Introduction to Data Analysis [GK1076]

OVERVIEW

Organizations need to make business decisions more quickly and accurately than ever before. Basing these decisions on data and best practice analysis techniques and less on gut feel or "the way we have always done things" is how today's corporate management is demanding information. A solid foundation of data analysis for business decision making is a critical skill you should have regardless of whether your motive is to obtain or sustain a competitive advantage or simply better steward your resources to serve customers.

In this course, you will learn to use data analytics to create actionable recommendations, as well as identify and manage opportunities where data-based decisions can be used to change the way you do business.

Please note: Exercises in this course are not compatible with Excel in a web browser. Please make sure you have a version of Excel locally downloaded on your computer or access to Excel via Microsoft 365.

• 14 PMI PDU Credits, 17 NASBA CPE Credits

OBJECTIVES

• Learn the terms, jargon, and impact of business intelligence and data analytics.
• Gain knowledge of the scope and application of data analysis.
• Understand the impact of analytics on gaining competitive advantage and decision support.
• Explore ways to measure the performance of and improvement opportunities for business processes.
• Be able to describe the need for tracking and identifying the root causes of deviation or failure.
• Learn the basic principles, properties, and application of probability theory and the normal distribution.
• Introduction to different methods for summarizing information and presenting results including charts.
• Learn about statistical inference and drawing conclusions about the population.
• Learn about sample sizes and confidence intervals, and how they influence the accuracy of your analysis.
• Learn about forecasting, including introduction to simple linear regression analysis.
• Gain knowledge to interpret your results and draw sound and relevant conclusions on business.
• Explore different methods and algorithms for forecasting future results and to reduce current and future risk.
• Be awarded PMI® Approved PDU®s, IIBA® Approved CDU®s, or other continued education credits.
• Refresh your process improvement and analysis skills.
• Learn where powerful reference material exists and how to leverage to enhance your decision-making.

AUDIENCE

Anyone involved in operations, project management, business analysis, or management who needs an introduction to data analysis, would benefit from this class. Please note: Exercises in this course are not compatible with Excel in a web browser. Please make sure you have a version of Excel locally downloaded on your computer or access to Excel via Microsoft 365.

Professionals who may benefit include:

• Business Analyst, Business Systems Analyst, Staff Analyst
• Those interested in CBAP®, CCBA®®, or other business analysis certifications
• Systems, Operations Research, Marketing, and other Analysts
• Project Manager, Team Leads, Project Leads, Project Assistants, Project Coordinators
• Those interested in PMP®, CAPM®, or other project management certifications
• Program Managers, Portfolio Managers, Project Management Office (PMO) staff
• Data Modelers and Administrators, DBAs
• Technical & other Subject Matter Experts (SMEs)
• IT Staff, Manager, VPs
• Finance Staff, Manager
• Operations Analyst, Supervisor
• External and Internal Consultants
• Risk Managers, Operations Risk Professionals
• Operations Managers, Line Managers, Operations Staff
• Process Improvement, Compliance, Audit, & other Governance Staff
• Thought Leaders, Transformation & Change Champions, Change Manager
• Executives, Directors, & other senior staff exploring cost reduction and process improvement options
• Executive and Administrative Assistants and Coordinators
• Job seekers and those who want to show dedication to data analysis and process improvement
• Leaders at all levels who wish to increase their Data Analysis capabilities

CERTIFICATION

CONTENT

Day 1

• Introduction to Data Analysis and Analytics
• Application of Probability and Probability Distributions
• Introduction to Data Mining and Warehousing
• Describing Information Needs

 Day 2

• Data Exploration Concepts and Formulas
• Introduction to Risk Management
• Forecasting
• Review
• Additional Resources and Exercises