Course

Course Summary
Credit Type:
Course
ACE ID:
BISK-0129
Organization's ID:
VIL85
Organization:
Bisk Education
Location:
Classroom-based
Length:
8 weeks (32 -- 48 hours)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Upper-Division Baccalaureate 3 Business Analytics or Information Technology
Description

Objective:

The course objective is to explore data structures as they relate to business intelligence, focusing on BI front end tools, data and technical architecture, data modeling, and success factors and constraints faced by IT teams.

Learning Outcomes:

  • Illustrate how data flows through from sources to reporting
  • Apply master data management models for customers, products, and transactions to real-world situations
  • Determine the advantages and disadvantages of ETL
  • Describe the significance of leadership buy-in
  • Discuss how to get people on board and involved with a BI project, ways to build and maintain momentum, and how to align and design the right incentives
  • Describe scorecards, dashboards, and key performance indicators (KPI)
  • Explain and list the eight phases of waterfall development methodology, the advantages and disadvantages, and describe how these phases can be applied to BI application development
  • Discuss the Agile software methodology and how it applies to a business intelligence application
  • Outline the three different types of online analytical processing (OLAP)
  • Discuss the definitions of data quality assessment and explain how to effectively perform data quality assessments
  • Outline the data modeling process, including defining requirements back-to-front and front-to-back
  • Identify the key components of CWM, along with the primary design considerations and critical design factors
  • Identify the four CoE phases
  • Explain what scalability is, and how to use load balancing to achieve scalability
  • Summarize when and why performance testing is done

General Topics:

  • Success factors and constraints, BI front end tool segments, data architecture and quality, data modeling, customer data management (CDM) and master data management (MDM), industry standards, creating a center of excellence, and technical architecture
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Case Studies
  • Discussion
  • Lectures

Methods of Assessment:

  • Examinations

Minimum Passing Score:

70%
Supplemental Materials