM Cognos Analytics and Google Looker

Course 511 hours4.5 (12 ratings)

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