Big data refers to access to extensive amounts of unprocessed (raw) and processed (structured) data from a broad range of sources. The data are often complex, due to the huge volume available, so sophisticated computer systems are used to capture, process, and analyze the data. Such tasks would be beyond the ability of humans without the use of technology to manage the process.

In general, business decision-making can be improved when there are large amounts of meaningful data available. Market analyses show that big data as a service market was valued at $12.74 billion in 2020 but is forecast to increase to $93.52 billion by 2028 (which represents a compound annual growth rate of 28.2%). The reason for this projected growth is that big data can help businesses in numerous interrelated ways, including:

• Making more informed business decisions, based on facts, trends, and logic.
• Understanding their customers in better ways, thereby supplying goods and services that meet their changing needs.
• Improving business activities and operational efficiency.
• Generating additional revenues and profits.

  Watch this short video to see how the health care industry in the US is using big data and data analytics to improve the lives of patients.

There are five key characteristics of big data, referred to as the 3Vs, developed by Doug Laney (2001), a management and technology consultant. He defines big data as:

• Volume - the large amount of data generated. Volume (and variety) can come from numerous sources, such as smartphones, tablet computers, streaming services, e-commerce databases, and social media platforms.

• Variety - the diversity or different types of data, enabling multiple perspectives and comprehensive insights to an issue.

• Velocity - the speed at which data are generated and stored, often live.

Two additional Vs were later added:

• Veracity - th extent to which the data are accurate, including the ability to separate out inaccurate data.

• Value - the extent to which the data are useful for supporting problem solving and improving decision making.

Value is a particularly important aspect of big data in today's highly digital and interconnected world. In this context, value refers to the worth of the data being extracted from the variety of data sources. Having endless volumes of data is of no real value to a business unless the data can be turned something meaningful and useful for the business. Hence, it is important to understand the costs and benefits of collecting, processing, and analyzing the volumes of data to ensure that they can be used by the organization.The sheer amount of data generate constitute the data sets that are necessary for data analytics and data mining.

In the modern and competitive corporate world, there is a growing expectation to use more scientific decision making, rather than methods that rely on intuition and gut feelings. Given the increasing complexities and widespread impacts of many business decisions, strategies based on scientific methods are easier to document and account for, especially if clear justifications are required.

Similarly, given the huge volume of data available, big data has revolutionized traditional market research. Implementing big data analytics can give businesses a competitive advantage as they gain information to improve strategic decision making. Using big data analytics also helps to boost customer acquisition and improve customer retention. For example, Netflix claims that it knows users so well that the company's retention rate is about 93%.

Some other examples of how businesses use big data in the real world include the following:

• Airline companies use big data to determine different prices to charge passengers on each day of the year, using dynamic pricing.

• Amusement park operators, such as Walt Disney World Theme Parks, use big data to understand visitor behaviour at its theme parks and hotels, so that it can offer an even more "magical" experience for its guests.

• Social media marketers can access large amounts of data for market research and market planning purposes in order to better inform their sales practices and improve promotional techniques.

• Banks use big data to deliver improved and more personalised services for their customers. Using data from bank statements and transactions enables the banks to knows a lot more about their customers, from what they like to buy, and how often, to where they go on holiday most frequently. Big data also enables banks to detect fraud.

• Car manufacturers use big data such as live GPS data from motor vehicles to improve traffic flow and reduce congestion. It is also used to predict and warn drivers about maintenance needs for their vehicles, such as repair and servicing schedules. Many insurance companies also use big data from a car's black box to make more informed decisions about risk management and insurance premiums.

• E-commerce businesses, such as Amazon, and online streaming services, such as Netflix, use big data for product recommendations. Amazon earns about 35% of its sales revenues from product recommendations.
• Energy companies use big data to optimize the generation, distribution, and consumption of energy in homes and places of work. This includes analyzing big data from power plants as well as monitoring and examining data from smart metres in residential homes to improve energy efficiency.

• Food delivery service providers, such as Uber Eats, use big data to make accurate forecasts of food delivery times for their customers, as well as meal recommendations.

• Healthcare providers use big data to track patient information, monitor pandemics, and improve medical research, e.g., big data is used by medical clinics to store and analyze electronic health records to identify patterns and predict health risks.

• Wealth managers and financial advisers use big data and data analytics to assess credit risk and inform investment decisions. It can also enable them to create personalized financial products and services for their clients.

Netflix uses big data to make programme recommendations to their subscribers