This article has been written by Jyoti Sharma.
This article has been edited and published by .
Nowadays, data has become a very important part of businesses so financial analysis needs to be combined with data analytics to make smarter and more efficient decisions and operations. Companies use more data than ever to be ahead of their competitors and for that reason we need both financial and data analytics.
Financial analyses mean using numbers and calculations to support decision-making, risk management, and performance improvement. For instance, financial analysts build models to make predictions used by companies for deciding where they need to invest or how they can improve their processes, but data analytics are different. It’s about wading through massive amounts of data to discover helpful patterns and trends. It involves applying advanced techniques like statistical analysis, machine learning, and predictive modelling to understand market and customer trends—as well as how to improve operations.
The job market for finance and data analysts is vast. The number of financial analyst jobs in the U.S. will increase @ 11% by 2026. In India, it is ascertained that there will be 500,000 data analytics jobs by 2025 and a CAGR growth of 23%. Banking sector generates the largest number of data analytics jobs in India which accounts to nearly 40% followed by e-commerce with about roughly 13%. Salaries range between $70,000 — $120,000 per year in the US and INR 6 lakhs —15 lakhs in India. Artificial intelligence use-case are booming and more opportunities of remote work.
When you mix finance and data analysis together, you open up a world of career roles like financial data analysts, retail risk managers, or investment analysts. Due to employment trends focusing on using evidence to drive financial decision-making, this illustrates the point further.
This field analyses financial data and methods for estimating financial risks and dealing with money issues. The purpose is to make the financial expenditure evaluated objectively cuz that it should not create losses to the business entity.
Financial analysis guidelines help in assuring accuracy, clarity, and stability.
It is important to follow these rules to ensure responsible and ethical investigations and to protect personal accounts and financial information.
A career in financial data analytics requires a multi-skill set, which includes technical skills, analytical skills and communication skills. This helps the professionals to excel well in understanding intricate financial data and sophisticated analytical processes.
The job depends on strong understanding of economic principles. Management must have knowledge on factors such as financial markets, accounting and investment methods. This understanding enables them to review risk procedures, scope finance proposals and make recommendations that are beneficial to the organisation.
It is essential to have skills in using these tools for data analysis. Skills such as Excel, SQL, and programming languages Python and R are essential in analysing large amounts of data. Other helpful skills would be the use of data visualisation software such as Tableau and Power BI to help the researcher enhance the presentation of the solutions from the data. The growing use of machine learning techniques and predictive models within financial analysis has also necessitated the use of these advancements.
Conceptual skills are a prerequisite for pattern detection, interpretation and making decisions supported with data Mastery of a variety of statistical concepts and techniques as well as application of logic to qualitatively evaluate business decisions based on the data received is very fundamental.
The necessity of accurate communication is relevant for the effective transformation of complicated data results into business-orientated activities. The scientists in social science should know how to communicate their findings to non-expert users so that the users are able to make sense out of it, which promotes making decisions based on science rather than sheer guesswork.
The knowledge of law and abiding As everyone knows, knowing the legal aspects of any activity is vitally important considering the delicate nature of financial obscurity. Regulations like the General Data Protection Regulation and the Sarbanes-Oxley act have to be strictly followed by businesses so as to help avert legal issues and enhance ethical conduct.
Problem-solving and change management with the knowledge of dynamics involving the work of a financial analyst. One needs to be sharp in problem-solving as well as versatile in the face of emerging technologies and market changes. According to Nelson (2005), in order to remain competitive in such a fast-changing landscape, continuous improvement and development of processes is critical.
To aggregate the above information, to pursue a career as a financial and data analyst in any other environment, one has to take certain steps that provide them with the education, skills and experience relevant to this need.
Begin with a bachelor’s degree in finance, but minors in economics will usually suffice. Advanced degrees in finance or data science and membership in professional bodies like the Chartered Financial Analyst (CFA).
Accountant (CA) and Financial Risk Manager (FRM) enhance global employability (CFA Institute, 2021). International law and cross-cultural communication are also important.
Be adept at data analysis and financial modelling with advanced knowledge of using Excel, SQL, Python, and Tableau. Familiarity with machine learning and predictive analytics is of big advantage as well (McKinsey & Company, 2020).
