Course Description and Competencies

What to Expect

In this course, you will work through three modules of content. These modules are broken into smaller lessons. Throughout the course, you will be directed to learning resources such as readings, videos, and exercises. You will mainly access these resources through the use of links. A heading indicates each learning resource to make it easily identifiable. As you progress through the modules, lessons, and units of the course, complete the learning resources provided. Once you have completed the assignment as indicated, return to the course page and continue your progress.

In some cases, you may need to close or navigate back from a learning resource to continue on to the next portion of the course. It is recommended that you progress in this manner rather than continuing directly through the remainder of the learning resource, as some chapters or segments of the learning resource may not be required.

Prerequisites:

Cloud Databases (D607A) and Data Processing (D608A) are prerequisites for this course.

Course Competencies

This course covers the following competencies:

  • The learner explains the advantage of using a big data analytics solution. 
  • The learner proposes a large-scale data analytics solution to meet a business need.

Assessment

You will demonstrate competency through two performance-based assessments. The assessments provide an opportunity to demonstrate your mastery of the competencies in this course. You must achieve a ranking of Competent on each assessment to pass the course. You may attempt the assessment two times before additional support is necessary. If you require further attempts, please contact your Student Experience Team.

2 Final Projects
3 Competency Units

Course Outline

ModuleUpon completion of this module, you will be able to:
Advantages of Big Data
  • Assess an organizational need to implement big data strategies. 
  • Use different methods of data analysis. 
  • Promote the benefits of implementing big data strategies for specific datasets.
Large Scale Data Solutions
  • Assess an organizational need to implement big data strategies. 
  • Create data architectures, including databases, and large-scale processing systems. 
  • Develop data visualization models that map big data to graphical elements.
  • Estimate the frequency at which the data for big data is processed. 
Implementing Big Data Solutions
  • Ensure structure, accuracy, and quality of data. 
  • Develop data processing models, including sourcing, loading, transformation, and extraction. 
  • Deploy a system. 
  • Implement technologies for data analysis. 
  • Implement system architectures that meet requirements and adhere to industry standards. 
  • Conduct analytics on large datasets with MapReduce approaches.

Key Contacts

Certificate Connect
Check out this online community to take advantage of course resources, including videos and tips from your educators. You can ask and answer questions, provide feedback on your progress, and interact with fellow students. You will find this platform in the Student Resources section of the course. Log on and do some exploring!

Technical Support
If you encounter technical issues, be sure to contact the Help Desk. Just submit a Support Request for assistance.

Program Support
Do you have questions about your account? Student Support has answers. They can help with billing, switching courses, and other requests. You can contact them at (888) 320-0540 or support@academy.wgu.edu.

Accommodations

WGU provides compliant and accessible learning experiences. If you require accommodation, please contact us at the start of the course. You can email disability@academy.wgu.edu.

We are committed to ensuring that all students with disabilities have equal access to WGU's services and materials. We strive to use best practices for accessibility. Our goal is to conform to existing U.S. laws, including the Americans with Disabilities Act and Section 504 and Section 508 of the Rehabilitation Act.

Our learning management system (LMS) platform is Open edX. Open edX’s commitment to accessible content is published in their Website Accessibility Policy.