Implications of Big Data in Accounting: Challenges and Opportunities

Objectives: This paper aims to comprehensively explore the implications of Big Data within the realm of accounting, dissecting both its potential advantages and the hurdles it presents. The primary goal is to introduce and delineate the potential benefits of Big Data integration in accounting practices. Additionally, it seeks to identify and thoroughly examine the challenges impeding the seamless assimilation of Big Data into accounting methodologies. By delving into diverse applications, including Auditing, Cost Management, and financial reporting, this study aims to shed light on the multifaceted nature of Big Data's role in accounting. Methods/Analysis: This paper commences with an introduction to the concept of Big Data and its anticipated advantages for accounting practices. It proceeds to conduct a meticulous review and synthesis of existing literature, dissecting the intricate relationship between Big Data and accounting. Through this review, it emphasizes the stumbling blocks encountered in integrating Big Data. Subsequently, it offers a detailed exploration of Big Data's applications in accounting. Findings : Big Data exhibits the potential to substantially transform accounting practices, offering avenues for superior decision-making and analysis. However, the challenges related to data management and analysis pose substantial barriers for accountants in effectively integrating Big Data. Novelty/Improvement : This study offers a comprehensive exploration, dissecting both the potential advantages and challenges presented by Big Data within accounting practices. It provides detailed insights into specific applications of Big Data in accounting, going beyond a surface-level understanding and focusing on domains like Auditing, Cost Management, and financial reporting.


1-Introduction
In recent years, the field of accounting has been transformed by the rise of Big Data.Big Data refers to large and complex sets of data that cannot be easily analyzed using traditional data processing tools.These massive datasets are becoming increasingly common in the accounting profession, as businesses generate vast amounts of financial data that must be analyzed and interpreted [1].The use of Big Data in accounting has opened up new opportunities for accountants to gain insights into financial data and make better decisions.With the help of advanced analytics and machine learning tools, accountants can now analyze large datasets in real-time, identify patterns and trends, and make predictions about future financial performance [2].This can help businesses to optimize their financial strategies and make better-informed decisions [3].
The integration of big data into accounting processes has revolutionized the landscape, yet significant challenges persist.Managing colossal volumes of data, ensuring its accuracy and reliability, and navigating rapidly evolving technologies pose substantial hurdles [4].This paper delves into these challenges, aiming to illuminate their impact on traditional accounting practices [5][6][7].One key area where Big Data is making a significant impact is in financial auditing [8].Traditional auditing methods involve manually reviewing a small sample of financial transactions to identify errors or discrepancies.However, with the help of Big Data analytics tools, auditors can now analyze entire datasets in realtime, making it easier to identify potential issues and irregularities.This can help to improve the accuracy and efficiency of financial audits and reduce the risk of fraud or other financial irregularities [9][10][11][12][13][14][15].Despite the potential benefits of Big Data in accounting, there are also challenges associated with its use.The sheer volume and complexity of the data can make it difficult to analyze, and there are concerns about data privacy and security.As financial data becomes more valuable, the risk of cyber-attacks and data breaches also increases, making it essential for businesses to implement robust data security measures [16,17].
The rise of Big Data analytics is also influencing the new generation of accountants, particularly millennials who are more tech-savvy and open to adopting new technologies [18][19][20].Emerging technologies, including Big Data analytics, are transforming the audit and assurance profession by introducing new tools and methodologies that enhance audit quality and efficiency [21,22].This paper will explore the ways in which Big Data is transforming the field of accounting, including the benefits and challenges associated with its use [23].We will examine the tools and techniques used to analyze Big Data in accounting, as well as the implications of Big Data for the accounting profession.
Previous studies exploring the implications of Big Data in Accounting have laid a foundational understanding of the transformative potential this integration holds [24].Cheng et al. [25] have extensively investigated the multifaceted aspects of Big Data, elucidating its capacity to revolutionize decision-making processes and enhance analytical capabilities within accounting frameworks.They have underscored the challenges posed by the vast influx of data, emphasizing issues surrounding its management, quality assurance, and the need for evolving technological infrastructure.Moreover, prior research has delved into specific applications of Big Data in accounting domains such as Auditing, Financial Reporting, and Cost Management, showcasing its diverse utility.These studies have significantly contributed to unveiling the opportunities and complexities inherent in incorporating Big Data into traditional accounting practices, setting the stage for further exploration and innovation in this evolving field [25].

