Introduction to Data Analysis

This course is already delivered, please contact us for the next available session tel:+357 22 44 14 92
Course Outline in PDF


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.

Who Should Attend:

Anyone involved in operations, project management, business analysis, or management, who needs an introduction to Data Analysis, would benefit from this class. This training course is perfect for:

•Business Analyst, Business Systems Analyst, CBAP®, CCBA®
•Systems, Operations Research, Marketing, and other Analysts
•Project Manager, Program Manager, Team Leader, PMP®, CAPM®
•Data Modelers and Administrators, DBAs
•IT Staff, Manager, Director, VP
•Finance Staff, Manager, Director, VP
•Operations Analyst, Supervisor, Manager, Director, VP
•External Consultants
•Risk Managers, Operations Risk Professionals
•Process Improvement, Audit, Internal Consultants and Staff
•Executives 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
•Senior Staff who make or recommend decisions to executives

At Course Completion:

After completing this course, students will be able to:
•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.


Module 1: The Course

•Course Expectations
•Agile & Integrated (A&I™) set of PMPower™ Tools and Best Practices
•References & Resources
•Practice Sessions

Module 2: Introduction to Data Analysis and Analytics

•Definition and history
•Current Technology Environment and the growing availability of data
•Role of the Business Analyst and Data Analyst
•Applications for gaining competitive advantages
•Practice Sessions

Module 3: Application of Probability and Probability Distributions

•Key concepts and essentials
•The Normal Distribution
•Many business distributions are nowhere near normal… Constraints!
•Establishing Confidence Intervals
•Practice Sessions

Module 4: Introduction to Data Mining and Data Warehousing

•Data Mining concepts and application
•Introduction to application benefits of Data Warehousing
•Practice Sessions

Module 5: Describing Information Needs

•Identify operational and executive information classes
•Executive Information Needs and the Balanced Scorecard
•Pivot Tables in Excel
•Tracking and Managing Business Process Performance
•Practice Sessions

Module 6: Data Exploration Concepts and Formulas

•Basic Concepts
•Descriptive measures of a sample
•Establishing and Analysing Correlation among different Variables
•Explanation of Variance
•Practice Sessions

Module 7: Introduction to Risk Management

•Uncertainty & Risk Analysis
•Assessing Your Organization Risk Culture and level of Risk Tolerance
•Identifying, Describing, Ranking, Prioritizing, and Controlling Risks
•When to use Quantitative Risk Analysis
•Important Risk Management Best Practices
•Practice Sessions

Module 8: Forecasting

•Forecasting Methods and Models
•Time Series Analysis
•Establishing Trends and Business Cycles (i.e. seasonality) and Confidence Limits
•Selecting Independent Variables for Predictive Models including Regression techniques
•Practice Sessions


•Data Analysis and Analytics
•Probability & Distributions
•Data Mining, Data Warehousing, Need for Information
•Statistic Inference, Forecasting, & Decision Support
•Next Steps Options
•Practice Sessions

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