Harrah’s script
Good evening everyone. I am Shixin. Today my group member Na and I will talk about a data mining case study about Harrah’s. In this presentation, we will introduce the company background at first, and then tell you the company’s objective. After discussing the current resource and application, we will come up with the method improvement. In the end, we will make a summary. Firstly, let’s look at the company background.
Harrah’s is the world’s largest casino company. It is an entertainment company that has business interests in casinos, food & beverages and hotel rooms. By 2010, Harrah’s has already had 48 properties, more than 3 million square feet of casino space and over 38,000 hotel rooms.
Here are some pictures of Harrah’s.
Although Harrah’s is the largest one, it faces pressure from its competitors all the time. Harrah’s has a longer history and more diversified geographic locations than others. It is not very practical to spend a large proportion of their budget in property development as its competitors do so Harrah’s aims to boost the frequency without increasing much budget.
So what resources does Harrah’s have currently? Harrah’s has a data base collecting information from national network. There are two types of cards. Application card contains the basic information such as birth date and home address. Reward card keep track of transactions, such as customer play preferences, where they like to eat in the casino and whether they stay the
DATA MINING Data mining has emerged as an important tool for identifying useful information from data in almost all industries. Industries are using data mining to increase revenue and reduce costs. According to Seidman (2001), “Data mining is particularly valuable for organizations that collect large quantities of historical information. Banks, insurance companies, credit card companies...use this technology to derive critical information from large, unwieldy data samples.” (p. 6). “We…
PART 1 - DATA, TEXT, AND WEB MINING TECHNICAL REPORT 1 INTRODUCTION The purpose of this report is to examine the different types of mining and provide insight into their applicable use and relevance. It also provides a number of notable uses for each type of mining along with some personal reflection from the author on the implications of mining on privacy and ethics. 2 BACKGROUND Turban, Sharda and Delen (2011) define data mining as “a term used to describe discovering or mining knowledge from…
Abstract- Outlier detection is an active area for research in data set mining community. Finding outliers from a collection of patterns is a very well-known problem in data mining. Outlier Detection as a branch of data mining has many applications in data stream analysis and requires more attention. An outlier is a pattern which is dissimilar with respect to the rest of the patterns in the data set. Detecting outliers and analyzing large data sets can lead to discovery of unexpected knowledge in area…
What is data mining? How can it be integrated into the business strategies? Data is collected from different operational databases, this data is limited in scope and therefore is used mainly for transaction processing When the summarized data from different departments within the company is collected it is stored in a data warehouse in a multidimensional database. The information that can be pulled from this data is used to support decision making. However the way the information is stored in…
Abstract Simply collecting data for research is nearly a faux pas in today’s competitive web-market. Analysts are now looking toward the predictive analytics of association discovery in web and data mining, to find Business Intelligence of clustering sub=populations while eliminating errors to keep collected data valid. In the midst this data crunch are fears of lost privacy. Do not fear. Creative innovations are bringing mash-ups to our diversity. Data Analytics Report Useful information…
Assignment 4: Data Mining Data mining is consider analyzed data-collect from different aspects and summary that is transformed into useful information. Companies does this Predicive analytics is a predictor which is measured per customer. For instance, recency, which prefers to the past customer to recent customers.there will be a higher value from past customers then present. "That means that if you contact your customers in order of recency -- first, call the most-recent customer; next, call…
Data Mining. •Data mining has been defined as "the nontrivial extraction of implicit, previously unknown, and potentially useful information from data" and "the science of extracting useful information from large data sets or databases" •Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. •Data mining tools predict future trends…