Data Sampling and Error Rates in Selected Audience Manager Reports data-sampling-and-error-rates-in-selected-audience-manager-reports

A summary of the sampling methodology used for some reports, sampling error rates, and a list of reports that return information based on sampled data.

Data Sampling Ratio data-sampling-ratio

Some Audience Manager reports display results based on a sampled set of the total amount of available data. The sampled data ratio is 1:54. For reports that use sampled data, this means your results are based on 1 record out of every set of 54 records.

These reports use statistical sampled data because they need a tremendous amount of computing power to generate results. Sampling helps strike a balance between reduced computational demands, maintaining system performance, and providing accurate results.

Error Rates error-rates

Errors can occur in reports that generate overlap data. An error is defined as the percentage of records that:

It’s important to note that our tests and models show that the error rate decreases in an inverse proportion to the number of records in your data set. Data sets that have a lot of records generate fewer errors than sets with a small number of records. Let’s look at this assertion in a more quantitative manner. As shown in the following table, for a set number of records, 95% of your report results will be below a specific error rate.

Uso de la metodología de muestreo Minhash minhash

Basado en la metodología de muestreo Minhash, Audience Manager usa un nuevo método para calcular los estimadores de rasgos y segmentos sobre un boceto de datos hash de permutación única. Este nuevo método produce una variación menor que el estimador estándar para la similitud de Jaccard. Consulte la sección siguiente para ver los informes que utilizan esta metodología.

Informes que utilizan datos de ejemplo reports-using-sampled-data

Los informes de Audience Manager que usan datos estadísticos muestreados y la metodología de muestreo Minhash incluyen: