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Introduction to Data Analysis - Online

Course Code: STTA DATALYTICS
Length: 3 Days
Tuition: $1,495.00
Official

Schedule for this Course

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Course Description:

PMI: 14 PDUs

Data Analysis skills are required for many roles including analysts, subject matter experts, managers, and senior staff, who need to know the fundamentals of Business Data Analysis.

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.

This course provides many of the common data analysis tools used to gather, analyze and adapt your data to feed business decisions. You do not need heavy Excel or data analysis experience. This course includes introductory exercises on Excel add-ins, standard deviation, random sampling, and an introduction to pivot tables and charts. These exercises will show you how to effectively demonstrate basic data analysis functions and reporting in Excel or Google Spreadsheets. We will simplify math jargon and complex symbols and equations to concentrate on what your data can tell you and your organization. In addition, you will learn how to present to those executives, managers and subject matter experts who need to quickly make decisions that drive your organization.

We take time for each attendee to discuss their own data analysis questions and challenges and how they impact the day-to-day operations in their organization. We will discuss how other businesses, non-profits and agencies get value from data analysis and the tools they use to gather data. These tools include project management, risk management, document management, business analysis, data modeling, data reporting and more.

This course is packed full of instructional discussion and materials complemented by carefully chosen videos, examination of industry materials, proven best practices, and exercises in which the participants will gain insight into the practical application of the material. Be prepared to discuss and analyze some of your own challenges with identifying and quantifying the risks associated with decision making and forecasting future results. The course will provide insight into the future of analytics and the changing roles of those performing roles such as Business Analyst, Operations Analyst, Project Manager, Department or Division Manager, and IT functions. You will understand steps needed to implement a data analysis plan for your organization and begin your plan during class.

Analyze Business Problems down to Root Causes

In addition to providing the participants the opportunity to learn and apply the needed concepts, you will apply your acquired knowledge and skills in your real business scenarios to improve processes and applications. The measure of performance for this program consists of the following elements:

  • Learn the essential techniques and methodologies used to gather and assess data
  • Learn how to identify your real problems based on established qualitative and quantitative models and to enhance the accuracy in communicating real causes of performance deviations
  • Identify, quantify, and reduce uncertainty in making your decisions and in forecasting future events
  • Provide the foundation for the identification and documentation of the data requirements of the business
  • Support key management decisions by identifying significant trends and correlation between business results and controllable and uncontrollable variables
  • Be better prepared to communicate reasons to use data analysis techniques, strengths and weaknesses of each, and your recommendations based on sound data analysis principles
  • Gain the knowledge of skills and knowledge to establish business process performance metrics and the mechanisms to track business process performance
  • Present your draft plan for adoption of Data Analysis processes to the class

Practice Real-World Tools and Techniques for Immediate Application

Overall goals of this program include participants acquiring the foundation of required knowledge of probability theory and gain skills in the basic business analysis, data management, and statistical analysis techniques. Participants will better be able to analyze operational data to support the information and functional needs of the organization. This overall goal is achieved by a combination of lecture, videos, outside references, discussions, and exercises. The exercises will reinforce the key concepts and also will address the practical application of these concepts and techniques in different business situations. The overall learning objectives can be broken down into the following topics:

  • Be better prepared to communicate reasons to use data analysis techniques, strengths and weaknesses of each, and your recommendations based on sound data analysis principles
  • Learn the scope and impact of applying qualitative and quantitative methods to the analysis of data
  • Gain knowledge of the basic concepts of probability theory and statistical techniques including forecasting
  • Learn and use the Data Analysis & Results set of PMPower™ Tools for Data Analysis and Business Transformation
  • Support key management decisions by identifying significant trends and correlation between business results and controllable and uncontrollable variables
  • Gain the knowledge of skills and knowledge to establish business process performance metrics and the mechanisms to track business process performance

In Class Individual and Group Exercises

Practical and realistic discussion, analysis, hands-on exercises, and other practices will allow the participant to apply the foundations of qualitative and quantitative business analysis. The participants are exposed to basic spreadsheet analysis functionality. Participants will learn to analyze realistic business situations to select and apply the appropriate methods and tools to draw relevant conclusions. Participants will learn the value of analytics in supporting decision-making processes and the management and controls of business processes. Exercises will be flexible, and will be tailored to the needs of Virtual or on-site deliveries.

