To make sure we're on the same page. Here is a glossary of some useful financial modelling and other terms. They have been used all around the site.
Types of Financial Modelling
Financial modelling can be broadly categorised into 3 types. Each of these have popular use cases.
Revenue and Expense Projections
Statistical Analysis of Data
Machine Learning Algorithms
Automate Reporting Processes
Planning and Analysis
Build models of future operations and communicate your plan. Read more about this on our blog.
Communicating information to the right people who can act on it at the right time. Read more about this on our blog.
When you're building financial models, you should look at the entire process the model falls into and use all the tools available to you. Not only in Excel. The idea is to use all the tools that are easily available to you.
Excel is the de facto king of financial model building. This has been the case for decades. It is probably the most widely used application in the world. It's popularity is founded on its ease of use for users of all levels.
Used to automate processes. Make them faster, more accurate and efficient. VBA works on the main MS Office programs and can be used like a "glue" to connect them all together.
To go from single user Excel solutions to multiple users. MS Access lets you build more data intensive projects with proper relational database functionality that is already included in in the MS Office suite of programs..
To scale up your data analysis. Python offers libraries that let you run statistical analysis and machine learning algorithms to your data. You can also build complete data products from extraction, analysis and reporting.
Other Terms and Concepts
Procedure that relies on random numbers to model real world outcomes. It can be used to estimate probabilities of complex real world events.