2-Applications, Tools and Technologies for Big Data in Accounting
There are several applications of Big Data in accounting, including auditing, fraud detection, and financial analysis.One of the main applications of Big Data in accounting is auditing.By analyzing large amounts of financial data, auditors can identify patterns and anomalies that may indicate fraudulent or suspicious activity [26][27][28].This can help to improve the accuracy and effectiveness of audits, while also reducing the risk of fraud [29,30].Another application of Big Data in accounting is fraud detection.Big Data can be used to identify unusual patterns or anomalies in financial transactions, which may indicate fraudulent activity [31][32][33].This can help to prevent and detect fraud, which can have significant financial and reputational consequences for businesses.
Finally, Big Data can be used for financial analysis.By analyzing large amounts of financial data, accountants can identify trends and patterns in financial performance, which can be used to inform financial forecasting and planning [34][35][36].This can help businesses to make more accurate predictions about future financial performance and make better decisions about resource allocation [37,38].
As the use of big data continues to grow in accounting, new tools and technologies are being developed to help accountants and financial professionals effectively collect, store, and analyze large amounts of data [39][40][41].In this chapter, we'll take a closer look at some of the most commonly used tools and technologies for big data in accounting.

2-1-Data Visualization Software
Data visualization software is an essential tool for accounting professionals who need to make sense of large amounts of financial data.These software tools allow users to turn complex financial information into visual representations that are easy to understand and interpret [42].This makes it easier for accountants to identify patterns, trends, and insights that may be hidden in the data.Some popular data visualization software tools for accounting include Tableau, QlikView, and Power BI.These tools offer a range of features such as interactive dashboards, customizable charts and graphs, and data filters.They can also connect to a variety of data sources, such as accounting software, spreadsheets, and databases, allowing accountants to easily access and analyze their financial data.
Data visualization software can be used for a range of tasks in accounting, such as financial reporting, budgeting, forecasting, and auditing.They can also be used to identify anomalies, such as unusual transactions or patterns of behavior, that may indicate fraud or other financial irregularities [43].Overall, data visualization software is an essential tool for accounting professionals looking to gain deeper insights into financial data and improve decision-making processes [44].

2-2-Machine Learning Algorithms
Another powerful tool for big data in accounting is machine learning algorithms.These algorithms use statistical models to find patterns in large data sets and can help identify anomalies or potential areas of risk.They can also be used to automate certain accounting processes, such as transaction categorization and invoice matching [45].Machine learning has transformed the accounting industry, offering new ways to automate tasks and gain insights from financial data.Some of the most common machine learning algorithms used in accounting include regression analysis, decision trees, random forest, Naive Bayes, neural networks, and clustering.Each algorithm has its own strengths and weaknesses, and it's important to choose the right one for the specific accounting task at hand.These algorithms can be used for a range of tasks, such as analyzing financial decisions, classifying transactions, and grouping expenses.Overall, machine learning is a powerful tool for accounting professionals looking to streamline their work and gain deeper insights into financial data [46].

2-3-Cloud Computing Platforms
As the amount of data collected by companies continues to grow, many are turning to cloud computing platforms to store and manage that data.These platforms offer flexible storage and processing capabilities and can be easily scaled up or down as needed [47].They also provide a secure and reliable environment for data storage and analysis.Popular cloud computing platforms used in accounting include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform.Cloud computing has transformed the accounting industry, providing businesses with new opportunities to manage their financial data and streamline their operations.Below are mentioned some of the most popular cloud computing platforms for accounting [48]: QuickBooks Online: QuickBooks is one of the most popular cloud-based accounting platforms available, and it's designed specifically for small and medium-sized businesses.It offers features such as invoicing, payroll management, expense tracking, and financial reporting.
Xero: Xero is another cloud-based accounting platform that offers similar features to QuickBooks.It's designed for small and medium-sized businesses and offers features such as invoicing, payroll management, expense tracking, and financial reporting.
FreshBooks: FreshBooks is a cloud-based accounting platform designed for freelancers and small businesses.It offers features such as invoicing, time tracking, expense tracking, and financial reporting.
Sage Intacct: Sage Intacct is a cloud-based accounting platform designed for mid-sized businesses.It offers features such as general ledger, accounts payable, accounts receivable, cash management, and financial reporting.
Wave: Wave is a free cloud-based accounting platform designed for small businesses.It offers features such as invoicing, accounting, and receipt scanning.
NetSuite: NetSuite is a cloud-based accounting platform designed for mid-sized businesses.It offers features such as financial management, order management, inventory management, and e-commerce.
Each of these cloud computing platforms has its own unique features and benefits, so it's important to evaluate them carefully and choose the one that best meets the specific accounting needs in each case.

