Financial Analytics in RStudio: Identify Profit Drivers

Financial Analytics in RStudio: Identify Profit Drivers

Financial Analytics in RStudio: Identify Profit Drivers Taught in English Instructor: Moses Gummadi Included with • Learn more Guided Project Learn, practice, and apply job-ready skills with expert guidance Intermediate level Recommended experience Close Recommended experience Intermediate level Basic R language (variables, vectors, data frames) Familiarity with RStudio interface Elementary knowledge of Operational Finance. OK

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Description

Financial Analytics in RStudio: Identify Profit Drivers

In today’s fast-paced business environment, identifying the key drivers of profitability is crucial for businesses to thrive and remain competitive. Financial analytics plays a crucial role in this process by providing companies with valuable insights into their financial performance and profitability. One of the leading tools for conducting financial analytics is RStudio, a powerful open-source platform for statistical computing and data analysis.

RStudio offers a wide range of features and tools that can help businesses analyze their financial data and identify the key drivers of profitability. By leveraging the capabilities of RStudio, businesses can gain a deeper understanding of their financial performance and make informed decisions to improve profitability.

One of the key advantages of using RStudio for financial analytics is its ability to process large volumes of financial data quickly and

Financial Analytics in RStudio: Identify Profit Drivers

Taught in English

Moses Gummadi

Instructor: Moses Gummadi

Included with Coursera Plus

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Intermediate level

Recommended experience

2 hours
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning

What you’ll learn

  • Import operational and financial raw data, and perform exploratory analysis of operational and financial performance.

  • Analyse the cost components, calculate the Operating Margin (OM) by period, and determine the factors driving the OM.

  • Calculate OM variance to plan & variance between periods. Determine factors driving OM variance. Plot OM waterfall, and identify corrective actions.

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