Unique ID: 2015097
| Division: | Office of Information and Regulatory Affairs |
|---|---|
| Issue Date: | February 13th 2019 |
| Last modified: | February 22nd 2019 |
Cost: FREE
U.S. household food purchases and retail food sales
Using retail sales data for household food purchase information
Statistical Area
Project Sources
| Type Of Institution: | National statistical office |
|---|---|
| Big Data Source: | Scanner data, Health records |
| Region: | North America |
| Country Area: | United States |
| Id Country Regional: | country |
Partnerships
| Data Providers: | Intermediary Big Data provider |
|---|---|
| Other Partners: | Academic institute |
Accessing Data
| Data Access Rights: | Only for this project |
|---|---|
| Intermediary Comments: | Private U.S. company IRI sells the data under a custom agreement. University of Chicago's National Opinion Research Center (NORC) hosts the data and software and provides access to approved research collaborators. |
| Data Access Comments: | Many research projects are under an umbrella agreement regarding appropriate access and disclosure. |
Data Coverage
| Data Coverage: | Only a portion of all data |
|---|---|
| Coverage Geo Pop: | Whole country / high % of market |
| Cost Implication: | Commercial |
| Cost Comments: | Data purchased from private market insights vendor. |
| Coverage Period: | 2008-2014 |
Data Quality
| Quality Framework: | Quality of source/input |
|---|---|
| Quality Aspects Evaluated: | Privacy and Security, Accessibility, Relevance, Institutional/Business Environment, Validity, Accuracy, including selectivity, Coherence, including linkability to other sources |
| Validation Comments: | Summary data are compared to results from other sources and projects, and detail data are compared to other source data. |
| Quality Framework Comments: | The evaluation process includes both quantitative and qualitative components. |
| Data Quality Concerns Comments: | Dozens of checks are run to identify data issues, including gaps, duplicates, outliers, and various anomalies. |
Methodology
| Methods Used: | Traditional statistical methods |
|---|
Technologies
| Technologies: | Column store database, Spreadsheet, Other, Hadoop Clusters |
|---|---|
| Technologies Comments: | SAS, Stata |
Other
| Income Level: | High-income |
|---|---|
| Iso: | US |
| Timeframe To Produce Indicator: | NA |
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