This is not new that technology and big data have become universal day-to-day operations of most businesses, nevertheless of size or industry. Data scientists, data analysts, and non-IT professionals with data analytics knowledge have become important in their organizations’ hunt to transform raw data into workable and actionable formats that can be used to identify trends, draw meaningful conclusions, and model future result.
What is data analytics in simple words?
Data analytics is the science of analyzing raw data to make conclusions about that information. The techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.
Data surround us | by the year 2020 about 1.7megabytes of new information will be created every second for every human being on the planet. In fact more data have been created in the last 2 year than in the entire previous history of the human race.
We define Data Analysis as the process of evaluating data with the purpose of drawing conclusion to address business question .An effective data analysis provides a way to search through large structured and unstructured data to discover unknown patterns or relationship.
Data analytics involve the technologies system practices methodologies database statistics and applications used to analyze diverse business data to give organization the information they need to make sound and timely business decisions .
That is the process of data analysis aims to transform raw data in not knowledge to create value.
What is the role of data analytics?
What is the role of data analytics? Data analytics helps individuals and organizations make sense of data. Data analysts typically analyze raw data for insights and trends. They use various tools and techniques to help organizations make decisions and succeed.
Data analytics affects business
Data analytics could vey much transform the manner in which companies run their business in the near future because the real value of data comes from data analysis .With the wealth of data on their hand, companies use data analysis to discover the various patterns of their customers investigate anomalities that were not anticipated forecast future possibilities and so on.
For example : with insight provided through data analytics companies could execute more directed marketing campaigns based on pattern observed in their data giving them a competitive advantage over companies the do not use this information to improve their marketing strategies.
Data analytics in Auditing :
Technology will enhance the quality ,transparency and accuracy of auditing .Data analytics is expected to be next innovation in the evolution of the audit and professional accounting industry .
No longer will they be simply simply checking the error material misstatement fraud and risk in financial statement or merely be reporting their finding at the end of the engagement .Now audit professional will now be collecting and analyzing the company data similar to way a business analyst would to help management make better business decision.
Data analytics is going to have exceptional effects on auditing financial reporting taxation and managerial accounting .
Data analytics also potentially has an impact on financial reporting. With the use of so many estimates and valuation in financial accounting some believe that employing data analytics may substantially improve the quality of the estimates and valuations.
Data analytics may also allow an accountant to assess the probability of a goodwill write down warranty claims or the collectability of bad debts bases on what customers investors and other stakeholders are saying about the company in blogs social media .This information might help the firm determine both its optimal response to the situation and appropriate adjustment to its financial reporting.
Tax in Data analytics
Data analytics valuable for its ability to help tax staffs to predict what will happen rather than reacting to what just did happen So data analytics predictive analytics predicting future like how much tax to be paid by the company.
Career options for Accountants
Here are some career options for accountants with strong data analytics skills:
Financial analysts use data analytics to assess the financial performance of companies, identify trends, and make investment recommendations. Your accounting knowledge will be valuable for understanding financial statements and ratios.
Forensic accountants investigate financial discrepancies and fraud by analyzing data and financial records. Data analytics skills can help you uncover irregularities and provide evidence in legal cases.
Management accountants use data analysis to provide insights to help organizations make strategic decisions. You can help businesses optimize their operations and finances.
If you want to focus more on data analysis, you can work as a data analyst in various industries, including finance. You’ll gather, clean, and analyze data to provide valuable insights for decision-makers.
Analyst: Business intelligence analysts use data to create reports and dashboards that help organizations understand their performance and make informed decisions. Your accounting background can help you interpret financial data accurately.
Risk analysts assess financial risks that organizations face. They use data analytics to model potential risks and develop strategies to mitigate them.
Internal auditors ensure that an organization’s financial records are accurate and compliant with regulations. Data analytics can help you identify anomalies and areas of concern more efficiently.
With strong data analytics and accounting skills, you can work as a consultant, helping businesses improve their financial processes, optimize their budgets, and make data-driven decisions.
Financial Planning and Analysis (FP&A) Analyst:
FP&A analysts play a crucial role in financial planning and forecasting. Your ability to analyze data can help in creating accurate financial projections and budgets.
Investment analysts use data to evaluate investment opportunities, such as stocks, bonds, or real estate. Your accounting background can help you understand financial statements and assess the financial health of potential investments.
To pursue a career that combines accounting and data analytics, you may need to enhance your data analytics skills through courses or certifications in data analysis tools like Excel, SQL, data visualization tools (e.g., Tableau, Power BI), and programming languages (e.g., Python, R). Additionally, gaining experience with data analysis projects, even within your current accounting role, can be valuable for transitioning into these careers.
Data analytics in accounting refers to the use of data analysis techniques to examine financial data, identify trends, anomalies, and insights, and make informed decisions in the field of accounting and finance.
Data analytics helps accountants and finance professionals make sense of large volumes of financial data quickly and accurately. It enhances decision-making, improves financial reporting, detects fraud, and optimizes financial processes.
Common data analytics tools for accounting include Microsoft Excel, SQL for data querying, data visualization tools like Tableau or Power BI, and programming languages like Python or R for more advanced analysis.
Essential skills include data analysis, proficiency with relevant software and tools, statistical analysis, critical thinking, problem-solving, and the ability to communicate findings effectively.
You can learn data analytics for accounting through courses, certifications (e.g., data analysis certifications workshops, and hands-on experience with real data analysis projects.
Data analytics in auditing can improve audit efficiency, detect anomalies or fraud more effectively, provide deeper insights into financial statements, and reduce audit risk.
Yes, data analytics can enhance budgeting and forecasting by analyzing historical data trends, identifying key variables affecting budgets, and providing more accurate financial projections.
Emerging trends include the use of artificial intelligence (AI) and machine learning for predictive analytics, blockchain for transparent financial data, and cloud-based analytics solutions for scalability and accessibility.
Job roles include financial analysts, data analysts, forensic accountants, management accountants, internal auditors, and various roles in financial planning, analysis, and consulting.