Data blending enables the self-service join of a primary data source (e.g. corporate data) with one or more secondary data sources (e.g. local spreadsheet) which contain common linked dimensions.

Let’s use the following example to illustrate this feature: Data blending to join company products (CrossFit and Yoga) and census data. In this example we see that some neighborhoods in Los Angeles buy CrossFit products (lime) while others buy Yoga products (cyan).  We use data blending to join census data to learn more about these customers.

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In Lumira Desktop, join two datasets using a common linked dimension. First we add a new dataset, in this case a spreadsheet of census data which includes neighborhood, average education score and estimated income.  We link both datasets using the neighborhood dimension.

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Then use a chart to analyze the blended data. For example: CrossFit products (top bubble chart) appeal to a broader educational section of the population compared to Yoga, but the largest Yoga sales (bottom chart) also came from the neighborhood with the highest income per capita (Bel Air).

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Before the census data is blended, it seems both CrossFit and Yoga sales are quite similar. However, after the census data is added, users gain more insight into the two products.

“Did you know…” is a series of short blogs by the BI & Analytics Competence Centre, a global team within SAP engineering focused 100% on customer success. They are a useful reminder of Lumira hints, tips and best practices.

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