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What is a data join?

A data join, based on a similar field, is like connecting two pieces of a puzzle that share a common element. Here's how it works:

  1. Two Sets of Data: You begin with two distinct sets of data, each containing its own information. While these sets may be related, they haven't been combined yet. Spotzi users often employ this method to link their own data to geographical areas.
  2. Common Field: You identify a field or attribute in both datasets that is the same or similar. Spotzi commonly uses a geographical identifier as the common field, such as postal codes, municipalities, or other administrative boundaries.
  3. Matching Records: Subsequently, you match the records in both datasets based on the identified common field.
  4. Merging Information: Once the records are matched, you can merge the information from both datasets into a single, comprehensive dataset. With Spotzi, this results in a dashboard with data at the postal code level, for example.
  5. Better Decision-Making: By linking these two sets of data based on a shared field, you gain the ability to make more informed decisions. For example, you can use this information to personalize marketing efforts or optimize inventory based on historical sales data.

In summary, data joining based on a common field is about uniting two sets of data by finding a matching element. This process enables you to consolidate information, conduct more meaningful analysis, leading to improved decision-making and a deeper understanding of your data. It's analogous to combining pieces of a jigsaw puzzle to reveal the broader picture.

Connecting Data with Spotzi. Fast and Simple.

With Spotzi, we make the process of linking data to geographical areas even simpler. In fact, our database already contains an extensive collection of consumer data at various geographic levels. From demographic characteristics to consumer behavior data, you can effortlessly map your business data and generate valuable insights for your next campaign.

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