Online Mastering Data Management and Technology Course

8-Week Course

8 Continuing Education Units

50.75 PDUs

80 Military Clock Hours

About the Course

Building upon the foundation concepts of Essentials of Business Intelligence, this course explores more advanced topics including data modeling, securing business intelligence content, reporting and performance management. With case studies and exercises, you’ll gain real-world insight into all facets of business intelligence.

Prerequisites for this course:

Essentials of Business Intelligence

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Curriculum

8 Week Course

Week 1

Success Factors and Constraints

Describe the significance of leadership buy-in
Name the three key characteristics of a strong and active sponsor
Summarize ways to bridge the gap between business and IT
Discuss how to get people onboard and involved with your BI project, ways to build and maintain momentum and how to align and design the right incentives
Name and explain the five structured phases of change

Week 2

BI Front End Tool Segments

Describe scorecards, dashboards and key performance indicators (KPI)
Review waterfall methodologies as applied to BI programs and compare/contrast waterfall vs. Agile for BI program management
Discuss Agile program management methodologies and how they apply to business intelligence initiatives
Outline the three types of Online Analytical Processing (OLAP)
Discuss modern BI reporting capabilities

Week 3

Data Architecture and Quality

Provide data quality issues and ways data quality can be improved
Explain the differences between the top-down approach and the bottom-up approach to data quality
Discuss the definitions of data quality assessment and explain how to effectively perform data quality assessments
Illustrate how data flows through from sources to reporting
Differentiate real-time from right-time data

Week 4

Data Modeling

Illustrate star schema and snowflake schema design basics
Identify fact types and dimension types
Outline the data modeling process, including defining requirements back-to-front and front-to-back
Summarize when to create aggregate tables and why they appear in the data warehouse

Week 5

Customer Data Management (CDM) and Master Data Management (MDM)

Define Master Data Management (MDM), customer master data and product master data
Explain how customer master data and product master data are used, and provide the best practices for integrating each
Discuss why an MDM team is necessary as well as their roles and responsibilities
Analyze case studies in Master Data Management

Week 6

Industry Standards

Define middleware, identify the three forms and explain the uses of each
Summarize the meaning of ETL, explain how it works and when to use it
Discuss best practices in ETL processing

Week 7

Creating a Business Analytics Competency Center (BACC)

Define what a BACC is, why it is needed, its role and how to place it in an organization
Identify best practices for creating and managing a BACC
Analyze BACC case studies to investigate real-world competency center application

Week 8

Technical Architecture

Name the three tiers that support technical architecture and explain each tier’s purpose
Discuss best practices in cloud-based BI and MDM
Distinguish the differences between virtualization and traditional architecture
Explain what scalability is and how to use load balancing to achieve scalability
Summarize when and why performance testing is done

Learning Objectives

Skills Learned

Business Development Performance Analysis Agile Data Management Data Analysis Data Modeling

What You’ll Study

Data Architecture and Quality

Business Case for Improving Data Quality
Data Quality Assessment
Process Improvements, Source System Validation
Attribute Constraints, Profiling and Precision
Historical Data
Real Time vs. Right Time
Granularity for Analysis

Data Modeling

Dimension Types
Snowflake vs. Star
Fact Types
Aggregates
Process for Designing

CDM and MDM

Master Data Management (MDM)
Customer Master Data
Product Master Data
Other Types of Master Data
MDM Best Practices and Benefits
MDM Team Creation and Scope

BI Front-End Tool Segments

User Interfaces
Waterfall Development
Agile Methodology
The Different Types of Online Analytics Processing
Network Architecture
Maintaining Your BI Application

Industry Standards

Middleware (ODBC, ODBO, XMLA)
MDX
ETL
SQL Introduction
Common Warehouse Meta Model (CWM)
HTML

Creating a Business Analytics Competency Center (BACC)

BACC Review
Initialization
Define
Establish
Organize
Operate

Technical Architecture

Cloud-Based BI and MDM
Virtualization
Load Balancing
Performance Tuning
Online Analytical Processing (OLAP)

Success Factors and Constraints

Leadership
Business/IT Partnership
Business Alignment Incentives
Company Culture
Change Management

Related Certificate Programs

Business Intelligence Certificate

24 Weeks

3 Courses

$6,059

Learn how to turn data into actionable insights.

Certification Available

Who Should Register?

Whether you’re a strategic decision maker, project manager, business analyst, market researcher or IT professional, this course can provide you with a solid understanding of critical business intelligence topics. With subjects including best practices in data modeling, data architecture and performance management, you can gain the skills needed for success in today’s highly competitive global data analytics market.

Tuition & Payment

Total Course Cost

$2,295

Course offerings and associated prices are subject to change without prior notice. Pricing for multi-course certificate programs varies depending on course selection. View the Professional Education Catalog for more information on the courses and programs.

Payment Options

There are multiple ways to pay for your certificate program. Just let your enrollment representative know the choice that works best for you.