Practical Data Integration

Course Available
2 Units
Online Fixed-Date

Course Description

Practice Data Integration Techniques for Informed Decision Making

Want to learn how to transform raw data into actionable insights that drive meaningful decisions? Our Practical Data Integration course rounds out your career preparation by delving into the critical phase of the data engineering pipeline, empowering students with the skills needed to ingest data in scalable and efficient ways. Master the art of optimization as you explore various techniques in data transformation, connections, and staging. By the end of the course, you'll not only possess the essential knowledge to refine and enhance data, but also the expertise to seamlessly turn it into a valuable service for analysts, business intelligence professionals, data scientists, and your fellow data engineers. This is the third course in the Practical Data Engineering Certificate program. Before enrolling, students must complete Data Engineering Fundamentals (PDE-X800) and Practical Data Extraction (PDE-X801).

Course Details

Number of Units: 2.0 graduate level extension credit(s) in semester hours

Who Should Attend: Our Practical Data Extraction courses provide continuing education for the following:

  • Data Experts: Are you a data analyst, business analyst, data scientist, computer scientist, machine learning engineer, or AI virtuoso? Our program is your gateway to mastering data engineering principles and wielding the essential tools of the trade.
  • Career Changers: If you hold a college degree or are a full-time student looking to pivot your studies, our program offers the perfect opportunity to foray into data engineering.
  • Passionate Professionals: If you're enthusiastic about diving deep into practical data engineering topics and want to amplify your professional prowess, our Practical Data Engineering Certificate is your ticket to success.
  • Trailblazers in the Making: Whether you're a seasoned pro or a fresh enthusiast, if you aspire to enter the dynamic field of data engineering and architecture, this program will help illuminate your path forward.

Technical Requirements

Course Options

Course Date Units Price
PDE-X802 – 003 07 May 202424 Jun 2024 2 $1375

Practical Data Integration

07 May 202424 Jun 2024
2
$1375

Practical Data Engineering Certificate – Bundle and save 10% when you enroll in all four courses (must add all 4 courses in one transaction for discount):

  • PDE-X800-Data Engineering Fundamentals
  • PDE-X801-Practical Data Extraction
  • PDE-X802-Practical Data Integration
  • PDE-X803-Practical Data Engineering Capstone

To apply credit, select the checkbox and select  "BUS – PDE Bundle and Save 10%" for a discount on each course.
**Only one discount can be applied per course. Discount does not apply to certificate fee. **

Online Fixed-Date
Mahdi Ebrahimi

Once you have enrolled in your course, log in to your account to access the course Welcome Letter, which includes directions on how to access the New Student Orientation and your online course.

PDE-X802 – 004 03 Sep 202421 Oct 2024 2 $1375

Practical Data Integration

03 Sep 202421 Oct 2024
2
$1375

Practical Data Engineering Certificate – Bundle and save 10% when you enroll in all four courses (must add all 4 courses in one transaction for discount):

  • PDE-X800-Data Engineering Fundamentals
  • PDE-X801-Practical Data Extraction
  • PDE-X802-Practical Data Integration
  • PDE-X803-Practical Data Engineering Capstone

To apply credit, select the checkbox and select  "BUS – PDE Bundle and Save 10%" for a discount on each course.
**Only one discount can be applied per course. Discount does not apply to certificate fee. **

Online Fixed-Date
Federico Giacomelli

Once you have enrolled in your course, log in to your account to access the course Welcome Letter, which includes directions on how to access the New Student Orientation and your online course.

What You Will Learn

Current or aspiring data engineers who complete our series of professional engineering courses can expect to:

  • Understand the fundamentals of data architecture, data mastering, and data staging
  • Learn the best practices when transforming data and selecting table types
  • Discover the ethical requirements around security, data privacy, data governance, and documentation

Instructors

Professional development courses offered by the University of San Diego’s Division of Professional & Continuing Education are taught by faculty that possess a depth and breadth of academic and real-world professional experience.

Why USD?

The Professional and Continuing Education program nurtures key partnerships on the local, national, and international level. The goal is to better serve working professionals who seek to enhance or build their careers and help achieve their highest value and potential. Contact us today to learn more.

Informative Stats and Facts

600+

High-quality, career-building courses to choose from

50+

In-depth, innovative, and relevant topics

25+

Career advancing certificates

Learning Method Information

Courses offer a convenient, yet rigorous style of learning that allows you to structure your education to suit your schedule while keeping you on pace toward achieving your educational.

Online Fixed-Date

Online Fixed-Date: Online fixed-date courses offer a convenient, yet rigorous style of learning that enables you to collaborate with your instructor and other students in a shared, online learning environment. These courses have fixed start and finish dates, but as an online student you will have 24/7 online access to your classroom assignments, syllabus and course resources. Our online fixed-date courses allow you to work on your assignments anytime, although you are required to complete the assignments by specific dates.

How is the learning structured? In an online fixed-date course, you and your classmates will proceed through the curriculum together, collaborating in a shared learning experience. Each online fixed-date course is asynchronous, meaning that you can work on your assignments anytime, although required to complete the assignments by specific dates. The course is designed with learning modules where all of the content is grouped into weekly assignments. Each module covers one or more topics. Within each of the learning modules, you can expect the following components:

  • Module introduction that outlines what you can expect to learn in the module.
  • Required readings (textbook, articles, journals, etc.) and presentations (audio and/or video).
  • Assignments with due dates (which may include: written assignments, journal entries, research, blogs, etc.) based on the readings and presentations.
  • Discussion forum where you answer prompts from the instructor and interact with your classmates.
  • Module conclusion to review the topics and what you should have learned.
  • Typically, there is a final project, paper, or exam due in the last module that culminates all of the topics covered in each of the learning modules. You’ll find that the design of the learning modules has a rhythm to help you manage your time in the course.

Frequently Asked Questions

How long does it take to complete the Practical Data Integration course?

Each online, fixed-date course is seven weeks long. Students are required to complete certain assignments by specific dates, but have 24/7 access to coursework to complete assignments on a schedule that is convenient for them.

What background or prerequisites do I need?

Students should have completed PDE-X800 Data Engineering Fundamentals and PDE-X801 Practical Data Extraction prior to enrolling in PDE-X802 Practical Data Integration. However, no prior professional experience in data engineering is required.

Can I earn credit for this course?

Practical Data Integration is worth two academic or Continuing Education Units (CEUs). It is part of the Practical Data Engineering Certificate program.

What will I be able to do once I complete the course?

Upon successful completion of Practical Data Integration, you will have a fundamental understanding of data architecture, data mastering, data integration, and data staging, as well as the ethical requirements around security, data privacy, data governance, and documentation.