2-4-Blockchain Technology
While still relatively new in accounting, blockchain technology has the potential to transform the way financial transactions are recorded and verified.This distributed ledger technology allows for secure and transparent transactions, with each transaction recorded in a tamper-proof digital ledger.This could greatly reduce the risk of fraud and errors in financial reporting [49].However, there are still challenges to be addressed in terms of standardization and regulation.In addition to these tools and technologies, there are also a range of other tools that can be used for big data in accounting, including data warehouses, and natural language processing tools.Blockchain technology and artificial intelligence are becoming integral to the accounting profession, offering new ways to handle transactions, data integrity, and predictive analytics [50][51][52][53].As the use of big data continues to grow in accounting [54], it's important for financial professionals to stay up-to-date with the latest tools and technologies available to them.By doing so, they can more effectively manage and analyze the vast amounts of data that are now being generated by companies across a range of industries [55].

3-Challenges and Limitations of Big Data in Accounting
While the use of big data has the potential to revolutionize accounting practices, there are also several challenges and limitations that need to be addressed.Some of the major challenges and limitations are discussed below.

3-1-Data Quality and Reliability
One of the major challenges of big data is the quality and reliability of the data.Big data is often sourced from a variety of different systems, both internal and external to the organization [56].This data can be unstructured, incomplete, or contain errors.This makes it difficult to ensure the quality and reliability of the data.Furthermore, since big data is often sourced from external systems, there is a risk that the data is not accurate or up-to-date [57].

3-2-Data Privacy and Security
Another major challenge of big data is data privacy and security.With the increase in the amount of data being collected, there is a risk of data breaches and cyber-attacks [58].Accounting data is particularly sensitive and needs to be protected from unauthorized access.Organizations need to ensure that they have the appropriate security measures in place to protect their data [59,60].

3-3-Skill Set and Expertise
Big data requires a unique skill set and expertise.Organizations need to have staff with the necessary skills to manage and analyze large amounts of data.This includes skills such as data analytics, data visualization, and machine learning.Furthermore, organizations need to ensure that their staff have the necessary training to work with big data [61].

3-4-Integration with Existing Systems
Another challenge of big data is integration with existing systems.Many organizations have legacy systems that are not designed to handle large amounts of data.This can make it difficult to integrate big data with existing systems.Organizations need to ensure that their existing systems are capable of handling big data [62].Big Data has prompted the development of new models for integrating large datasets into existing accounting information systems.A REA (Resources, Events, Agents) ontology-based model has been proposed to map Big Data effectively to these systems, enhancing their functionality and providing richer insights [63].

4-Impact of Big Data on Accounting Functions
The use of big data has the potential to significantly impact various accounting functions such as financial reporting, auditing, and cost management.With the increased availability and accessibility of data, the traditional role of accountants in collecting and processing data is likely to change.Accountants will need to develop new skills in data analytics and visualization to take advantage of the insights provided by big data [64].

4-1-Financial Reporting
The advent of big data has significantly influenced corporate reporting.The vast amount of data available can lead to more detailed and comprehensive reports, but it also introduces paradoxes where too much information can overwhelm decision-makers.Proper governance and strategies are needed to navigate these challenges effectively [65,66].Big data analytics can help companies process and analyze vast amounts of financial data, allowing them to identify patterns and trends that might otherwise go unnoticed.One way that big data is improving financial reporting is through the automation of routine tasks.By using machine learning algorithms, software can automatically categorize financial data and flag potential errors, allowing auditors to focus on more complex tasks [67].Additionally, big data can help companies identify potential fraud or other financial irregularities.By analyzing vast amounts of financial data, companies can identify patterns that may indicate fraudulent activity or other types of financial wrongdoing.Another way that big data is impacting financial reporting is by improving the speed and accuracy of financial statements.By automating many of the manual processes associated with financial reporting, companies can produce financial statements faster and with fewer errors.Overall, the impact of big data on financial reporting is significant, and companies that embrace this technology are likely to enjoy significant benefits in terms of improved accuracy, greater efficiency, and increased transparency [68].As big data technology continues to evolve, it is likely that we will see even more innovative applications of this technology in the field of financial reporting.