Look for internships or entry-level jobs in financial or data analytics positions in order to learn the routine and the peculiarities of the industry (World Economic Forum, 2020)
Seek employment either in different markets or look for international companies so that you can attend professional networks and international conferences in the event that they pursue expatriate opportunities.
Commit to lifelong learning through courses and certifications to stay current with technological advancements and industry trends.
The following are some of the certifications that are recognised for individuals who have an interest in this field: These certifications enhance credibility, provide specialized knowledge, and increase employability in the global market. These certifications enhance credibility, provide specialised knowledge, and increase employability in the global market.
Chartered Financial Analyst (CFA)
Offered by: CFA Institute is a global not-for-profit organisation that sets the standards for assessment, education and professional development of researchers.
Focus: Basic concepts of investment analysis and portfolio management, legal and ethical considerations.
Relevance: Known in the financial sector, especially to those personnel who perform investment analysis and management.
Certified Financial Planner (CFP)
Offered by: Certified Financial Planner Board of Standards
Focus: Goals and objectives of the insurance and financial planning, investment processes and management of risks.
Relevance: Perfect for any contributor that deals with self-employment and finance.
Certified Analytics Professional (CAP)
Offered by: INFORMS
Focus: The capabilities include data analytics, predictive modelling or advanced analytical models.
Relevance: Most appropriate for data analysts and others who have to incorporate analytics on their work on a daily basis.
CAIA—Chartered Alternative Investment Analyst
Offered by: CAIA Association o Focus: Other investment assets such as hedge funds, private equity, and real asset investments.
Relevance: It is therefore suitable for professionals in the area of operation of such services, such as the field of professional asset and/or option management.
Certificate in Quantitative Finance (COF)
Offered by: Fitch Learning Fitch Learning o Focus: Applications include: quantitative finance, financial engineering, and risk management.
Relevance: Designed especially for the working professionals who operate at the quantitative positions for financial organisations.
Certified Public Accountant (CPA)
Offered by: AICPA or NY state requirements or equivalent with the regulations of all the other countries.
Focus: Accounting, auditing, taxation and financial reporting.
Relevance: Very important, especially for the finance professionals to possess accounting skills in their practice.
Microsoft Certified Data Analyst Associate
Offered by: Microsoft o Focus: Information representation, Power BI and data manipulation.
Relevance: For information professionals, who base themselves and their decisions on analysed data.
In doing so, financial and data analysts involve themselves with the collection and subsequent formatting of financial and operating data on large scales. They feed it data from various sources, ensure that the data is accurate and sometimes correct it if there is an instance of error. They specifically utilise special software in order to manage and sort the information in the right manner.
They must also be involved in evaluating the financial information to develop the trends, patterns and details of anomalies. They provide complex data in written form and use different graphics to enable people to make the right decision. Researchers are expected to present such data in terms that are quite straightforward so that everyone, including laypeople, can understand.
There is also the need for analysts to adhere to all the policies that are related to the financial industry as well as data protection laws. People have to act to secure data and organise processes according to rules such as GDPR or CCPA to protect people’s data.
Both financial and data analytics are two strong growing fields, fuelled by the advancement in analytics in almost every sector. The U.S. Bureau of Labour Statistics has forecasted the 9% increase in employment for the financial analysts in the next decade of 2020 to 2030, which is far better than the average position for all occupations (BLS, 2021). In the same manner, the global market for data analytics is considered to grow from $54. In 2021, it was approximately $3 billion and it is expected to rise to about $105 billion by 2027 with a CAGR of 30.08% (Statista, 2023). This kind of growth is a very good thing, as there are always jobs to be found and this area offers great job security.
These positions are versatile and people who work in those positions can work in the finance industry, technology industry, healthcare industry and retail industry among others. This diversity affords the possibility of bringing the analytical skills to bear in a variety of situations and in a variety of fields there by improving flexibility and promotional opportunities.
The use of technologies such as machine learning and artificial intelligence in these fields guarantees continuity of innovation. Employment of quantitative tools is common practice for financial and data analysts, which makes the work challenging, on the one hand, and up-to-date, on the other. Incorporation of new technologies is part of these careers and will always be helping the individuals to grow in their profession.
Financial and data analysis are human beings who help in the planning of major operations that can define business performance as well as economic development. Through such activities as trend analysis, outcome prediction and risk management, they play a pivotal role in the formulation and implementation of organisational strategies and tactics.
