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DQ Blog Article What does good data look like?

What does good data look like?

Martin Doyle October 5th, 2021 Article
Blog

Conducting any form of research into data will likely turn up multiple blogs, articles and statistics on bad data and how it can impact your business. These articles will stress the importance of good data, but typically neglect to tell us what good data actually looks like.

In this blog, that’s exactly what we intend to do – show you what good data looks like, and how you can build it.

  1. It’s Complete

A good piece of data will be complete, meaning it contains all the information needed for its purpose.

To make sure your data is complete, you’ll first need to consider how you want to use it. For example, if you are planning on an email marketing campaign, you’ll only need information such as an email address, name, surname, title, and company name.

Things like a telephone number or address are supplementary at this stage, and so aren’t required.

  1. It’s Formatted Correctly

Incorrectly formatted data is one of the most common data complaints.

Fields such as telephone numbers, email addresses and postcodes will all need to be formatted correctly, with international codes being taken into consideration for telephone numbers.

  1. It’s Unique

Duplicate records are very common, particularly with customer data. People frequently use different email addresses or shorten their names, leading to the creation of multiple records for the same individual.

Cleansing your data of duplicates and consolidating that data into a Single Customer View, or Master Golden Record, will leave you with one record containing all the relevant information.

  1. It’s Consistent

It’s common place for the same data to be stored across multiple systems, such as your CRM, ERP and marketing services, but it can lead to different versions of the same data on each system.

Good data will be updated across all systems to remain consistent and ensure everyone using that data is working with the most up to date version.

  1. It’s Valid

This is arguably the most important characteristic of good data.

Valid data is data that comes from an authentic source and has been proven to be correct and up to date.

A good way to build valid data is to establish good data collection processes, purchase it from a trusted provider or use data management tools to validate your data for you.

DQ Global and Data Quality

At DQ Global, we have been helping organisations around the globe to get the most out of their data, driving growth, critical business insights and valuable analysis.

Our current suite of products is the culmination of 25 years’ experience in customer data, delivering essential data management solutions to our array of market-leading clients (link to case studies).

But we understand establishing good data processes can be time consuming.

Through our Data Improvement Discovery Sessions, you can arrange a no-obligation call to discuss your data quality challenges with our data quality experts. They can provide you with the tools and knowledge to start improving your customer data quality immediately, so get in touch today.

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