What is Big Data and why it is important?
“Big data” is a relatively new term that describes the large volume of data that inundates a business each day. However, it’s not the amount of data that’s important, but how organizations interpret it. Big data can be analyzed using artificial intelligence (AI) to generate insights into better decisions and strategic business moves.
Big data is typically characterised by the four “V’s”:
Volume: Organizations collect data from a variety of sources.
Variety: Data comes in many formats and from sources (i.e., machines and people).
Velocity: Data is generated quickly and constantly.
Veracity: As big data is sourced from many places, the quality and accuracy must be tested.
Big data analytics tools have changed our daily lives significantly and affect organizations across all industries. It plays a very important role in any business. With big data, you can effectively present and analyze issues to achieve your brand’s goals.
When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:
-Optimizing business decisions through data-driven insights.
-Gaining a better understanding your customers’ needs.
-Determining the causes of failures and issues.
-Detecting fraudulent behavior before it affects your organization.
-Generating additional revenue by selling big data insights.
What is Big Data Analytics and why does it matter?
By definition, analytics is the discovery and communication of meaningful patterns in data. For businesses, analytics tools help optimize key processes, functions, and roles.
Big data analytics examines large amounts of data to uncover hidden patterns, correlations, and insights. With the evolution of technology, it’s now possible to analyze your data and get answers almost immediately. Speed and efficiency are the main benefits of big data analytics tools.
Organizations can use analytics to improve the efficiency and effectiveness of decisions and actions. Big data analytics helps organizations harness data and use it to identify new opportunities.
Tom Davenport, the director of research at the International Institution of Analytics, interviewed more than 50 businesses to understand how they used big data and summarized the information in his report “Big Data in Big Companies”. He found companies found value in the following ways:
-Big data technologies can reduce data storage costs.
-The ability to analyze information immediately creates better decision making.
-Big data analytics allows companies to better understand their customers’ needs and provides insights into new products.
Pros and Cons of Big Data
No emerging technology is without its strengths and weaknesses. Enterprises report multiple advantages of big data such as:
-Increases business/IT agility
Another common use of big data analytics is in fraud detection. Big data analytics systems are excellent at detecting patterns and anomalies.
Although there is no doubt the big data revolution and AI have created substantial benefits for businesses, there are also risks that go along with using big data. While implementing big data analytics initiatives, many companies have reported significant challenges such as compliance, data quality, and rapid data changes.
Hiring or training data scientists and big data experts can also increase costs substantially, and the process of acquiring big data skills can take considerable time.
Despite the risks big data sometimes brings, it’s here to stay so companies should be aware of the potential risks in order to embrace it.
The role of Big Data Analytics in Payroll
Errors in payroll departments, no matter how small, can create major problems with significant cost implications for multinational organizations. Big data provides the ability to track trends over time, which can help organizations and human resources departments identify areas for improvement and earn significant savings.
Predictive analytics and data analysis of the payroll department can provide accurate yearly forecasts, which can help manage budgets and cash flow in times of change or growth.
The right analysis of payroll data can inform future strategies and improve hiring practices.
Payroll data often shows the correlation between compensation and performance, providing insight on how to attract and retain top talent. Recent research revealed around 48.4% of Fortune 1000 companies are now achieving “measurable results” from big data ventures.
Getting consistent, high-quality data is key and is still a challenge for many multinational organizations. A good global payroll solution will offer a real-time data collection and provide full visibility across countries.
Payslip is a Global Payroll Management Software solution that provides centralized process control, systemized data protection, and vendor management to international employers. Payslip reduces global risk and delivers clear business intelligence on a significant company cost.