Define And Describe The Three Analytics Types Essay

Businesses give an analysis of the profit and sales also other business data to find a trend of popular sales and what is making the most money for the company. An example is if an item is usually sold out in days and making lots of profit and if an item is barely sales businesses would buy more of the popular product and less of the unwanted product.

My classmates, peers, and friends would describe me as diligent, focused, and friendly. Diligence shows the most when I’m doing something that I love or something that I want to complete. I show diligence every day at ballet, along with my hard work at school. Diligence shows not only because I know that I am expected to perform well, but also to impress myself. I find myself constantly looking at my work and finding all the miniscule details that bother me, even if it isn’t necessary. I tend to show my focused side more when I’m at school, ballet, or when I am under pressure. With my focused mindset, I find myself getting more done, and helping others out in any way possible. Finally, friendliness appears when I’m with classmates or meeting new people. If I’m participating in an event or something that I enjoy, my friendliness helps counter my fear of meeting new people, therefore making experiences more likeable.

The concept of Business analytics is a component of business intelligence, it has evolved in recent years and now in the for front center of business. With the growth of technology and the continuing improvement

Having data is not valuable but using data is. Analytic insights are changing the way corporates strategize and also redefining customer expectations. Analytics is the new differentiator between success and failure in the cut throat e-commerce and internet services based industry. The huge proportions of data generated from the increasing number of smart phones, the social networks and the ever more penetrating internet are automating customer centric marketing and other services. The idea is to predict what a customer may want to buy even before the customer realizes what they need. The techniques to achieve these results are broadly classified as Predictive Analytics.

Retrospective risk assessment deals with problems that have happened or problems that almost occurred. With this method, looking back on what caused the problem to occur or almost occur are assessed. Then ideas are gathered to help prevent these problems from happening again. This is where risk managers are essential to a healthcare organization. This process was created and is used today to lessen the chances of financial risks to the healthcare organization now and long-term. This is done by trying to limit the liability throughout the system of the organization, whether this is staff, goals, rules, equipment, or etc. This is a very complex process and is much deeper than finding a single employee that was involved and blaming them for the fault. With retrospective risk assessment the uses of analytics are extremely important to figure out what has caused a problem and what can be done to prevent it from happening again or any slight alternatives to the problem.

Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analysed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data.

The sections below go into greater detail about how organizations can use analytics as a competitive weapon to introduce new goods and services and support existing ones.

To compete effectively in an era in which advantages are ephemeral, companies need to move beyond historical, rear-view understandings of business performance and customer behavior and become more proactive(tableau). Predictive Analytics is the use of data science for audience profiling. Generic audience profiling involves determining specific characteristics of your target audience and creating specific personas to represent each type of person within your target audience. Predictive analytics is essentially the same process, but from a data perspective (koozai). Predictive analytics can be used in wide areas in the industry, it’s importance is not constrained to a particular domain and ranges from marketing, telecommunication, retail, banking, etc. For example, the telecommunication industry has noticed a high customer churn since the switching costs are slim to none. So telecommunication companies operating in this industry are looking for new ways to differentiate themselves from competitors in order to retain customers. By using predictive analytics as a solution to this problem, they would be able to understand the customer needs, requirements and retain them also allowing them to acquire new ones more effectively. With predictive analytics, companies can predict trends, understand customers, improve business, drive strategic decision making and predict behavior. A company named Cox Communications, the third largest cable entertainment and broadband

This has taken the competition in this ever changing globalized world to another level quite literally. There is no room for outdated or 'gut feeling' method of conducting businesses. Predictive Analytics is a real game changer and s here to stay. From inventory planning,

Business analytics, in a nutshell, is usage of the type of data that can help one analyze a particular business situation and decide how to improve it. Instruments used for such an assessment include statistics, and both quantitative and qualitative analysis, as well as predictive and explanatory modeling.

Prescriptive analytics, on the other hand refers to the exploration of these business activities happening in the future. Predictive analytics is used in the exploration of business activities that are more likely to happen in the near future in order to find relationships in the data that couldn’t otherwise be found with the use of descriptive analytics. These different analytics mostly focus on larger data, but can also be used with smaller data as discussed in Chapter 17.

Business forecasting is the process of studying historical performance for the purpose of using the knowledge gained to project future business conditions so that decisions can be made today that will aid in the achievement of established goals. Forecasting plays a crucial role in today 's uncertain global marketplace. Forecasting is traditionally

Broadly, there are two types of Analytics i.e. Business/Cube Analytics and Predictive Analytics. Business Analytics is a traditional way where historical measures (revenue, profit, loss etc.) available are extracted, transformed, modeled and stored for analysis. It is about getting insights on events that already happened. E.g. Year-on-Year sales report. In the contrary, Predictive analysis applies data mining and statistics on large volume of data for Forecasting, projecting, and predicting. E.g. KFC giving combo offer based on prediction of consumer’s possible purchase behavior to increase overall sales.

Descriptive statistics are entirely used to describe the sample under study. They are used basically to describe the fundamental characteristics of a given data. They offer simple summaries concerning the measures and the samples. When utilized together with simple graphics study, they form the heart of practically each quantitative study of data. This means that descriptive statistics utilized both

A descriptive research design was adopted for this research. According to (Cooper & Schindler, 2003), a descriptive study is concerned with finding out the what, where and how of a phenomenon. (Saunder et al, 2003) further assert that descriptive research is used principally to gain a deeper understanding of something. The descriptive research collects data in order to answer questions