4-2-Auditing
The modern audit engagement is evolving with the integration of Big Data and analytics.There is a growing need for research to optimize these tools for audit purposes, addressing specific needs and challenges within the field [69,70].Additionally, the timing of introducing Big Data analyses into the audit process is crucial for maximizing their effectiveness [71].In the past, auditors relied on a limited amount of data, typically focused on financial statements and other internal accounting records.However, with the rise of big data, auditors now have access to a much larger and more diverse set of data sources.One key way in which big data has impacted auditing is by enabling auditors to conduct more thorough and detailed analyses of a company's financial records.By analyzing large amounts of data from various sources, including social media, email records, and other non-financial data sources, auditors can gain a more comprehensive understanding of a company's operations and potential risks [72].Another impact of big data on auditing is that it has enabled auditors to identify potential fraud and other irregularities more quickly and accurately.By analyzing data from a wide range of sources, auditors can detect patterns and anomalies that may indicate fraudulent activity, such as unusual financial transactions or suspicious behavior by company employees [73].In addition, big data has also helped auditors to conduct their work more efficiently and effectively.By automating many of the data analysis and verification processes, auditors can reduce the time and resources required for traditional audit procedures.This not only increases the speed and accuracy of the audit process, but also frees up auditors to focus on more complex and strategic tasks.Overall, the impact of big data on auditing has been significant, enabling auditors to conduct more thorough and detailed analyses of financial records, detect potential fraud and irregularities more quickly, and operate more efficiently and effectively [3,74].As the amount of data continues to grow, it is likely that the impact of big data on auditing will continue to evolve and become increasingly important in the years to come.

4-3-Cost Management
Big data has had a significant impact on cost management in accounting.By providing companies with access to large amounts of data, big data has enabled them to more effectively analyze their costs and identify areas where they can save money [75,76].This has resulted in cost reduction and optimization, which can help companies improve their profitability.One keyway in which big data has impacted cost management is by providing companies with greater visibility into their costs.This allows them to identify trends and patterns that may not have been apparent before, as well as to track costs in real-time [77].By having a more detailed understanding of their costs, companies are better equipped to make strategic decisions about where to cut costs and where to invest.Big data has also enabled companies to more accurately forecast their costs.By analyzing data from a variety of sources, including historical data, market trends, and other external factors, companies can make more accurate predictions about their future costs.This allows them to plan more effectively and make adjustments to their operations as needed.Overall, the impact of big data on cost management in accounting has been significant.By providing companies with greater visibility into their costs, enabling them to more accurately forecast their costs, and identifying areas where they can save money, big data has helped companies improve their profitability and remain competitive in an increasingly challenging business environment [78].

4-4-Sustainability Management
Sustainability accounting is gaining prominence as businesses seek to balance financial performance with environmental and social responsibilities.Big Data is also playing a critical role in sustainability management and accounting.By guiding the development of Design Science Information Systems (DSIS), it supports sustainable business practices and informed decision-making that aligns with long-term environmental goals [79][80][81].

4-5-Regulatory Compliance
The use of big data in accounting also has implications for regulatory compliance.With the increased availability and accessibility of data, regulatory bodies are likely to demand more detailed and timely reporting from organizations.Organizations that are able to take advantage of big data to provide timely and accurate reporting are likely to have a competitive advantage [82].

4-6-Ethics and Governance
The use of big data in accounting raises several ethical and governance issues.The collection and use of data must be conducted in an ethical manner, and organizations must ensure that they have appropriate governance structures in place to manage the risks associated with the use of big data [83].Organizations must also ensure that they are transparent in their use of data and that they comply with all applicable laws and regulations [84].