15 Benefits of Attending This Training Course

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

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

Prerequisites

n/a

Course Outline:

1. The Course

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

Practice Sessions – Individuals prepare a brief Challenges & Interests List. We will all introduce ourselves and the instructor will consolidate and standardize terms for our Challenges ? Interests List used to further tailor the delivery. The group will debrief on areas of interest and if needed take on homework to research topics and report to class 2nd day.

2. Introduction to Data Analysis and Analytics
This purpose of this module is to review the history and evolution of the field of business intelligence and the role of data analysis. We introduce the term analytics and its relevance in gaining a competitive advantage by exploring a number of successful applications.

  • 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
    • Fact based decision making
    • Process tracking and control

Practice Sessions – Individuals prepare a brief addition to their job description to cover their new duties using data analysis. A group exercise will review each job description portion.

3. Application of Probability and Probability Distributions
Effective decision-making requires a determination and assessment of the relative or expected value and uncertainty of future events. Better decisions come from knowledge of the probable impact of different controllable and uncontrollable variables. Probability theory provides the foundation for determining and taking into consideration the uncertainty and risks inherent in making decisions.

  • Key concepts and essentials
    • Decision making under uncertainty
    • Random Variables
    • Population and Samples
  • The Normal Distribution
  • Many business distributions are nowhere near normal… Constraints!
  • Establishing Confidence Intervals

Practice Sessions - Use spreadsheet functions to estimate parameters of a given probability distribution. From these results, establish the expected value and standard deviation.

4. Introduction to Data Mining and Data Warehousing

This module outlines the scope of the field of business intelligence and introduces two topics that compliment and expand the concepts of analytics to a full implementation.

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

Practice Sessions – Individuals discuss what data mining and data warehousing practices ongoing in their areas. Best practices and tools are noted where they are used.

5. Describing Information Needs

This module covers the background for and best practices of information requirements of various levels of management needed to make decisions and review operational performance. Application of analytics is a key part of building systems to effectively provide the information required by all levels of management.

  • Identify operational and executive information classes
    • Modeling Key Decisions and the Needs for Information
    • Describing Key business Transactions and Documents
    • Map Information Needs to underlying Data
  • Executive Information Needs and the Balanced Scorecard
  • Pivot Tables in Excel
  • Tracking and Managing Business Process Performance
    • Selecting Measures and Targets
    • Measuring Performance and finding Performance Gaps
    • Root Cause Analysis

Practice Sessions – Students work with a Pivot table Exercise to gain basic skills with this Excel.

6. Data Exploration Concepts and Formulas

This module discusses how to apply a number of tools to extract information from a set of observations by calculating key parameters and summarizing the data in graphs and tables. The relevance and validity of the Sample information extracted from a sample is confirmed by making inferences that apply to the whole population.

  • Basic Concepts
    • Types of Variables
    • Selecting Dependent and Independent Variables
    • Sample vs. Population
  • Descriptive measures of a sample
    • Key Sample Parameters
    • Variability
    • Sampling Distributions
    • Sample Size
  • Histograms
  • Establishing and Analyzing Correlation among different Variables
  • Explanation of Variance

Practice Sessions – Students practice using the "rand()" function in Excel.

7. Introduction to Risk Management

This module outlines generally accepted Risk Management processes and introduces best practices that compliment and expand traditional Risk Management. We provide a sound process for qualitative Risk Management. We discuss how and when to move from qualitative to quantitative 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 - Individuals outline their current and desired approach to Risk Analysis as it relates to the course material. Optional exercise addresses a specific scenario Risk Analysis practice.

8. Forecasting

Decision-making depends on forecasting of future events and results. Accurate forecasting depends on discovering patterns in historical data and on the assumption that those patterns will hold over time. Optimal forecast methods rely on the historical patterns and the knowledge provided by subject matter experts and even sometimes on publicly available data. Different methods and techniques can be used including the need for incorporating the input from subject matter experts.

  • Forecasting Methods and Models
    • History of Forecasting
    • Long and Short Term Forecasts
    • Heuristics
  • 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 - Individuals outline their current and desired approach to Forecasting as it relates to the course material.

9. Review

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

Practice Sessions – ABQ! (Adopt, Bright Spots, Quit) – Declare your intent topics from this course in your work or volunteer work in three ways: ADOPT What you will start to do; BRIGHT SPOTS What you will continue to do that has been proven to work in your organization; QUIT What you will stop doing.

10. Additional Resources and Exercises

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