Glossary.
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.
Planning
Annual Budgets
Forecasting
Revenue and Expense Projections
Inventory Planning
Analysis
Statistical Analysis of Data
Product/Customer Profitability
Probability Simulations
Machine Learning Algorithms
Reporting
Data Visualisation
Performance Dashboards
Automate Reporting Processes
Planning and Analysis
Build models of future operations and communicate your plan. Read more about this on our blog.
Reporting
Communicating information to the right people who can act on it at the right time. Read more about this on our blog.
The Software
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
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.
VBA
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.
MS Access
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..
Python
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
Simulation
Procedure that relies on random numbers to model real world outcomes. It can be used to estimate probabilities of complex real world events.