Compliance with such regulations as GDPR and CCPA remains essential among the organisation’s priorities. Due to the fact that analysts work with large amounts of data, they have to ensure the data’s security through the use of measures such as encryption (European Commission, 2021).
The rate of growth of technological advancements is increasing day by day and sometimes it gets difficult to cope up because of the demands of constant learning and tweaking.
Other challenges that may affect the reliability of the analysis may include the control of inconsistent or inaccurate data and the merging of data obtained from different sources (Harvard Business Review, October 2020).
The construction and analysis of complicated financial models represent rich theories and methods, which require much experience.
Altogether, the choice of a profession in the field of financial and data analytics can be considered safe since it is demanded in all industries and does not have any shortage in the number of promising vacancies. The opportunities are evident from the enhancement of innovative technologies alongside the opening of global markets. However, there are always some obstacles that professionals face like the conflicts of data privacy, lack of skills and talents, and ethical problems to reach success in these areas. The industry is dynamic and it is therefore crucial that people have to stay curious and willing to learn more in order to try and match the changes so as to be relevant and able to meet the demands.
The post appeared first on .
This article has been edited and published by .
Introduction
Nowadays, data has become a very important part of businesses so financial analysis needs to be combined with data analytics to make smarter and more efficient decisions and operations. Companies use more data than ever to be ahead of their competitors and for that reason we need both financial and data analytics.
Financial analyses mean using numbers and calculations to support decision-making, risk management, and performance improvement. For instance, financial analysts build models to make predictions used by companies for deciding where they need to invest or how they can improve their processes, but data analytics are different. It’s about wading through massive amounts of data to discover helpful patterns and trends. It involves applying advanced techniques like statistical analysis, machine learning, and predictive modelling to understand market and customer trends—as well as how to improve operations.
The job market for finance and data analysts is vast. The number of financial analyst jobs in the U.S. will increase @ 11% by 2026. In India, it is ascertained that there will be 500,000 data analytics jobs by 2025 and a CAGR growth of 23%. Banking sector generates the largest number of data analytics jobs in India which accounts to nearly 40% followed by e-commerce with about roughly 13%. Salaries range between $70,000 — $120,000 per year in the US and INR 6 lakhs —15 lakhs in India. Artificial intelligence use-case are booming and more opportunities of remote work.
When you mix finance and data analysis together, you open up a world of career roles like financial data analysts, retail risk managers, or investment analysts. Due to employment trends focusing on using evidence to drive financial decision-making, this illustrates the point further.
Overview of financial and data analytics
Definition of financial analytics
This field analyses financial data and methods for estimating financial risks and dealing with money issues. The purpose is to make the financial expenditure evaluated objectively cuz that it should not create losses to the business entity.
Regulatory framework
Financial analysis guidelines help in assuring accuracy, clarity, and stability.
- The Dodd Frank Act and the Sarbenes-Oxley Act are two important acts which required strict financial reporting in order to prevent fraud.
- Data analysis: The two important acts are the General Data Protection Regulation and the California Consumer Privacy Act. GDPR mandates teams to obtain formal consent before using personal data and to maintain proper records of their consent. The California Consumer Privacy Act gives rights to individuals based on their personal information that also include the right to access and delete their data.
It is important to follow these rules to ensure responsible and ethical investigations and to protect personal accounts and financial information.
Skills required for a career in financial and data analytics
A career in financial data analytics requires a multi-skill set, which includes technical skills, analytical skills and communication skills. This helps the professionals to excel well in understanding intricate financial data and sophisticated analytical processes.
Economic knowledge
The job depends on strong understanding of economic principles. Management must have knowledge on factors such as financial markets, accounting and investment methods. This understanding enables them to review risk procedures, scope finance proposals and make recommendations that are beneficial to the organisation.
Technical knowledge
It is essential to have skills in using these tools for data analysis. Skills such as Excel, SQL, and programming languages Python and R are essential in analysing large amounts of data. Other helpful skills would be the use of data visualisation software such as Tableau and Power BI to help the researcher enhance the presentation of the solutions from the data. The growing use of machine learning techniques and predictive models within financial analysis has also necessitated the use of these advancements.
