What Software Do Financial Analysts Use?

Financial Analysts rely on a range of software, applications, tools, and programming languages to perform their jobs. Although the tools you’ll use in finance will likely depend on your industry focus and particular role within your organization, some common tools used by most Financial Analysts are Microsoft Excel, SQL, Python, and Tableau. These tools allow finance professionals to retrieve large amounts of financial data, organize and analyze this data, and visualize the results so they can be shared. Read on to learn more about how these tools can be used to help you as a Financial Analyst.

What is a Financial Analyst?

Financial Analysts study financial data and perform various research tasks to spot investment opportunities and analyze possible outcomes for business decisions. These professionals play an integral role in helping to create more informed investment strategies for their organization or its clients. To do so, Financial Analysts routinely perform tasks for their employer like studying current events and developments in the market, examining financial statements, and creating financial models that can anticipate future performance. They also may study macroeconomic trends or hone in on particular industries or sectors. Financial Analysts rely on their background in math, accounting, research, reporting, communication, critical thinking, and data analytics to perform these tasks.

Because of how valued they are by organizations, Financial Analysts often find employment with large corporations like insurance companies, security firms, investment banks, venture capital firms, or government agencies. They play an integral role in supporting an organization’s budgeting initiatives, as well as writing financial status reports and recommendations. Their process often involves steps such as collecting data, organizing information, performing data analysis on these numbers, providing projections or forecasts, offering recommendations, creating Excel models, presenting their findings to organizational stakeholders, and writing reports or dashboards to convey suggestions. Depending on their professional focus, Financial Analysts do extensive research on their organization’s buy-side and sell-side financial data. They often focus on either credit markets or equity markets.

Read more about what a Financial Analyst does.

What Software Do Financial Analysts Use?

The following sections will explore four of the tools commonly used by Financial Analysts to handle their organization’s financial data:

Microsoft Excel

Microsoft Excel is a popular tool for those who work in finance. This spreadsheet application comes with a range of built-in functions and features that have applications for core financial analytics tasks. Many finance professionals use this industry-standard spreadsheet app for financial modeling. Excel allows users to create Excel models using integrated data. It’s also helpful for performing subroutines, array functions, and user-defined VBA functions. One of the features that make Excel popular is its capacity to integrate with other apps in the Microsoft 365 suite, as well as other programs. This allows Financial Analysts to easily analyze data and arrive at better financial outcomes.

Tableau

Tableau is another popular tool among Financial Analysts. This data visualization software helps with a range of financial tasks, from investment tracking to budget comparison. Tableau includes many helpful features for assessing company risk, performing audits, and managing compliance. It also has the capability to conduct pricing and revenue analytics, generate forecasting models, and manage accounts receivable, each of which is a core task in the financial sector. Many financial organizations use Tableau to simplify common tasks, such as sourcing, travel and expenses, and managing vendors.

SQL

SQL, or structured query language, allows people to communicate with databases to retrieve vast information stores. This programming language is commonly used in financial analytics. SQL databases like MySQL, PostgreSQL, and Microsoft SQL Server allow Analysts to collect and store information and use data visualization and business intelligence tools to create financial predictions and models. Financial Analysts who use SQL can create more advanced database systems than they’d be able to do using Excel or other tools. Financial institutions that collect and store data rely on SQL because it ensures that the information that’s being stored, such as user trends, is kept safe.

Python

Python is a high-level programming language that has many similarities to the English language. Its intuitive syntax and extensive support modules make Python a popular programming language among Developers, Data Scientists, and financial professionals. Those working in finance often handle large loads of data, and Python helps them perform qualitative and quantitative analyses of this information. This is why it’s considered one of the most essential programming languages in FinTech. Analysts use Python to make stock market predictions and create machine learning technologies related to stock. 

How to Learn Financial Analytics Software

If you want to learn the software needed to be a successful Financial Analyst, a variety of in-person and online learning options are available. For those who wish to receive instruction in real-time, in-person, and live online Excel and Tableau courses are available from Noble Desktop, as well as other top educational providers. These small classes provide hands-on training from industry experts. Because they are conducted in real-time, students can ask questions as they arise and receive guidance on advanced spreadsheet and data visualization tasks. These courses also allow learners to network with other students, a benefit that extends far beyond the classroom.

Another way for Financial Analysts to learn how to use Tableau or Excel for financial tasks is on-demand coursework. Unlike in-person and live online courses, which take place at regularly scheduled intervals and occur in real time, self-paced content is pre-recorded. This means you can access it anytime and from any location. It also allows you to set the pace for study. Because no instructor is available to ask questions, it can be difficult to learn complex Excel functions in this format or to master Tableau’s more advanced features. 

It may be tempting to try and teach yourself the tools of financial analytics. However, if you’re learning for professional reasons, truly mastering Excel or Tableau may require more structured learning options like live online coursework or in-person study.

Other Skills Needed to Become a Financial Analyst

In addition to programming knowledge, as well as Excel and Tableau skills, most Financial Analysts also possess a range of soft skills. Clear communication is essential for those interested in working in financial analytics. Not only is the ability to communicate clearly helpful when writing reports and emails, but it’s used to run meetings, manage teams or projects, and impart data findings to a range of stakeholders. Collaboration skills, too, are also necessary to perform these tasks.

Additionally, Financial Analysts need to have an eye for detail. Because they work to find insights in large datasets and perform detailed research on their organization’s prior financial data, they must be prepared to locate essential insights amid vast amounts of data. This requires patience, focus, and attention to detail. The ability to think critically is another soft skill that’s important in the finance sector. Financial Analysts often are tasked with making decisions that will affect their organization’s financial outcome. Thinking critically allows them to weigh possibilities and decide on the best course of action. 

Some Financial Analysts work on multiple projects at the same time. This requires flexibility and the ability to prioritize the most pressing tasks so that deadlines are adhered to and budgets are created on schedule. Successful multi-tasking is one of the core soft skills you’ll use in financial analytics.

Learn the Skills to Become a Financial Analyst at Noble Desktop

Noble Desktop, an educational provider located in New York City, offers a range of classes devoted to financial modeling and analysis. Financial Modeling Bootcamp is a hands-on, 18-hour course that teaches students fundamental financial concepts, such as corporate valuation, accounting, and finance. Participants in this small class create their own discounted cash flow using Microsoft Excel. Over three days, expert instructors also help students develop a comprehensive financial model for an actual company. As a prerequisite to this bootcamp, students should have intermediate Excel proficiency.

Noble also has a Financial Analyst Training Program that provides expert instruction on timely corporate and financial concepts, such as making a full valuation model. Those enrolled in this intensive program receive instruction on fundamental Excel skills, such as using shortcuts and PivotTables. Advanced Excel techniques are also covered in this 30-hour program, like Goal Seek and cash flow projection tools. All learners also receive instruction on creating a three-statement financial model for a public restaurant company.

In addition to the Financial Modeling Bootcamp and Financial Analyst Training Program, Noble Desktop also has in-person and live online financial modeling training courses. The

Excel Bootcamp offers 18 hours of instruction on core business Excel skills like working with VLOOKUP, INDEX, MATCH, and What-If Analysis for Goal Seek. FinTech courses are also available, like Algorithmic Trading with Python, Python for Data Science Bootcamp, and FinTech Bootcamp. This course provides students with hands-on training from expert instructors in FinTech skills like working with Python and SQL for data analysis, creating machine learning models, and working with different data types like integers, floats, and strings. All students have the option of a free course retake for up to one year, as well as one-on-one mentoring.