![]() ![]() Similar to other forms of data analysis, financial analysis utilizes raw financial data and/or business information in order to gain insight into the financial viability of a company, institution, or individual. By learning financial analysis and data science skills, analysts that are working within business and financial institutions can increase their knowledge and capabilities in the collection of user data and/or engagement with financial technologies. ![]() SQL databases offer analysts the ability to not only collect and store information and data but also work with business intelligence and data visualization tools that create valuable financial models and predictions. This makes the SQL programming language an essential skill for financial analysis. ![]() Modern-day Financial Analysts do not only rely on traditional finance skills, such as accounting, statistics, and business analytics, but many Financial Analysts are learning data science skills, such as programming languages and predictive analytics, as well as data visualization and modeling to improve their career prospects.ĭue to the popularity of data science and the need for databases to collect large stores of information, Financial Analysts benefit from learning skills that combine data science and database design. Financial data is primarily collected from users through their engagement with financial technologies or through transactions and consumer behavior. From accounting information to banking transactions, there are many businesses and institutions which rely on the collection of data on finances. The analysis of financial data is one of many subsets of data science and database design that focuses on the collection, storage, and analysis of raw finance data. ![]()
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