Analysis and critical thinking
Conceptual skills are a prerequisite for pattern detection, interpretation and making decisions supported with data Mastery of a variety of statistical concepts and techniques as well as application of logic to qualitatively evaluate business decisions based on the data received is very fundamental.
Communication skills
The necessity of accurate communication is relevant for the effective transformation of complicated data results into business-orientated activities. The scientists in social science should know how to communicate their findings to non-expert users so that the users are able to make sense out of it, which promotes making decisions based on science rather than sheer guesswork.
Legal knowledge and compliance
The knowledge of law and abiding As everyone knows, knowing the legal aspects of any activity is vitally important considering the delicate nature of financial obscurity. Regulations like the General Data Protection Regulation and the Sarbanes-Oxley act have to be strictly followed by businesses so as to help avert legal issues and enhance ethical conduct.
Problem-solving and adaptability
Problem-solving and change management with the knowledge of dynamics involving the work of a financial analyst. One needs to be sharp in problem-solving as well as versatile in the face of emerging technologies and market changes. According to Nelson (2005), in order to remain competitive in such a fast-changing landscape, continuous improvement and development of processes is critical.
How to become a financial and data analyst professional
To aggregate the above information, to pursue a career as a financial and data analyst in any other environment, one has to take certain steps that provide them with the education, skills and experience relevant to this need.
Educational foundation
Begin with a bachelor’s degree in finance, but minors in economics will usually suffice. Advanced degrees in finance or data science and membership in professional bodies like the Chartered Financial Analyst (CFA).
Accountant (CA) and Financial Risk Manager (FRM) enhance global employability (CFA Institute, 2021). International law and cross-cultural communication are also important.
Technical skills development
Be adept at data analysis and financial modelling with advanced knowledge of using Excel, SQL, Python, and Tableau. Familiarity with machine learning and predictive analytics is of big advantage as well (McKinsey & Company, 2020).
Gaining practical experience
Look for internships or entry-level jobs in financial or data analytics positions in order to learn the routine and the peculiarities of the industry (World Economic Forum, 2020)
International exposure and networking
Seek employment either in different markets or look for international companies so that you can attend professional networks and international conferences in the event that they pursue expatriate opportunities.
Continuous learning
Commit to lifelong learning through courses and certifications to stay current with technological advancements and industry trends.
Certifications available for financial and data analyst professional
The following are some of the certifications that are recognised for individuals who have an interest in this field: These certifications enhance credibility, provide specialized knowledge, and increase employability in the global market. These certifications enhance credibility, provide specialised knowledge, and increase employability in the global market.
Chartered Financial Analyst (CFA)
Offered by: CFA Institute is a global not-for-profit organisation that sets the standards for assessment, education and professional development of researchers.
Focus: Basic concepts of investment analysis and portfolio management, legal and ethical considerations.
Relevance: Known in the financial sector, especially to those personnel who perform investment analysis and management.
Certified Financial Planner (CFP)
Offered by: Certified Financial Planner Board of Standards
Focus: Goals and objectives of the insurance and financial planning, investment processes and management of risks.
Relevance: Perfect for any contributor that deals with self-employment and finance.
Certified Analytics Professional (CAP)
Offered by: INFORMS
Focus: The capabilities include data analytics, predictive modelling or advanced analytical models.
Relevance: Most appropriate for data analysts and others who have to incorporate analytics on their work on a daily basis.
CAIA—Chartered Alternative Investment Analyst
Offered by: CAIA Association o Focus: Other investment assets such as hedge funds, private equity, and real asset investments.
Relevance: It is therefore suitable for professionals in the area of operation of such services, such as the field of professional asset and/or option management.
Certificate in Quantitative Finance (COF)
Offered by: Fitch Learning Fitch Learning o Focus: Applications include: quantitative finance, financial engineering, and risk management.
Relevance: Designed especially for the working professionals who operate at the quantitative positions for financial organisations.
Certified Public Accountant (CPA)
Offered by: AICPA or NY state requirements or equivalent with the regulations of all the other countries.
Focus: Accounting, auditing, taxation and financial reporting.
Relevance: Very important, especially for the finance professionals to possess accounting skills in their practice.
Microsoft Certified Data Analyst Associate
Offered by: Microsoft o Focus: Information representation, Power BI and data manipulation.
Relevance: For information professionals, who base themselves and their decisions on analysed data.
