Data AnalyticsProfessional Courses

Top 5 Courses in Data Analytics for Finance Professionals

Do you have commendable problem-solving skills and are great with numbers? Look no further for a booming career option. Data analytics is the science of numbers. It involves solving business problems by analyzing the data and observing the trends. The field offers many job opportunities as well as requires great learning ability. Data analytics has highly evolved in recent times and continues to contribute to solving various financial problems for businesses. There are several institutes and online platforms offering courses on data analytics for finance professionals, students, business professionals, and freshers. Let us further learn courses in Data Analytics for Finance Professionals in this blog below.

What Is Data Analytics?

Data analytics is a procedure that examines raw data to discover significant insights, patterns, and trends. This information enables a business to make strategic decisions, optimize performance, and maximize profits. It uses a certain set of statistical and programmatic techniques to convert large sets of data into applicative insights.

This systematic arrangement of data helps organizations to increase their operational efficiency by having a better understanding of customer behavior, and market risks, and identifying growth opportunities.

The field of data analytics for finance professionals helps them become a financial analyst. Financial analysts, as the name suggests typically work on financial data. They help businesses to make better investments for future growth.

Owing to the evolving worldwide automation of the simplest of tasks, various data analytics techniques have also been automated. Transformed into algorithms, these automated processes work on raw data for human consumption.

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Importance of Data Analytics for Finance Professionals

In today’s times, data analytics is an integral part of finance. Financial organizations need to utilize data analysis to get the work done efficiently. The use of data analytics for finance professionals includes better knowledge of Key Performance Indicators (KPIs).

They can easily calculate the generated revenue, cost of payroll, net income, and more to scan through the metrics and detect possible frauds. Data analytics also has a huge contribution to the way stock markets work today and has eventually improved investment-oriented decision-making.

Globally, an increased number of organizations now depend on data analytics to know their customers better and more deeply. It helps the leaders to make more result-oriented decisions that generate productive outcomes.

Before implementing a financial strategy, it is important to analyze the current financial status of the company which in turn is entitled to the operational statistics and data. This is when an organization requires a financial analyst.

Types of Data Analytics

There are various types of data analytics and the type suitable for a particular company can be applied depending on its stage of development. Organizations that have yet not started applying analytics to reduce proactive business decisions can find their business lacking expected performance. The types of data analytics include:

Descriptive Data Analytics

Descriptive analytics involves the use of historical data for understanding business behavior. It helps to analyze the strong and weak factors that can affect the overall sales and growth of a company.

Example: The financial metrics reports generated in a company such as monthly sales growth, Yearly pricing changes, etc. are mostly the result of descriptive analysis.

Diagnostic Data Analytics

Diagnostic Analytics is one of the toughest processes since it involves detecting the root cause of an action. It does not predict the future or analyze past behavior, however, digs deep into the initial cause of action.

Example: Whenever you make an online purchase there are a set of steps followed. The steps include:

  • Visiting a website or app
  • Selecting, opening, and viewing a product page
  • Adding the product to the cart
  • Going to the checkout page
  • Complete the payment and place the order

Now, whenever you drop a purchase mid-way through any of these steps, diagnostic analytics helps the company check the reason for failed conversion. It observes on which step the customer dropped off and thus deduces why.

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Predictive Data Analytics

As the name mentions, Predictive Data analytics is a procedure that makes use of the data for forecasting future outcomes. It uses statistical and modeling techniques to make predictions for businesses that help them reduce risk by understanding future behavior.

Example: Whenever you use an OTT platform for watching movies and series, it collects data from its customers. The data includes your viewing patterns, and genre of most watched content, etc. They use this data to generate “Since you watched this, you may like this..” and “Try Watching..”, etc, lists that are customized for different users.

Prescriptive Data Analytics

The prescriptive analysis technique answers the question of what needs to be done to achieve a particular goal. It is dependent on AI (Artificial intelligence) techniques including machine learning.

Machine Learning helps to process large amounts of data as and when it comes. It automatically adjusts the program to process the data faster than any human can ever do. Prescriptive analysis works hand in hand with predictive analysis. Depending on what is predicted as the future behavior, it alters the course of action for achieving it.

Example: It helps to detect and prevent bank fraud. Suppose you spend 5000 Rs per month on average, however this month you have a 500,000 Rs charge on your credit card. The algorithm analyzes your past behavior and sends an alert to the bank, informing you about the same. The course of action suggested here is to cancel the credit card since it might have been stolen.

Here, it would have been impossible to check such frauds manually amongst thousands of bank accounts. However, with the help of an algorithm running continuously, it is easier to detect such cases in multiple accounts at the same time.