5-The Future of Big Data in Accounting
The future of big data in accounting is very promising.As businesses continue to rely on technology to streamline their processes, big data will play an even bigger role in accounting [85].There are a few key areas where big data will likely have the greatest impact in the years to come [86].
First, big data will enable more accurate and timely financial reporting.With large volumes of data coming from various sources, companies will be able to produce financial reports more quickly and with fewer errors.This will give management more accurate information to make informed decisions.Second, big data will improve risk management.By analyzing vast amounts of data, companies can identify potential risks more quickly and take steps to mitigate them.This will help prevent financial fraud and other losses.Third, big data will change the role of the accountant.As machines become better at analyzing data, the role of the accountant will shift from simply collecting and processing data to providing strategic insights [87].Accountants will need to become more tech-savvy and focus on interpreting data to provide valuable insights to management.Fourth, big data will lead to the development of new accounting products and services.As companies become more reliant on data, there will be a growing demand for specialized accounting products and services that can help businesses manage their data more effectively.This will create new opportunities for accountants and accounting firms [88].Finally, big data will enable more efficient audits.Auditors will be able to use machine learning algorithms to quickly analyze large volumes of data and identify potential issues.This will streamline the audit process and help auditors identify risks more quickly [89].
Another promising area of impact is intellectual capital accounting, where Big Data is enabling new prospects for capturing and reporting intangible assets.This revolutionizes how businesses assess and leverage their intellectual capital, providing deeper insights and enhancing strategic decision-making [90].
To summarize, the prospects for big data in the field of accounting are highly promising.The advancement of technology is leading to the rise of Large-Scale IoT Systems, Blockchain Technology, and Smart Contracts, which are bringing about a substantial transformation in the realm of big data in accounting [91,92].These technological advancements do not simply add to existing practices; they fundamentally transform accounting, introducing an unprecedented era of efficiency, accuracy, and transparency.This integration marks the commencement of a novel epoch in accounting, distinguished by enhanced functionalities, robust security measures, and innovative approaches to financial data management [93].Consequently, businesses will increasingly depend on big data to streamline their accounting procedures, detect risks, and offer valuable managerial insights.This will result in enhanced prospects for accountants and accounting firms, as well as improved efficiency and precision in financial reporting.

6-1-Research Gap
Despite the extensive discourse on the integration of big data in accounting, a conspicuous gap exists regarding the comprehensive synthesis of the latest advancements and challenges in this domain.Many studies have explored specific aspects, such as data analytics tools or the impact of big data on financial reporting.However, a holistic review encompassing the evolving challenges, emerging trends, and their collective implications for accounting practices remains limited.This review aims to bridge this gap by consolidating diverse literature, providing a comprehensive understanding of the contemporary landscape where big data intersects with accounting principles.

6-2-Goals of the Research
This literature review endeavors to conduct a comprehensive synthesis of existing research on the intersection of big data and accounting, meticulously analyzing prevalent literature to discern key trends, challenges, and advancements in this evolving domain.Moreover, it delves into the far-reaching implications of big data adoption within accounting spheres, examining its influence on pivotal aspects like financial reporting, auditing practices, and cost management.Additionally, this review seeks to contribute by unveiling critical research gaps, pinpointing areas necessitating further investigation and development.Through this comprehensive approach, it endeavors to provide a foundation for future research endeavors, steering the trajectory of scholarship in this burgeoning field.

6-3-The PRISMA Approach
The systematic literature review is a constructive approach that can be used to uncover, evaluate and synthesize thorough, significant research data on a particular topic [91].This allows researchers to gain a thorough, deep understanding of the studies and the conclusions they found.In addition, the use of this method reduces the possibility of bias as a result of a human-induced errors.Generally speaking, the process of the systematic literature review is as shown in Figure 1.

Figure 1. Flow of Systematic Literature Review process
The current paper, however, focuses on literature regarding Big data in the context of accounting and auditing using the PRISMA Protocol.PRISMA is an acronym for "Preferred Reporting Items for Systematic Reviews and Meta-Analyses", and it is a set of reporting guidelines that was first published in 2009.In order to demonstrate that a user may benefit from a systematic review, researchers need to provide a narrative that is crystal clear, comprehensive and accurate on why the review is undertaken, what researchers have achieved through this and what are the results.The PRISMA-2009 protocol has been updated since then and is now known as PRISMA-2020.The updated protocol revises the rules for reporting systematic reviews to incorporate recent developments in methods for locating, selecting, analyzing and synthesizing publications.With the aid of this comprehensive analysis, accountants and auditors will have a better understanding of the benefits, problems, threats and applications of big data in their professions.
An exhaustive study was carried out in order to collect pertinent material from a variety of sources, bearing in mind the following purposes and objectives: • To gain a general understanding of big data and big data tools in the context of accounting.
• To highlight the challenges and limitations pertaining the big data adoption in the accounting profession.
• To showcase the impact big data can have in accounting functions.

