Though skeptics claim SQL has nothing to do with finance the technological world is fast evolving and inter-departmental boundaries fast disappearing. Most teams are now cross-functional, and the emphasis for operational efficiency is on being Agile and applying Scrum principles. Even data has moved to cloud storage. That’s obviously why financial analysts need knowledge in Python and SQL.
SQL and Finance:
Data and financial records form the very backbone of all financial analysis. SQL is a great programming language for financial applications. Couple that with cloud storage, cross-functional teams and the never-ending need for differentiating and cutting-edge live databases and it is easy to infer that at least the fundamental techniques of SQL are of paramount importance to the newbie financial analyst. Most people shy away from SQL which appears to be hard to learn and full of math.
However, SQL is the easiest way to store, move data locations, analyze your own data across various internal and external sources, retrieve data at will, make data analytics-based decisions, add the script to edited data, find a particular date’s stock prices and endlessly explore databases. Especially in financial analysis, there is no replacement of data to justify or argue a decision! SQL is truly awesome with queries, not so great at organizing data, has an awe-inspiring backend, works with very few filters and is declarative.
Python and Finance:
Having stressed the need for SQL, add the most-happening financial language of Python to the list of requirements for financial analysts. Python tools take care of math and programming difficulties.
Here are some reasons to adapt to Python:
- Financial modeling tools like VBA Macros and Excel are for beginners. Python can do all this and more with minimum code and not being limited to on-screen data interpolation.
- Testing strategies and trades are possible with simple Python code and algorithms in comparison to the C based coding for financial algorithms.
- Data Analysis is simplified by importing queries in SQL and producing more complex inferential analyses.
- Its libraries are vast and open source.
If you have to learn a few programming languages, then do so at the very beginning of your career to ensure happier more successful tomorrows. The older generation finds adapting to SQL, Python, etc. hard and you will have an unbeatable edge. Do give programming languages like the evolving Lisp, Haskell, and R a fair chance too.
You never know what software your future companies depend on or adapt to. In parting, assimilation of skills is the first hard step in your successful career. There are many skills both technical and non-transferable ones that contribute to making a successful financial analyst immaterial of which area you work in. Doing the financial analyst course at the renowned Imarticus Learning Academy will ensure you get a coveted financial analyst certification while the course comprehensively provides you with the easiest skill-enhancing route.
Also Read: – Do Financial Analysts Use Python