Financial Analysts vs Business Analysts

Both financial as well as business analysts help to scrutinize the data of the organizations or external clients for making significant business decisions. Data analytics techniques can use any type of data to get insights and improve outcomes.

Let us have a look at the importance of data analytics for finance professionals and business executives. On the financial front, analysts help the employer or clients in making investment-related decisions.

They study the financial data to figure out the trends and make forecasts about investments. In other words, they make periodic reports and help the companies buy or sell relevant stakes for better profits and growth. Analysts on a senior level are also required to make high-level decisions as to when is the suitable time to sell the company.

Business Analysts, on the other hand, help the employer to make operational and management-related decisions. The data and findings involved in business analytics are not investment-related but day-to-day operations-related.

They study certain strategies and business models that can also be linked to market analysis. It means that business analysts can also evaluate marketing and sales data. They help streamline the company’s operations and detect its inefficiencies.

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How is Data Analytics Used in Finance?

Data analytics is facing an increased demand in the finance field. Globally, many organizations have started using it to improve their internal operations. The process has a secure future in finance since it is important for the successful roadmap of financial institutions.

Finance is an extremely risky department where customers choose to switch services even after a single bad experience. It depicts high competition in the field. It has now been important for finance professionals to upgrade themselves with data analytics skills. Data analytics for finance professionals includes functions like:

  • Data mining
  • Data manipulating
  • Basic statistical methods
  • Analyzing large and complex data sets

Data analytics helps businesses to turn out profitable by eliminating risk and understanding ongoing market trends. It helps to effectively identify fraudulent and suspicious transactions. When it comes to banking and finance, customers always look for a better and trusted service.

It is a highly competitive market and financial data analytics gives data-driven solutions to understand this market pattern, design new products accordingly, and become operationally more efficient. It also helps banks against loans and investment-related frauds through risk modeling.

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Top 5 Courses in Data Analytics For Finance Professionals

 

1) IIM SKILLS

About: IIM SKILLS  is a rapidly growing ed-tech platform that offers various online courses related to finance, marketing, content writing, analytics, etc. It allows the students to attend online classes at the ease of their working schedules.

They provide lifetime access to the learning management system which includes all the relevant classroom study material, recorded lectures, and notes. It has introduced a certification course in data analytics for finance professionals and business enthusiasts.

 

Course NameData Analytics Master Course
Duration6 Months Program + 2 Months Non-Paid Internship
Course Fee₹ 49,900 + 18% GST

 

Core ModulesDuration
Data Analytics Using Advanced Excel9 Hours
Data Analytics Using VBA15 Hours
Data Analytics Using SQL39 Hours
Data Analytics Using Power BI24 Hours
Data Analytics Using Python-110 Hours
Data Analytics Using Python-210 Hours
Data Analytics Using Tableau15 Hours
R For Data Science20 Hours
Data Analytics Using Alteryx18 Hours

Other Professional Financial Certification Courses Offered by IIM SKILLS Are:

Contact Details:

+919580740740, [email protected]

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2) KPMG

About: KPMG India and Jaro Education offers a certification program in data analytics for finance professionals. It aims to provide strategic finance and analytical skills to working professionals that prepare them for better career growth. Along with the core finance learning, the course also focuses on developing soft skills.

 

Course NameCertification Program In Corporate Finance & Analytics
Duration6 Months Program
Course Fee₹ 96,000 + Taxes

Key Requirements for the Course:

  • Bachelor’s degree in B.com, M.com, Finance MBA, or similar from a recognized institute or university. The candidate must have passed with at least 50% marks or equivalent CGPA.
  • Prior work experience in the finance domain from 1 to 7 years is necessary.
  • Selection is based on profile evaluation and personal interview through video call or Zoom.

Key Features:

  • Virtual classroom program
  • 125 Hour instructor-led learning sessions
  • Completion certificate from KPMG in India

Course Curriculum:

Fund RaisingPortfolio Management
Financial AnalyticsWorking Capital Management
Data VisualizationPower Skills
Financial ModellingESG in Finance
Financial Decision MakingBuilding a career in finance

 

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3) Coursera

About: There are many platforms offering courses and learning programs in data analytics for finance professionals. However, in case you are at a beginner level and looking forward to learning about financial analytics, this is the perfect course crafted for you. Enroll for free and begin your learning journey at your own pace. This course is offered by the University of Illinois and can help you develop a successful career in finance.

Course NameFinancial Analysis – Skills for Success Specialization
Duration1 month at 10 hours a week

Key Features:

  • Learn in-demand skills from industry experts
  • Complete the course with a flexible schedule
  • Get hands-on projects to master a tool or subject
  • Learn key concepts with deep understanding
  • The University of Illinois Urbana-Champaign gives a career certificate on course completion.

