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Introduction to Data Analysis

  • Tuition USD $1,295
  • Reviews star_rate star_rate star_rate star_rate star_half 4425 Ratings
  • Course Code 1076
  • Duration 2 days
  • Available Formats Virtual, Classroom

Data Analysis is an ever-evolving discipline with lots of focus on new predictive modeling techniques coupled with rich analytical tools that keep increasing our capacity to handle big data. However, in order to chart a coherent path forward, it is necessary to understand where the discipline has come from since its inception.

The field of Business intelligence depends largely on Data analysis tools and techniques in order to inform effective decision-making. In fact, the disciplines are so intertwined that some often confuse the two. Therefore, we begin our introduction by examining the history of Business intelligence, its relationship to data analysis, and why the two are needed to help businesses deliver a complete assembly of their 'data puzzle'. This module also addresses some of the hurdles businesses face when dealing with data overload and suggests some possible solutions to the problem.

With the explosion of big data, businesses recognize there is a greater need for employing someone who is qualified to correctly analyze the data. In this module, we explore the qualifications for the data analyst as well as the analytic tools associated with the position. It is unfortunate that there is such a dearth of data analysts. With a projected shortage of 190,000 data science jobs into 2018, it is no wonder that businesses are scrambling to recruit talent.

Skills Gained

  • Learn the terms, jargon, and impact of business intelligence and data analytics.
  • Gain knowledge of the scope and application of data analysis.
  • 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.
  • Review the basic principles, properties, and application of Probability Theory.
  • Discuss data distribution including Central Tendency, Variance, Normal Distribution, and non-normal distributions.
  • Learn about Statistical Inference and drawing conclusions about a Data Population.
  • Learn about Forecasting, including introduction to simple Linear Regression analysis.
  • Learn about Sample Sizes and Confidence Intervals and Limits, and how they influence the accuracy of your analysis.
  • Explore different methods and easy algorithms for forecasting future results and to reduce current and future risk.

Who Can Benefit

Anyone involved in operations, project management, business analysis, or management who needs an introduction to Data Analysis, would benefit from this class:

  • 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 starr 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

Course Details

1. Course Introduction

  • Logistics, materials, and course expectations
  • Agile and integrated (A&I) set of tools and best practices
  • References and resources

2. Introduction to Data Analysis and Analytics

  • Definition and history
  • Current technology, the growing availability of data, and increasing challenges
  • Applications for gaining competitive advantages

3. Rethinking the Value and Usage of Data

  • The impact of vast volumes of available data especially for decision making
  • Data difficulties and limitations: ROI vs. effort/expense, incomplete and inconclusive data
  • Dealing with data uncertainty
  • Getting real value out of your data: The data continuum
  • Effective and responsible data ownership
  • Advantages and disadvantages of qualitative and quantitative data types
  • Solutions and best practices to transform the way your organization accesses and uses data
  • Organizing the entire organization's data for maximum efficiency using easily available tools
  • Taking advantage of the expertise of the entire organization

4. Introduction to Data Mining and Data Warehousing

  • Data Mining concepts and application
  • Application benefits of data warehousing

5. Data Distribution and Variance

  • Decision making under uncertainty
  • Probability
  • Data distribution
  • Variance
  • Standard deviation

6. Information Needs

  • Operational and executive information classes
  • Key functional transactions and documents
  • Map information needs to underlying data
  • Executive information needs and the balanced scorecard
  • Role of the business analyst and data analyst
  • How to use simple pivot tables in Excel or Google Sheets to analyze and present your data
  • Tracking and managing business process performance
  • Learning from data

7. Data Exploration Concepts and Methods

  • Basic concepts
  • Descriptive measures of a sample
  • Histograms
  • Statistical hypothesis and inference
  • Dependence and correlation
  • Moving beyond data and decision uncertainty - managing risk

8. Forecasting

  • Forecasting methods and models
  • Time series analysis
  • Linear regression
  • Establishing trends and business cycles (i.e., seasonality)
  • Selecting independent variables for predictive models including regression techniques

9. Review, Best Practices, and Next Steps

  • Data analysis and transformation
  • Best practices revisited
  • Next steps options

10. Course Closeout: Putting It All Together. The Value of Powerful Data

11. Additional Resources and Exercises

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals, and private on sites. View our group training page for more information.

Provided good amount of material and a great instructor to teach the material.

The training was good but needed the basic skills of maximo before getting deep in the configuration of it.

It would be better if the classroom had two power point screens so the instructor could have two screens shown to the class at the same time to reduce confusion switching back and forth

Although there seemed to be too many links for the course, everything worked smoothly.

Overall ExitCertified is a great training provider and the remote learning is as effective as in person.

15 options available

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  • Oct 4, 2021 Oct 5, 2021 (2 days)
    Location
    Virtual
    Language
    English
    Time
    08:30 16:30 EST
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  • Nov 15, 2021 Nov 16, 2021 (2 days)
    Location
    Virtual
    Language
    English
    Time
    08:30 16:30 EST
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    EXTRA DATES ADDED - SAVE on this course -  Promo Code: SUMMER500
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