Organisational demand for financial and data analyst professionals
Data collection and processing
In doing so, financial and data analysts involve themselves with the collection and subsequent formatting of financial and operating data on large scales. They feed it data from various sources, ensure that the data is accurate and sometimes correct it if there is an instance of error. They specifically utilise special software in order to manage and sort the information in the right manner.
Analysis and reporting
They must also be involved in evaluating the financial information to develop the trends, patterns and details of anomalies. They provide complex data in written form and use different graphics to enable people to make the right decision. Researchers are expected to present such data in terms that are quite straightforward so that everyone, including laypeople, can understand.
Compliance and data security
There is also the need for analysts to adhere to all the policies that are related to the financial industry as well as data protection laws. People have to act to secure data and organise processes according to rules such as GDPR or CCPA to protect people’s data.
Why should one choose a career in financial and data analyst
Growing demand and job security
Both financial and data analytics are two strong growing fields, fuelled by the advancement in analytics in almost every sector. The U.S. Bureau of Labour Statistics has forecasted the 9% increase in employment for the financial analysts in the next decade of 2020 to 2030, which is far better than the average position for all occupations (BLS, 2021). In the same manner, the global market for data analytics is considered to grow from $54. In 2021, it was approximately $3 billion and it is expected to rise to about $105 billion by 2027 with a CAGR of 30.08% (Statista, 2023). This kind of growth is a very good thing, as there are always jobs to be found and this area offers great job security.
Diverse career opportunities
These positions are versatile and people who work in those positions can work in the finance industry, technology industry, healthcare industry and retail industry among others. This diversity affords the possibility of bringing the analytical skills to bear in a variety of situations and in a variety of fields there by improving flexibility and promotional opportunities.
Intellectual stimulation and innovation
The use of technologies such as machine learning and artificial intelligence in these fields guarantees continuity of innovation. Employment of quantitative tools is common practice for financial and data analysts, which makes the work challenging, on the one hand, and up-to-date, on the other. Incorporation of new technologies is part of these careers and will always be helping the individuals to grow in their profession.
Impactful decision-making
Financial and data analysis are human beings who help in the planning of major operations that can define business performance as well as economic development. Through such activities as trend analysis, outcome prediction and risk management, they play a pivotal role in the formulation and implementation of organisational strategies and tactics.
Challenges as a financial and data analyst professional
Data security and privacy
Compliance with such regulations as GDPR and CCPA remains essential among the organisation’s priorities. Due to the fact that analysts work with large amounts of data, they have to ensure the data’s security through the use of measures such as encryption (European Commission, 2021).
Technological advancements
The rate of growth of technological advancements is increasing day by day and sometimes it gets difficult to cope up because of the demands of constant learning and tweaking.
Data quality and integration
Other challenges that may affect the reliability of the analysis may include the control of inconsistent or inaccurate data and the merging of data obtained from different sources (Harvard Business Review, October 2020).
Complexity of financial models
The construction and analysis of complicated financial models represent rich theories and methods, which require much experience.
Conclusion
Altogether, the choice of a profession in the field of financial and data analytics can be considered safe since it is demanded in all industries and does not have any shortage in the number of promising vacancies. The opportunities are evident from the enhancement of innovative technologies alongside the opening of global markets. However, there are always some obstacles that professionals face like the conflicts of data privacy, lack of skills and talents, and ethical problems to reach success in these areas. The industry is dynamic and it is therefore crucial that people have to stay curious and willing to learn more in order to try and match the changes so as to be relevant and able to meet the demands.
References
- CFA Institute (2021). Career Path in Financial Analytics.
- McKinsey & Company (2020). The Rise of Analytics in Financial Markets.
- PwC (2021). Continuous Learning in Finance and Analytics.
- World Economic Forum (2020). The Future of Jobs Report.
- U.S. Bureau of Labor Statistics (BLS, 2021). Employment Projections.
- Statista (2023). Global Data Analytics Market Size.
- Glassdoor (2023). Median Salaries for Financial and Data Analysts
- Harvard Business Review (2020). The Challenges of Data Quality in Analytics.
- CFA Institute (2021). Financial Modelling and Analysis,
- McKinsey & Company (2021). The Future of Data Analytics in Finance. European Commission (2021). General Data Protection Regulation (GDPR)
The post appeared first on .