Data standardization transforms data that enters your organization from disparate sources into a consistent format that meets your data classification standards. Standardizing data makes it easier to identify and correct errors and transform your data into a reliable asset that can be leveraged to improve your bottom line.
Your organization’s data is critical to your success. When your data is accurate, reliable, and formatted consistently, you’re able to operate efficiently and connect with customers most effectively. However, many businesses struggle to optimize the quality of their data. Data often flows into organizations from disparate sources in various formats.
When the data’s format isn’t consistent, it can be difficult to find and correct errors. These errors result in wasted money, missed opportunities to connect with customers, and excess time spent fixing data issues that could have been avoided.
Hi, I’m Rishi Patel from Experian Data Quality. Today I’m going to take you through the data transformation and standardization capabilities of Experian Pandora.
So we’re looking at the interface of the tool, and we’ve already loaded some data that sits in the repository under it. We’re going to briefly show how we can improve the quality of the data by potentially transforming it and standardizing it, and instantly see the results that we get from it.
Let’s look at the previous customer table and focus in on the telephone number. Here we can see we have telephone numbers of different formats containing parenthesis and hyphens. We can start by looking at how many formats we have in this column. Right click over here, and instantly format this data. We can see that we have 80 groups or formats for this particular table.
In order to standardize this information, I’ll start off by cleaning and removing the noise. I can insert a column over here; select the data cleanse function, and remove the noise. I can see the results in here instantly, and that is part of our prototyping. I can take this a step further and edit this transformation. Go to transformations, edit…and within our expression editor we have a whole host of functions here to transform and manipulate data.
The next thing I want to do is add in some dial code information. Within this table we do have the countries, so I can search for any country function and convert that country to a dial code. I’ll take that as an input, I’ve got the country name, and I’ll select the dial code. What I can then do is concatenate the information together. Taking that dial code, add in a hyphen, and our cleansed number. Now if you go ahead and profile that transformation, we can now see that we’re left with 7 groups, the dominant being a +44, most likely in the UK.
That was a brief demonstration, but I hope it gives you a good idea of the standardization and transformation capabilities of Experian Pandora.
Standardize data formats including structured and semi-structured data sets.
Transform and manipulate data with hundreds of built-in functions
Build your own transformation rules to meet your individual business needs
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