FPR - Logo - SQ - REd and Blue.png
  • LinkedIn - Black Circle
  • Facebook
  • Twitter

©2019 by Fusion Professionals

  • michaelthould

Is Your Enterprise’s Data Quality Management Meeting Industry Standards?

Updated: May 30, 2019

“Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming.”

– Chris Lynch, AtScale CEO


Businesses that aim to scale can no longer afford to keep data collection in the back seat, lest they wish to get left behind.

Admittedly, however, data analytics and the challenges of big data are difficult to manage, and definitely not a walk in the park to plan for, implement, manage and utilise, so how can organisations know that the quality of their data management is meeting industry standards, or even better, setting them?


Here is a quick checklist you can run through to determine if your enterprise is adequately taking advantage of data management to produce quality results:



Is your data quality management at an operational level?

Each individual in your enterprise is responsible or at least aware of the data they influencing; whether this is administrative, financial, marketing, etc., depending on the business function. Therefore, data management is a cross-functional, position agnostic responsibility and this should be reinforced through the culture of the organisation, within your business.


Are the processes and software you have in place working together?

Data Analytics and Big Data Technology should be making the operations easier for your enterprise to meet its customer needs.. Are the data lead insights impacting across the organisation, improving or consolidating phases of your existing business processes leading to better customer solution and experiences aided by solution architecture designed to continually support, cleanse, and monitor, for optimisation.


How regular is your maintenance?

To produce quality results, proper data management and maintenance must be planned and continuous. Your enterprise should have dedicated management and systems to analyse, filter and categorise data, ensuring the quality and integrity of information that is being used to produce the best results for your business.


What happens to your qualified data?

A fundamental step in data quality management is the actual application of what has been processed. Qualified data leads to qualified results.

Many enterprises are still wary of how they begin to optimise their Data Analytics and Big Data structures and progress to implementing an integrated best in breed solution given the choice of suppliers, platforms and applications available. Let alone the significant organisational outlays in terms of time, money and potential restructuring. For these reasons, at the very least, you should look to improve your data quality using our simple checklist.

Does your Data Quality Management need improvement? Or perhaps you’ve decided it’s finally time for your enterprise to make data optimisation a priority. Consult with Fusion Professionals to catalyse the growth of your business today.