6-4-Research Questions Formulation Method
PICo served as the compass that directed the study issue.PICo is a tool that was designed in order to assist researchers in the process of formulating research questions.Pοpulation, Interest and Context are the three pillars upon which PICo was constructed.On the basis of these three ideas, the authors of this paper developed the primary research questions (Table 1), which consisted of accountants as the population, big data as the interest and the accounting profession as its context.

6-5-The Research Strategy
The research approach included three key components: the selection of keywords, the screening process and the eligibility checks.The topic of this study served as the impetus for the development of a list of keywords.For the purpose of this analysis the following terms were determined as useful keywords: big data analytics; big data in accounting; accounting professions; big data in auditing; and big data tools in accounting.This investigation looks at research on the use of big data in accounting that has been published on Scopus, Science Direct, Web of Science, Springer Link and Emerald Insight.The databases were chosen by taking into consideration the access credentials, the amount of time available and the reference lists of previously published papers on topics linked to the use of big data in the accounting profession, during the past 10 years.Furthermore, the chosen databases have published a significant number of publications that have been subjected to external reviews of quality.The criteria for the research are listed in Table 1.
The following constitutes the inclusion criteria (IC): • IC-1: Articles that talk about Big Data in Accounting; • IC-2: Articles published between 2013 and 2023; • IC-3: Articles published in English; • IC-4: Articles published in reputed journals.
Papers that did not meet set criteria were excluded from the research.A general summary pf the systematic literature review process under the PRISMA protocol is shown in Table 1 and Figure 2.

6-6-Analysis and Data Extraction Methods
The four steps listed below were utilized in order to search for and retrieve research data: • Article identification through database searches, using keywords "big data", "accounting", "big data tools", or "big data in accounting".Any duplicate entries were removed.
• Keywords, titles and abstracts were searched thoroughly, based on selection criteria, and irrelevant articles were excluded.
• Articles were fully analysed in order to determine eligibility and exclusion decisions were made with good justification.
• Cross-reference publications were screened for detailed research and a final decision on which articles to include in the systematic review was made.
Duplicate articles were removed.The selected publications' titles and abstracts were carefully examined for appropriateness.Additionally, the reference lists of chosen publications were searched for any new related research.Chosen publications were then looked at.

7-1-Description of Articles Used
In all, this research looked at 70 scholarly publications, that had been vetted by other researchers, and were sourced from reputable resources.Table 2 presents the total sum of relevant articles, as determined by reputable publishers.A time distribution analysis on big data in accounting is presented in Figure 3 (from 2013 -2023).All articles found between 2013 and 2023 were included in the review.An exponential increase in publications was noted in 2015 (11), in 2017 (12) and in 2022 (14).We concluded that 2022 was the year with the most relevant articles published.The main focus of the research is on the use of big data in the professions of accounting and auditing.

7-2-Summary of Articles Reviewed
Our research underscores a burgeoning trend wherein big data is increasingly finding application within the accounting and auditing realms, heralding immense potential for future advancements that could substantially refine decision-making processes.Within this scope, our study meticulously defines "big data" in the context of accounting, shedding light on the current landscape of big data technologies, their advantages, and inherent limitations.This contribution serves to augment the existing knowledge repository, enriching our understanding of how big data and its tools intersect with accounting and auditing practices.Notably, this exploration underscores the imperative for companies to acquaint themselves, at least to a certain extent, with the benefits, challenges, and constraints posed by big data in the accounting domain.As a result of this comprehensive literature review, the attention of accounting practitioners has been firmly directed toward the implementation and integration of big data strategies within their domain.
It's pertinent to note that our study does not hinge on data sourced directly from respondents; instead, it draws upon a wealth of information gleaned from reputable databases.Academic research papers spanning from 2013 to 2023 have formed the bedrock of our analysis, allowing for a comprehensive examination of the evolving landscape.The implications of our findings are far-reaching, carrying significant practical consequences as they underscore the pressing need for the accounting domain to embrace and leverage big data tools and strategies.Policymakers within the accounting sphere stand to gain substantial insights from our study, as it presents compelling data that advocates for the integration and adaptation of big data methodologies within the regulatory framework, thereby shaping the future trajectory of the field.

