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using Big Data Analytics to crack extensive, diverse data

With the advent of the Internet Age, many businesses have built websites. These websites cater to a clientele that finds the internet a better alternative. The Internet, among other things, provides cheap and easy-to-access services to a broader range of clients. Many entrepreneurs have jumped on the bandwagon of the gold rush of the internet, creating websites and mobile apps. These provide services; ranging from ride sharing to messaging to online retail stores.

To meet the demands of their repeat customers, online businesses record their customer data and sales preferences on databases. Due to the size of the data, it has to be stored in data warehouses, using a network of servers to manage it. This data is helpful in suggesting a set of services and products in which a particular customer might be interested. Online businesses analyze the data, using a science called Big Data Analytics to analyze the customer’s preferences.

Big Data Analytics is the science of using advanced analytical methods to crack extensive, diverse data (“What is big data analytics? ” 2017). The data may contain different types; like streaming/batch, structured/unstructured, and various sizes. Big Data refers to data far from being managed and processed by traditional databases. It can come from multiple sources, such as social media, log files, transactional applications, online retail stores, etc.

Owing to its vast and varied usage, Big Data has many advantages and disadvantages (“Big Data pros and cons,” n.d.).


As its name suggests, Big Data has almost unlimited storage capacity for massive data. It can be accessed through the internet, from any place on Earth, through any device with internet available. And, it can be obtained at high speeds, thanks to the latest technologies available. Big data is most useful because of the valuable information it provides to its customers and potential clients.


While it has many advantages, it also has a few disadvantages. Big Data may sometimes provide us with irrelevant information, and it may be up to us, to separate the required information. Furthermore, security is a significant issue. Big Data may not provide high protection and privacy, and information might be leaked easily and cause harm to individuals.

Decision Making:

The advantages of big data seem to be rosy. It appears that using Big Data Analytics may be an excellent option for determining customer preferences. The technique helps a lot in decision-making. Notably, the companies that thrive on customer response require Big Data Analytics. There is also a tool called Accounting Intelligence Systems (AIS) (Staff, 2010). This device uses Big Data Analytics to analyze accounting-related data and decide on a company’s financial health. This clearly means that big data is used in various fields because of its benefits.


Big Data pros and cons. (n.d.). Retrieved October 10, 2017, from

Staff, I. (2010, November 14). Accounting Information System – AIS. Retrieved October 10, 2017, from

What is big data analytics? – IBM Analytics. (2017, January 12). Retrieved October 10, 2017, from //



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