Introduction
The growth of big data has had significant transformative effects on several industries including technology, agriculture, health, education, and finance. Over the past decade, the number of humans using smartphones has increased tremendously and this has created a big pool of user data as smartphone users stamp their digital footprint all over the web. The electronic data collected as a result of these activities yield Big Data that provide valuable insights to decision-makers looking for data points to inform their decision processes. The growth of Big Data has necessitated the development of computer algorithms and tools that can analyze the data at scale. Good analysis and interpretation of the data allow organizations to ‘co-create’ solutions alongside their target users and create new value that is highly tailored to the needs of the market (Turner, Schroeck & Shockley, 2013).

The financial services sector is one of the industries that have adopted Big Data at scale to inform decision making. In stock trading, algorithmic trading and big data help investors utilize historical data to maximize the returns on their portfolios. As the adoption of Big Data in the financial services sector continues, the landscape of the industry is likely to see significant changes in the coming years. Nonetheless, it is notable that organizations are still facing some challenges in capturing, storage, analysis, and interpretation of huge volumes of data (Chen, Chiang & Storey, 2012).

Big Data Opportunities

Traditional data management tools and models have posed several challenges to the finance industry in the past in terms of security and inefficiencies. One of the major security issues is fraudulent activity by insiders and outsiders. With the world increasingly becoming more connected, outsiders acting in bad faith such as hackers have more opportunities to gain access to company data. The traditional models do not have the systems required to secure digital assets as hackers become more advanced by the day. Therefore, this security problem should be overcome as soon as possible because of the tremendously big risk it poses to the financial services sector. The growth of Big Data and associated IT infrastructural development can cure this problem. Another limitation of traditional data tools and models is the ability to accurately analyze customer sentiment. Customer tastes are rapidly changing as they get more choices in the market. Industries must be able to fulfill these ever-changing needs and address them satisfactorily (Nath, 2019).

For companies to be able to know what their customers want in a timely manner, they need to collect and analyze a lot of customer data. Traditional data management tools and models do not provide the tools and techniques necessary to collect or analyze lots of data quickly. Also, the traditional tools and models do not have key functionalities such as the ability to segment customers by psychographic and demographic profiles. This inability for advanced segmentation limits businesses in their ability to accurately target their market segments when doing advertising. There is a growing need for a more advanced system that can help overcome these challenges especially in the financial services sector (Zhou, Fu & Yang, 2016).

The growth of technology and ever-increasing data proliferation has transformed how industries are run. In the recent few years, about 90% of the world’s data has been as a result of the world creating some 2.5 quintillion bytes of data every day. This data phenomenon is known as Big Data and it presents several opportunities in various areas including data collection, data processing, and data analysis. CFOs are increasingly spending their time on data analytics and analysis and the functions of their departments are constantly expanding and shifting. The average finance professional has to expand their skills to include data analysis and analytics to meet the demands of the new financial department. Therefore, CFOs are prioritizing the retraining of finance professionals working under them (Zhou, Fu & Yang, 2016).

It is vital that organizations put their focus on business areas that Big Data can provide disproportionate value. For most organizations...…waiting for resources for such big investments can slow down progress and extend the timeframes that businesses fail to take advantage of Big Data. CFOs should sell the need to move fast and take advantage of already existing infrastructure and data to get projects, however little, underway. Big Data projects can be expanded with time to include greater data varieties and even bigger volumes (Turner, Schroeck & Shockley, 2013).

CFOs and other finance department professionals should train their focus towards getting the specialized skills needed within their industries and organizations. This should include the skills necessary to do a comprehensive analysis of unstructured financial data and present the data in a way other decision-makers within the organization can easily understand. Achieving these objectives will require the finance department to work closely with other departments, especially the IT department (Turner, Schroeck & Shockley, 2013).

Conclusion

Big Data has had several transformative effects on several industries, especially the financial services sector and the finance departments of organizations. CFOs have not been left out in appreciating the role Big Data plays and will continue to play in their operational and strategic roles in organizations. CFOs and their organizations are indeed becoming inundated with data but this is for the good of the organizations they work for. Due to the novelty of the field, Big Data is being embraced rapidly and this will lead to the improvement of processes that usually comes with scale. Increased adoption of Big Data by the financial services sector and various organizations’ finance departments will make CFOs work easier due to increased automation, the accuracy of statistical calculations, ability to collaborate, and sophistication in Big Data tools (Turner, Schroeck & Shockley, 2013).

CFOs understand that to compete in today’s data-driven market, their organizations must leverage all of their data assets to better understand their customers, markets, products, competitors, supply chains, employees, and other players in the industry. Big Data will prove useful to all business leaders, not just CFOs (Turner, Schroeck & Shockley, 2013).…