The course teaches you numerous skills like Risk, accounting, financial analysis, decision-making, budgeting, and planning.

Course CurriculumDuration
Introduction to Financial Analysis12 Hours
Financial Analysis of Organizations16 Hours
Financial Analysis of Scenarios and Decisions17 Hours

 

4) Nulearn

About: It is a leading ed-tech company that helps you upskill and build a career in emerging industrial developments. Learn new skills with the help of an array of courses in the fields of operations, marketing, management, HR, IT, and analytics.

It offers an Executive Certification Program with IIM Kashipur in the field of Financial Data Analytics. It is also one of the best courses designed in data analytics for finance professionals.

 

Course NameeDP in Financial Data Analytics
Duration5 Months
Course Fee₹ 70,000 + GST

Key Features:

  • Blended learning with online sessions and campus visits
  • Certificate from IIM Kashipur
  • Case-based sessions
  • Weekend class schedule
  • Financial data analytics insights
  • Sessions from industry experts

Course Curriculum:

Financial Statement AnalysisFinancial Derivatives
Time Value of MoneyValue-at-Risk Estimation and Backtesting
Analysis of Bonds & Long-Term FinancingLeasing
Basic Portfolio AnalysisLinear Regression
Valuation of Equity and Firm/BusinessPredicting Binary Outcomes
Capital Structure AnalysisDecision Tree
Capital Budgeting Analysis

5) Udemy

About: Udemy is one of the leading online learning platforms with thousands of courses designed to upskill and provide efficient training programs. Unlike other courses in data analytics for finance professionals, this course does not require any prior knowledge or experience.

Course NameData Analysis for Business and Finance
Duration4.5 hours
Course Fee₹ 1,699

Key Features:

  • On-demand video for 4.5 hours
  • Lifetime access to the complete course
  • Completion certificate

The lectures are designed to build up skills and knowledge from basics.

Uni-variate Variable Analysis – 1
Uni-variate Variable Analysis -2
Bi-variate Variable Analysis
Probability
Probability Distribution
Sampling and Sampling Distributions
Statistical Inference: Hypothesis Testing
Statistical Inference: Confidence Interval
Regression Analysis
Regression Analysis: Statistical Inference
Time Series

 

Frequently Asked Questions

Q. Is data analytics a good career option?

Data analytics is great as a career option because a lack of data skills is affecting many industries worldwide. There will be a lot of requirements for data analysts as companies will need to compete with the ongoing trends and their competitors. Analytics makes it much easier for industries to predict patterns and find solutions to foreseen problems. Data analytics will soon be seen as one of the highest-paying career options worldwide.

Q. Do data analysts need coding?

Data analytics works on the statistical and mathematical observation of large data sets. Such an amount of data cannot be calculated manually. Data analysts require the use of certain programming languages such as Python and R to create mathematical and statistical models as well as algorithms to handle large data sets.

Q. How to become a data analyst in finance?

Data analytics for finance professionals helps them to become financial analysts. They help companies to make investment-related decisions that involve critical decision-making skills. The steps to become a financial analyst are:

  • First, acquire a bachelor’s degree in computer science or any finance-related field such as accounting, statistics, mathematics, business management, economics, etc.
  • A degree is not enough. Sharpen your data analysis skills to stand out in front of the employer.
  • Prepare a resume filled with internships, projects, skills, and more that could appeal to the employer at first glance.
  • Personal interviews are the final stage of the selection process. Build your personality and soft skills to present yourself in front of the interviewer.
  • Lastly, start applying for entry-level internships and jobs to gain relevant hands-on experience.

Q. Which companies hire data analysts in India?

Some of the top companies that hire data analysts in India are:

  • SG Analytics
  • Hyperlink InfoSystem
  • Accenture
  • Tata Consultancy Services
  • Tech Mahindra
  • Capgemini India Pvt Ltd.
  • Genpact
  • Tiger Analytics
  • LatentView Analytics
  • DataFactz

Conclusion

Data Analytics is the next trending technique for businesses to gain rapid growth and achieve the once impossible goals. It helps to analyze the large sets of data and simplify them to predict the future trends. They can foresee future insights and easily build a roadmap to get there. These large sets of data were once ignored by the organizations however, they are now used to track trends, patterns, customer behaviors, and more.

This analysis helps the finance industry as well. Data analytics for finance professionals helps them to reduce the risk of fraudulent transactions and make wiser investments. It has made it easier to make significant investment-related decisions. The finance and banking industry can now keep track of bank accounts and take relevant actions for any suspicious activities. Hence, it identifies the possible risks and also suggests ways to avoid or remove them. Data analysts should necessarily have data visualization, statistical knowledge, decision-making, and problem-solving skills.

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