username: gsteigerwald
email: glenn.steigerwald@temple.edu
Team member : Xiao Liu

E. All of the above

- Glenn Steigerwald
- Senior MIS Major
- Internship at Interactive Commerce Group, Lamps.com

My time spent at ICG was great, all of the employees are great people and I could not have asked for a better place to be at. After my internship is over at the end of the summer, I will be working part-time doing […]

The skill that I have leveraged the most from class was definitely from MIS 2502 regarding databases and SQL. That is pretty much all I have been using during my internship and have increased my skills in these […]

When I first started working at ICG, I noticed that the overall attitude of the company is laid back, just as long as you get your work done. They are great people and like to joke around which makes the […]

Like many other places, here at ICG you must have an overall knowledge of the e-commerce world and how it operates. I’ve found that the most important skill that I need to know is SQL. I learned it in MIS 2502, […]

Hey everyone, I will be working at Interactive Commerce Group/ Lamps.com/ Payrollshopping.com as a Summer Associate Intern. I will be migrated Microsoft SQL server data to a new platform, developing queries used […]

1. Support is the probability that customer has both of the products that are being analyzed.
Confidence is the probability that a customer has one product given that they have the other one.
Lift is the […]

2. SpotCrime uses OLAP analysis because it only shows the past crimes that have been committed. It doesn’t attempt to predetermine where future crimes may occur.

1. Classification is placing data into groups based on the data on the attributes of the entity.
Clustering is grouping the data so that they will be similar to one another and different from elements in other groups.

1. Classification is determining what group a data element belongs to based on that data’s attributes whereas clustering is grouping data so that data elements will be similar to one another and different from […]

1. The metrics that data mining software has to deal with is the probabilities of the outcomes that result from the data and information that you put into the decision tree.

The issues that the data mining […]

Data mining is the analysis of large quantities of data in order to discover patterns about the data that was previously unknown and potentially useful information from the data.

Data mining is not sales […]

1. The data that would be valuable to electoral candidate would be the information that they are gathering from their Facebook app as well as the qualitative information they are receiving.

A. Choose the business process – determined by the questions you want to the answer about your organization, what your data cube is about.

B. Decide on the level of granularity – level of detail for each event […]

The key objectives are:
– extract data from the operational data store
– transform the data into a format that is able to be analyzed
– load the data into the analytical database

The key issues are:
– data consistency (same format)
– data quality (missing data, incorrect data, information needed not there)

2. The SUM() function returns added values of an expression, mainly used for columns.

1. The command DISTINCT is used to retrieve unique values.