Business Data Management and Communication Specialization

In this course, you will learn foundations of financial accounting information. You will start your journey with a general overview of what financial accounting information is and the main financial statements. You will then learn how to code financial transactions in financial accounting language. In the meantime, you will learn about the most important concept in contemporary financial accounting: accrual accounting. You will then critically analyze how firms recognize revenues. Finally, you will finish the course with an analysis of accounting for short-term assets where you will go into detail on how firms account for accounts receivables and inventories.

Upon successful completion of this course, you will be able to: • Understand main financial statements and the financial information they provide • Write a financial transaction in financial accounting language and understand how this impacts main financial statements • Understand how accrual accounting and fundamental accounting concepts work • Understand revenue recognition principles and how they impact main financial statements • Account for accounts receivables and inventories. This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu.

In this course, you will explore advanced topics in financial accounting. You will start your journey with accounting for assets with more than one-year life. You will learn in detail how firms account for fixed assets. You will then move to financing of assets and discuss accounting for liabilities. The course will continue with an in-depth exploration of shareholders’ equity. Finally, you will critically evaluate preparation, components, and analysis of cash flows statement.

Upon successful completion of this course, you will be able to: • Account for fixed assets • Understand accounting for liabilities • Evaluate shareholders’ equity section of a balance sheet • Understand preparation and information provided by cash flows statement This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu.

This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.

Nearly every aspect of business is affected by data analytics. For businesses to capitalize on data analytics, they need leaders who understand the business analytic workflow. This course addresses the human skills gap by providing a foundational set of data processing skills that can be applied to many business settings.

In this course you will use a data analytic language, R, to efficiently prepare business data for analytic tools such as algorithms and visualizations. Cleaning, transforming, aggregating, and reshaping data is a critical, but inconspicuous step in the business analytic workflow. As you learn how to use R to prepare data for analysis you will gain experience using RStudio, a powerful integrated development environment (IDE), that has many built-in features that simplify coding with R. As you learn about the business analytic workflow you will also consider the interplay between business principles and data analytics. Specifically, you will explore how delegation, control, and feasibility influence the way in which data is processed. You will also be introduced to examples of business problems that can be solved with data automation and analytics, and methods for communicating data analytic results that do not require copying and pasting from one platform to another.