Experian Pandora’s data cleansing and enrichment capabilities help you ensure data is accurate, complete and fit for purpose.
With hundreds of cleansing capabilities, Experian Data quality can help you automatically detect data quality rule violations across your data landscape and eliminate any defects at the source.
The enrichment functionality of Experian Pandora allows you to append additional information about your customers or prospects from Experian’s vast reference data.
The video below is a brief demonstration of Experian Pandora’s cleansing and enrichment features.
Hello, I’m Rishi Patel from Experian Data Quality. For this video, I’m going to take you through the enrichment capabilities of Experian Pandora.
Looking at our customer data, there are two ways we can enrich this information. The first is utilizing the data itself, and adding some insight into it. Let’s look at first order date. Here we have some date information and lets say we want to find out how long it’s been since that first date. We can insert a column and look at the date functionality and add in a column that is the age in years. Now we’ve enriched this information with the number of years it has been since that customer first placed an order.
Another way we can look at this is the address information and our enrichment capabilities using Experian’s reference data. We have address information and lets say we want to clean the US addresses and add some geocodes. We can keep this selection and add in a few columns around validation and enrichment.
On the screen here, we can select which columns we want to clean and which columns we want to standardize an output. In this case, we will add in the full address information. We’ll also take in latitude and longitude values. We can have a look at our cleaning results and add in what action was actually taken on this address, as well as how confident we are in it. With this, we can kick off the process and see those results instantly.
In this example, we’ve got some cleaned and standardized addresses, we’ve included the ZIP+4 code, we’ve also got the latitude and longitude values, as well as reasons for addresses being cleaned or not. At this point, I can now choose to save these results as a table or a drilldown, or I can export it as a file and pass it on to whoever needs this data. In addition to saving this data or exporting it, it can also be automated in the entire process, so any time we have a new set of data coming in, we can automatically cleanse and enrich the data as we’ve done right now.
That was a brief demonstration, but I hope it gave you a good idea of how Experian Pandora can help enrich your data.
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