5 Things Are Destroying Your Data – But There are Tools That Can Help

753
3D visualization of big data in the form of databases and the table structure

There is a reason this point in history has been called the Information Age. It is estimated that as a global society, we create more than 2.5 quintillion bytes of data each day.

Data is everywhere

Innovative ways to utilize this information are invented almost daily. Search engines comb the data to determine which websites are credible and which are not. Geocoding allows us to use existing data to find the precise location for deliveries, risk assessment and more. Marketers use data to send highly personalized ads through social media and email. City planners use big data and geospatial information systems to determine where to place public transit, roads and parks. The list goes on and on.

Data allows businesses to reach new customers, identify potential employees and make better financial decisions. However, this is only true if the data is trustworthy to begin with.

As useful as data is, it has limitations. The cost of bad data has been estimated to be between $8 million and $15 million per year. That cost continues to climb as the sheer volume of data increases. And as artificial intelligence gets better, the speed at which we process and monetize information makes it more crucial than ever to start with clean data.

Why validating data is key

There are a variety of ways data can be corrupted and, therefore, useless. Let’s review some of the most common ways that data entry goes wrong.

  1. User Error

Customers obviously know their own addresses, phone numbers and emails, but when quickly entering their data in the process of checking out or downloading a freebie, accidental errors are bound to happen. Whether hitting two adjacent keys at the same time or simply spelling a street name incorrectly, the outcome is poor data.

  1. Reversed Entries

Data is only as good as the fields it occupies. If information appears in the wrong column or row, the resulting analysis will be flawed. Something as simple as city and state names being transposed or something as drastic as numbers being misallocated will create significant problems in your data.

  1. Voice-to-Text Transcription

While voice-to-text translators are extremely valuable for both accessibility and productivity, the technology still has some kinks to work out. Anytime data is input through a voice mechanism, it is worth double-checking for errors.

  1. Repeating Data

More data isn’t always better––sometimes, it is just more. Repeat data, such as the same address listed twice or a doubled-up equation does not add to the value of the information, it detracts from it.

  1. Missing Elements

Just as repetition causes havoc, if a piece of information is left out, you are left with an incomplete data set. If the detail is important, like a street name or email domain, the data you collect from users will not help you interact and build a relationship with them.

Fortunately, despite the myriad of ways that simple errors can disrupt data management, verification technology has risen to help sort things out.

There must be standards

For data to be truly usable, it needs to be standardized, complete, correct, and current. Doing this manually would take hundreds (or thousands) of hours of work, and the end result would still be imperfect. Subscribing to a data verification service can help cut that down to just minutes, depending on the size of the database. Through well-ordered computer code, information can be cross-checked for errors, cleaned, and returned in record time.

It is not enough to verify your data once. Remember, an unfathomable amount of information is produced every minute. Things change all the time. Email addresses come and go, people move or change jobs, research is updated, etc. To maintain a clean dataset, it’s important to validate the information on a rotating schedule––every three months or so.

The reality is consumer data entry mistakes or non-standardized information are fairly simple problems to solve using modern tools. Choose wisely––a bad validation service can set you back instead of pushing you forward. However, tried-and-true services with access to authoritative sources can reduce costs, save time, decrease returned mailings, and, ultimately, create more happy customers.

Subscribe

* indicates required
Previous articlePhilipp Wolf
Next articleIra DeWitt
Kiersten Nelthorpe is a software and data engineer at Smarty, the world champion of location data intelligence. Kiersten specializes in backend API design and data engineering. Prior to her work with Smarty, Kiersten worked for other industry leaders such as Microsoft and Vivint. Kiersten is passionate about inspiring more women to consider a career in tech, and is the founder and CEO of Multi Threaded, which aims to increase the visibility of women in tech through tech fashion. Kiersten holds a bachelor’s degree in computer science from Brigham Young University.