The pros and cons of big data for businesses vary among global companies adapting to the transformation of data-driven technologies using AI (artificial technology). Data executives and IT staff hold the keys to driving success in planning, implementing, and executing efficient data systems. We discuss the advantages and disadvantages of becoming data-driven based on research and survey participants in this review.
The Beginning of Large Data Collection
The history of data collection dates to the 1950s after an American insurance company collected tons of data, approximately 600 in megabytes. Companies began experiencing higher volumes of information with tasks more complex using the existing software. It had an impact on production and was very time-consuming in processing financial reports and other information.
By the 2000s, Google exceeded the processing of data, with nearly 25 petabytes. Data collection grew continuously with technology advancements, especially in computers and cloud computation. It created relevance and increased the benefits of speed processing, storage space, and analytics. Today, the production of information is gigantic in growth, forcing large organizations to build big data frameworks for data collection, processing, and reporting.
Chief data executives and upper management use information/data collections from data systems to help them make valuable decisions for growth and profitability. Without a properly functional framework, analysis of data is impossible and unlikely successful. Executives contribute to the success of their organization by implementing techniques to create a data-driven environment, competitiveness, and to manage assets.
What is the Methodology of Big Data?
Big data refers to the study, frameworks, techniques, and tools of enormous data groups. Since 2012, organizations are discovering that extracted data holds value in analytics. Machine learning and AB testing are examples of tools used for data information analysis. Databases and cloud computing are appropriate technologies referred to big data.
Estimated Total Dollar Investment in Big Data Systems
A 2021 Big Data and AI Executive Survey produced by NewVantage Partners shows that 62 percent of participants invested over $50 million into big data. Most executives in the healthcare, financial services, and life sciences participated in the research. The percentage of companies actively investing in AI and big data is 99, and 91.9 percent are rushing investment initiatives.
Pros and Cons of Data Analytics Solutions for Businesses
Advanced Business Analytics
Artificial intelligence and big data are contributing to executives and managers creating a productive workplace environment. They must use an effective method in business analytics progressively for data structure and mining and then run it through a learning machine or algorithm. Corporations hire data analyst experts to build customed frameworks with data analytics functions.
Executives and analysts use the collected data for:
1. Providing insight on customers’ shopping behavior, sales patterns, and trends.
2. Increasing sales and net profits.
3. Decreasing expenses.
1. Improving customer services.
1. Monitoring products and services, leading to a higher rate in converting consumers into loyal customers.
Creates Competitive Existence in Local to National Markets
Analysis of data collection helps businesses to become more competitive in markets and create existence. Data and AI technologies allow corporations to keep their information constantly flowing in real-time, enabling professionals to make decisions quickly. When market conditions affect the entire economy, marketing executives seek opportunities in other prospective areas to become competitors.
Both AI and big data technology solutions help to analyze test results and simulate possible outcomes. They provide insights during new product development, pricing adjustments, or targeting specific geographical regions. Competitiveness is a part of a business plan for opportunities to increase sales and revenue.
Improvements in Customer Service
Data collection is advantageous for analyzing information from customers to gain a better understanding of their specific needs. Data analysts produce data for chief data executives to interpret and predict potential issues and errors within a customer relationship management system. What matters the most in the system is its supportability and competence in collecting, processing, and generating viable information.
Fraud and Error Detection Features
Rapid detection of fraud and errors in real-time helps to protect the company assets. IT security systems work simultaneously with big data and AI technologies to prevent fraudulent activities and avoid mistakes. The responsibilities of IT Security and Data Analytics teams are to ensure data and information are secure and protected.
Higher Production Performance
Companies and organizations rely on big data solutions to help them reduce operational waste and predict issues. A report published by Forbes in April 2021 covered productive results of combining AI and big data technologies. Research shows combining both technologies automate about 80 percent of human work and 70 percent of data processing.
Apache Hadoop, for instant, is a solution comprising tools for increasing analytical information production. Most solutions have frameworks built with features for creating analysis, detecting fraud, and storing and processing data. Some of the best benefits include higher workforce production and reduction in costs and wasted time.
While there are advantages of big data analytics, it has cons as well. Here are five disadvantages corporations are facing, according to the survey results.
Defining the Roles of Big Data Executives
The survey noted that difficulties are defining the roles of the data executives on their responsibilities and duties. Statistics from the NewVantage Partners survey revealed that 33.3 percent of businesses clearly define executive roles.
Investment Struggles to Meet Governance Demand
Data privacy and information protection governance are pressuring corporations and companies of all sizes to comply with state and federal laws. Governance demand consistency created financial struggles, especially after the Covid-19 pandemic. It had an impact on data management and data literacy in most organizations. Metrics from the survey reflect the transformation struggles of data-driven enterprises.
Useless Data and Information
Information collected on customers can contain a considerable number of errors and useless data for management and executives. Such data interferes with the accuracy of reports and results in ineffective strategies and making bad business decisions. It can slow the processes of information and become costly without the expertise of a chief data officer or analyst.
Expensive to Implement and Maintain Big Data Technology with AI
A well-established data system and AI are costly to produce, maintain, and store information by professionals specializing in IT and data science. Companies such as Amazon and Facebook spend millions of dollars to keep their data systems operating securely and productively. The businesses that invested in big data invested over $50 million, which was over 60 percent.
Data Breaches and Violations of Privacy Laws
Poorly designed frameworks of data systems jeopardize businesses’ ability to protect their customers’ private and confidential information and data. Companies are subject to paying hefty fines and investing more money to build an efficient data and IT system. A challenge for many organizations is preventing hackers and ransomware from cybercriminal activities.
Summary of the Big Data Advantages and Disadvantages
Big Data has its pros and cons in different areas, such as collecting, processing, organizing, and securing information. Research proves that organizations are adapting to the evolution of big data analytical solutions to ensure governance compliance and to analyze significant data collection. A high percentage of participating data executives acknowledged success in the department of data analytics.
Businesses should be aware of the disadvantages of big data if the system lacks efficiency, speed, and the proper tools. The investment is costly, however, an asset when the system is efficiently built and structured. Before companies implement a data technology system, consult with a data and IT expert.