Treat your data like an asset – Not an inconvenience

Data Science   |   
Published September 28, 2016   |   

How do you look after your valuables? Do you use a safe deposit box or a postcode marker pen? You probably have the software installed on your smartphone to track it if it gets stolen, and no office is truly secure without CCTV.
Taking care of business assets is key to managing profit and growth, yet many businesses don’t protect their data in the same way they protect tangible assets. Data may not be an obvious asset, but that doesn’t make it any less valuable. And it shouldn’t be seen as an inconvenience you can ignore.

Why data matters

Your business relies on data to drive every part of its operations.
Businesses are currently investing millions in implementing and managing CRM systems. We know that our customers matter, and we’re beginning to put tools in place to manage and nurture relationships. Without the data we hold – and the information we derive from it – your people would not be able to do their jobs.
But data quality deteriorates as the months and years go by. You might have the most meticulous customer-facing staff in the world, and the best data storage processes you can afford, but you still won’t be able to protect data from natural decay. It’s impossible.
Once duplicate records creep in, your statistics and reports will become less reliable. If different systems are integrated, you may end up with incomplete records and inaccurate results. A date field might have different formats depending on the person you’re looking at. Those inconsistencies can cause single records not to save without error. Your data becomes problematic, inconsistent, unstructured and unreliable. Its value begins to drop.

Maintaining clean data: A staged process

Data quality can be elevated using a one-time initiative: deduplicating, validation and cleansing using data quality software. This initial data clean-up helps to tidy up records and remove unwanted duplicates. Once this process is complete, you can begin an ongoing data management program to ensure the errors are kept at bay.
Once your data has been cleansed, it is returned to a pristine state – but only for so long. It will immediately start to decay, so a program of ongoing maintenance is required. This will stop your data cleansing initiative from being a waste of time and will ensure that it’s still an asset a year from today – not the inconvenient, unreliable mess it would be without effort.
For many businesses, there are three particular techniques that make sense when it comes to ongoing data maintenance:
High-quality application integration, where data is passed between systems without fear of pollution.
Business automation, where separate steps are linked and automated to reduce human effort, and therefore cut down on validation errors.
Ongoing validation, enhancement, and improvement to prevent the build-up of errors and enrich the data you have. This may include simple form field validation so that data is less likely to be botched or formatted incorrectly at the point of entry. It may include automatic enhancement, where new, clean data is appended to yours.


Improving data quality need not be a technically complex endeavor. Using data quality and business automation software, you can make much of the process invisible, and this makes ongoing data quality initiatives so much easier to manage. Setting up automation can be as user-friendly, or technical, as you make it. And the investment will ensure your data is an asset for years to come.
This article originally appeared here. Republished with permission. Submit your copyright complaints here.