8-Conclusion and Future Work
This comprehensive review stands apart from prior studies, offering a unique synthesis of diverse perspectives that encapsulate the breadth of big data's impact on accounting.It transcends the narrow focus seen in earlier research by consolidating the latest advancements, challenges, and emerging trends within this domain.Undoubtedly, big data has the transformative potential to revolutionize accounting practices.Its utilization empowers organizations with invaluable insights, facilitating informed decision-making processes.However, alongside these opportunities, lie several inherent challenges and limitations demanding attention.To harness the full potential of big data, organizations must ensure adequate resources and expertise for managing and analyzing vast data volumes.Quality assurance and data reliability emerge as crucial factors, demanding meticulous attention.Moreover, the paramount importance of data privacy and security necessitates a top-tier position on the agenda of organizations employing big data methodologies [94].Addressing these challenges and limitations holds the key to unlocking the competitive advantage that big data promises within the realm of accounting.It's imperative for organizations to proactively confront these obstacles to fully capitalize on the strategic advantages offered by big data.By navigating these challenges effectively, organizations can leverage big data to align with their strategic goals and gain a substantial edge in today's dynamic business landscape.
Future research aimed at exploring the precise big data sources beneficial for accounting professionals and their analytical potential holds immense promise for reshaping accounting practices.This investigation involves a nuanced examination of various data repositories that can serve as rich reservoirs of information for accounting purposes.Financial transactions stand as a fundamental source, offering detailed insights into monetary movements, expenditures, revenue streams, and investment patterns.Beyond traditional financial data, customer interactions and social media platforms house valuable information on consumer behavior, market trends, and brand sentiment, providing a comprehensive view of customer preferences and market dynamics.Additionally, supply chain information and operational data can offer insights into inventory management, production efficiencies, and cost structures, contributing to strategic decision-making processes.However, the inclusion of non-traditional sources is equally pertinent.Sensor data from IoT devices or geospatial data can offer unique insights into logistics, asset tracking, and operational efficiency.Combining these diverse sources enables a holistic understanding of business operations, encompassing financial, operational, and external environmental factors.To leverage these diverse data sources effectively, accounting professionals need robust analytical methodologies.Advanced analytics techniques like predictive modeling, machine learning, and data mining can unlock patterns, trends, and anomalies within these vast datasets [95].For instance, predictive modeling can forecast future financial trends based on historical transaction data, while machine learning algorithms can discern patterns in customer behavior from social media interactions.Furthermore, integrating these disparate data sources into cohesive frameworks is crucial.This integration might involve employing data aggregation platforms or leveraging integrated software solutions capable of harmonizing and analyzing data from diverse sources.This synthesis allows for a more comprehensive analysis, enabling cross-functional insights crucial for strategic decision-making.However, alongside these opportunities lie challenges related to data quality assurance, reliability, and privacy.Ensuring the accuracy, integrity, and security of data becomes paramount.Future research needs to address these challenges by devising methodologies and frameworks that maintain data accuracy, ensure data integrity, and uphold stringent data privacy and security measures.Ultimately, the exploration of specific big data sources and the development of analytical methodologies tailored to these sources hold the potential to empower accounting professionals with a deeper understanding of business operations, facilitating informed decision-making, risk assessment, and strategic planning.

Figure 2 .
Figure 2. Diagram of articles included in the review based on PRISMA

Figure 3 .
Figure 3. Article time distribution

Table 1 . Systematic Literature Review under the PRISMA approach Topic Definition Journal Articles on "Big Data in Auditing" published between 2013 and 2023.
Big data in Accounting, Accounting professions, Big data in Auditing, Big Data tools in Accounting Identify Databases and proceed with search Scopus, Web of Science, Springer Link, Science Direct and Emerald Insight Article selection Articles published in English, in reputed journals, and in the context of Big Data and Accounting