Nielsen Holdings is a publicly traded, multinational data measurement company - an industry leader in analyzing consumer behavior in terms of both media and physical consumption. Nielsen helps retailers, product creators, and advertisers to improve sales efficiencies by better tailoring product content to what consumers most desire.
Accessing the Nielsen1 Dataset
The Nielsen1 dataset is contained within the Walton College of Business's Enterprise Systems.
The dataset can be accessed with SQL queries within the University of Arkansas's Remote Desktop environment. The best way to access the dataset would be within the University's Teradata SQL Assistant software or Microsoft SQL Management Studio (Systems).
Once an account is obtained, the Nielsen1 database can be queried as fit by the user.
Access To This Dataset
Access to this dataset is for educational use and Systems Access must be requested and approved prior to use. Once access has been approved, the Data Dictonary and Entity Relationship Diagram is available by logging into the requested system and selecting the Instructions tab.
Note: By legal agreement, It is forbidden to download the data from the University of Arkansas systems. This will be strictly enforced.Request Systems Access
Behind the Data
Nielsen has two major divisions: "What Consumers Buy" and "What Consumers Watch". The "What Consumers Buy" division analyzes data from external retailers to analyze trends in consumer purchasing patterns across various markets. The "What Consumers Watch" division analyzes what media content, for instance television programs, the general public consumes over time.
The Nielsen1 dataset is best used for analyzing general sales trends for product groupings. It contains detailed information for how the target retailer performed in specific products, in comparison with competitor retailers and previous year sales periods. The dataset can examine how the target retailer has performed in increasing both gross sales and market share for given products over time. The Nielsen1 dataset furthermore lists sales resulting from sales promotions for each product; such knowledge would be useful for analyzing which sales promotions were effective and what products require better promotion strategies.
The Nielsen1 dataset contains summary sales data circa 2012 for a major retailer (think a Walmart or a Target) in the United States sales area. Sales data is listed in unique records for individual products (ex:12 pack of Coca-Cola cans). Each unique product contains company owner information and general product group (Ex: alcohol). The dataset lists the sales data in various time slices for each product (Ex: Weekly, Quarterly, and Annual sales periods). The dataset furthermore contains comparisons of the target retailer's sales with both previous year sales and aggregated sales of competitor retailers.
The target variable for Nielsen1 datasets studies would likely be the variable "Dollars". The "Dollars" variable contains the total sales for a given product by the target company in 2012. Using the "Dollars" variable as the target allows users to analyze what effect input variables have upon total sales for a given product.
Useful input variables include "Dollars_PY", "Dollars_RM", and "Base_Dollars". "Dollars_PY" lists the total sales amount for the target retailer in the previous year sales period; this would be useful for making year over sales comparisons for products. "Dollars_RM" displays the total sales amount for all companies' exterior to the target retailer. This variable would be useful for assessing market share by the target retailer for a given product.
"Base_Dollars" lists the theoretical sales figures a given product would be expected to raise in the absences of all sales promotions. Such a variable would be useful for assessing the effectiveness of sales promotions.
These variables are but a few of the overall variables for the Nielsen1 dataset.
|Table Name||Time Frame||Rows||Attributes||Size (GB)|
|PERIOD||1/1/1900 to 1/1/2199||149||14||0.001|
|Platform data is currently available: Yes|