Data Analytics

Certificate Program

Modern business software produces mountains of data, and it's a professional’s job to examine it and draw meaningful conclusions. This Data Analytics certificate program and coursework will teach the fundamentals of quantitative analysis, so that trends can be understood from spreadsheets and converted into thoughtful business decisions.

This certificate in Data Analytics, offered by California State University, Long Beach (CSULB) in partnership with MindEdge, provides an overview of topics in statistics and their applications in a variety of fields. This certificate will present the basics of quantitative analysis and its increasing use in today's professional landscape. Learners are exposed to quantitative decision-making tools and techniques, which tie into real-world case studies. Each course in this certificate utilizes games, videos, interactive exercises, quizzes, real-world case studies, and other engaging content to ensure rapid mastery of the content as well as its direct application. Course videos and lessons focus on use of both Microsoft Excel and OpenOffice.

  • Current professionals working with data who want to learn new sklils and showcase knowledge to current or prospective employers
  • Working professionals in any industry who need to use data more frequently in their work
  • Those looking to obtain a job as a data analyst
  • This program is entirely online, in a self-paced instructor-facilitated format that allows learners to study at their own pace and on their own schedule.
  • The curriculum balances academic excellence with real-world practice, featuring text, video, interactivity, adaptive learning technology, quiz banks, and other features not available in a traditional textbook.
  • The Data Analytics certificate can be completed in an estimated 30 hours, with online access available for 365 days from the time of registration. This course is 3 CEUs. 
  • How to differentiate among various organizational performance measurements
  • The advantages and disadvantages of KPIs, Balanced Scorecard, and Net Promoter Score
  • Big Data and its current uses for analysis and future potential
  • Common analytics for business and quality improvement
  • Common analytics used in healthcare, education, and government
  • Fundamental concepts of measurement including levels, reliability and validity, errors, and information bias
  • Principles that help guide quality management activities
  •  Key fundamentals of probability and their real-world application

Data Analysis for Improving Organizational Performance

When using data analysis to improve organizational performance, it's vital to employ the tools that bring the data to life and keep people engaged in the process. Organizations in both the public and private sectors often use tools and frameworks to deliver the data, and the information the data might suggest, to their staff. This intermediate-level course will explain some of these measures and tools, describe some specific measurements, and explain the relationship between assessment and strategy. Summarizing the data with the correct tool can be the major factor in reaching staff and effecting changes that spur performance improvement.

Data Analysis in the Real World

How are data-driven decisions put into practice in the real world? How do these decisions differ when applied to different sectors, such as healthcare, education and government? This intermediate-level course will provide answers to these questions as well as recommendations for decision-making based on data analytics for each sector. The course will begin with an introduction to Big Data, then continue into a deeper dive on its implications within each sector. Industry case studies make the concepts applicable in the real world.

Introduction to Data Analysis

This course will introduce the different types of decisions made in an organizational setting, why quantitative analytics is important, and how data quality can affect decision-making. Since quantitative analytics is used in various settings, this intermediate-level course also offers insight into how research is used in different sectors. From a management perspective, the course highlights appropriate quantitative methods and ways to ensure quality and accuracy through research design.

Statistical Process Control

Statistical Process Control is all about boosting quality. Quality management can not only deliver value to customers and stakeholders, it can also enable data-driven decision-making that helps organizations gain a competitive advantage in the marketplace. This intermediate-level course will introduce the basics of quality management, explaining the difference between quality control and quality assurance, providing methods for application of analysis, and showing different applications of the Seven Basic Quality Tools. It all culminates in a brief case study, which illustrates the concepts covered.

Statistics as a Managerial Tool

Management today can require good instincts. However, instincts are not enough to manage the huge amounts of available data, and the complex variables of the business world. Statistics can help managers and leaders make sense of these complexities, support their assertions, and feel confident about when to take risks or when to play it safe. This intermediate-level course examines statistics as a managerial tool. It also looks at common graphical representations of data, and how these can be effective tools to explain situations and support persuasive arguments for a course of action.