Don't take clean data for granted

By Tristan Anwyn

Have you cleaned up your data recently?

Whether you are harnessing big data for customer insights or maintaining a mailing list, the quality of your data matters.

RELATED TOPIC: Are you protecting customer data or exposing it?

Inaccurate data means inaccurate results and potential mistakes. It's clear that your business data needs to be clean and relevant at all times, but what can you do to keep your data clean?

Know what you are harvesting and why

A clear idea of what data you are collecting, and why, will help you to keep your data relevant.

  • Say for example you're building a mailing list. Ask yourself:
  • What information do you need about each person who signs up?
  • Will just their name and address suffice?
  • Do you need details about their industry?
  • How about the products they are interested in?
  • Do you need any other demographic data?

A clear idea about your data needs and aims will help you to stay relevant and weed out unnecessary data.

Standardize data entry

As the article "6 Tips for Keeping Your Data Clean and Relevant" says, it's important to standardize data entry formats companywide. Every person who handles data should be given clear guidance as to how to enter data.

Automating the process where you can will help. Automated data entry cuts down on the risk of human error and helps keep things consistent business wide.

Decide who is responsible

Allocate a staff member to be your data steward. Having a responsible person will eliminate the tendency for staff members to assume someone else is responsible, with no one taking ultimate responsibility.

Make sure your allocated person has the necessary training and knowledge to understand what you need from your data, and from them. Set out what they will be responsible for so they know what to focus on.

Examine your data stream

To keep your data clean, set aside time to do a proper walk-through of your data stream.

Start at the beginning and look at:

  • Where data is coming from
  • How it is being harvested
  • How it is being entered
  • How it is being used and applied
  • Who is responsible for every stage?

For every point, consider what errors, variables or duplications could be slipping through. By breaking the process down, you can reduce the chances for error at every stage.

Eliminate variables

Too many variables can play havoc with your data, leading to unclean data and inaccurate results. The more you can eliminate variables, the better your results.

As discussed above, standardizing your data entry and automating where you can will both help to cut down on variables.

Examine where your data comes from so you can see how data is gathered and how much room there is for variation.

Narrow your focus

A focus that's too broad can add to your data problems.

If your remit is too broad, it's harder to grasp what data you need, and how you need it to be delivered.

Whatever your reason for entering data, get your aims clear first.

Know exactly what you need and where you're going to get it, so you can eliminate the rest and keep your data clean.

Test your results

If you want to know how clean and useful your data is, you'll need to test your results regularly. Make reviewing and testing your data a regular business task.

If you find inaccuracies in your data, plan and implement a solution and then test again. Keep testing, cleansing and repeating to keep your data in tip top shape.

If you want to make the most of the data available to your business, follow these steps to keep your data as clean and relevant as possible.

RELATED TOPIC: Some small Canadian companies big on data

About the Author: Tristan Anwyn writes on a variety of topics including social media, SEO that works, and how to use data to improve your business.

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