Big Data Analytics

The following sample Information Technology essay is 630 words long, in MLA format, and written at the master level. It has been downloaded 1087 times and is available for you to use, free of charge.

The CAIS article explains what the main business objectives of big data analytics are, and what the main challenges are risks are in this field. First, big data and analytics are defined by these terms because of the volume that the data takes up in a company. Big data involves high volume, high velocity, and high variety, and these can complicate how a business operates. Analytics has three different meanings, including descriptive analytics, predictive analytics and discovery analytics. Combined with data, business uses these terms in order to predict the outcomes of their companies and maximize profits.

One of the examples in the tutorial explained how a company can use big data analytics to their benefit and detriment. When Target used big data analytics to determine which of their customers were pregnant, in an attempt to market their products towards them, this lead to a scandal. By comparing the purchase history of women with baby registries at their store and the rest of their customer base, the target used big data analytics to cross reference the products purchased and sent people with a similar purchase history baby-related coupons. While not illegal, this use of data made many feel uncomfortable. Companies risk intrusion of privacy when utilizing these methods.

The benefits largely outweigh the costs. Big data analytics allows companies to research their client base and create ads that would interest them the most. If I was creating an ad company for my industry, which is currently retail, I would use to tailor sales to specific clients that are more likely to shop during specific periods of time. For example, by using data throughout the years and looking at sale patterns, it is easy to trace when a customer is most likely to purchase an item. By creating a promotion for this item at this time, big data analytics can increase revenue.

Using an ERP, or enterprise resource planning, the system in a business can be a useful resource if used correctly. An ERP contains most parts that are necessary to run a business: Planning, purchasing, inventory, sales, marketing, finance, and even human resources. The ERP tracks the needs of all of these departments and creates a functional tool that a company can use to work with big data analytics and maximize profits. Without an ERP, each department needs its own software system in order to organize this kind of information. An ERP works as an umbrella system and allows systems to communicate with each other from different departments. This creates a healthier business and organization system. When used correctly, an ERP system creates a highly functional business. However, often, a company does not need an ERP or uses their ERP system incorrectly. Using it incorrectly leads to an increase in cost running, and cuts into overall profits.

To use a retail business as an example, an ERP can help the various departments communicate with each other. If sales are doing well, the ERP can allow for the finance department to contact the HR department in order to schedule more employees to cover the increase in business needs. The marketing department can use the ERP to keep track of customer trends that are being tracked by the sales department. The ERP allows a business to understand why it is important to stay interconnected. A good business operates like a machine, and the ERP acts a control for the machine and allows the business to be successful if used properly.

Businesses are using information technology in new methods in today’s market, in order to stay relevant and increase sales. Big data analytics and ERPs allow businesses to stay functional. As long as both are used responsibly, a business should be able to thrive.