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Data Fidelity and Quality Management: What’s the Connection?

Table of Content
  • Defining Data Quality
  • Defining Data Fidelity
  • Data Fidelity and Quality Management: What’s the Connection?
  • The Conclusion
The most valuable asset to your organization is its data. First, however, you need to be sure that the data you use is reliable and trustworthy. Companies can make reckless recommendations when they work with untrustworthy data for any reason.

An individual’s data quality can be categorized into two categories: Data Fidelity and Data Quality. However, there are significant distinctions between these two terms. Both terms are used interchangeably. Companies making better business decisions need to understand the difference between their data’s accuracy, consistency, and context.

Defining Data Quality

Data quality is the degree to which data is reliable. Data quality is crucial to data integrity.

For data to be considered quality, it must be:
  • Complete: The amount of data available is a substantial portion of what is needed.
  • Unique: A unique dataset does not hold duplicate or unnecessary entries.
  • Valid: Data is as per business and compliance requirements.
  • Timely: The data is sufficiently current to be used for the intended purpose.
  • Consistent: This dataset is consistent in how the data is represented.

These criteria must all be met for quality data. The lack of just one element could compromise any data-driven initiative.

Related Article: Data Quality Management: Benefits of Electronic Document Management System Every Business Owner Should Know

Even high-quality data is not necessarily valuable for an organization. For example, even with a database of valid and correct customer names and addresses, without supporting metadata that explains the relationship between those customers and your company, that database is not as valuable as it could be. In this case, data fidelity is critical.

Defining Data Fidelity

In data fidelity, the characteristics of a source are quantified and embodied accurately. However, data fidelity is now used in cybersecurity to detect intrusions at the granular level using the granularity of event data captured. It is also possible to define fidelity in terms of granularity and accuracy of data detailed in a report.

To ensure fidelity, data must be;

  • Traceable: So, you can track it easily and quickly when needed.
  • Accurate: The data should be accurate to identify gaps and inconsistencies.
  • Secure: The data must be managed securely to ensure access for authorized users only.

Building, managing, and maintaining high-fidelity data architectures require more complex skills. Speed, volume, and variety of data have their respective effects, but these effects are influenced by technology drivers like asynchronous processing and improved I/O throughput mechanisms. Likewise, increasing fidelity and lowering latency requires more skill and engineering.

Data fidelity and finer granularity are important for EHR (Electronic Health Records) and CDS healthcare verticals.

It is essential to understand data fidelity and latency and how they relate to data complexity, architecture, and models to gain meaningful insights into the data. For data fidelity to be quantified within a domain like healthcare, it would require a scientific evaluation on a scale appropriate for an academic paper.

Similar to the efficacy of a vaccine, data fidelity and latency impact the data model. Data fidelity is an excellent way to quantify the success of any data-related project. As a rule of thumb, you can correlate data fidelity and latency to the different business scenarios and determine how well they worked.

Data Fidelity and Quality Management: What’s the Connection?

As already discussed above, data fidelity is an excellent way to quantify the success of any data-related project. Furthermore, it can play a crucial role in the success of your quality management system since the enterprises’ quality related decisions are data-driven.

In fact, data quality and fidelity – both are equally important for quality management.

So, how would you take care of both aspects while managing quality processes?

It just takes one simple solution to make things right. And the solution is Qualityze Forms Management System.

Qualityze Forms Management Software enables enterprises to manage form-related activities more effectively. It is easy to create, edit, share, and track all types of forms to capture valuable inputs from customers, employees, suppliers, and stakeholders. Data can be validated in real time with Qualityze Forms management. Validating your data when it is collected will improve the quality of your database. Furthermore, you can integrate it with existing quality systems to standardize data collection best-practices across the organization. You can effectively and efficiently manage forms with Qualityze Forms Management System by:

  • Centralizing forms and critical information in a database.
  • Monitoring the forms’ status whenever necessary.
  • Establishing standardized audit checklists, supplier questionnaires, customer feedback forms, and more.
  • Managing forms on a single site or across multiple sites.
  • Creating forms based on different business and regulatory standards.
  • Reducing the risk of compliance issues.
  • Controlling access to forms containing sensitive information.
  • Making better decisions by analyzing form inputs.

Building the right forms helps you gather the right data, which you can further analyze and make intelligent decisions. Qualityze Forms Management Solution standardizes the process and makes it simpler for you to create a quality data repository to assist you with critical decisions. It is a fully configurable and validated solution. Moreover, you need not stress about the forms’ data security since the solution has in-built security controls to keep all the data safe from unauthorized users.

You can see your product features and in-built capabilities by requesting a free demo today.

The Conclusion

An organization seeking data-driven decisions needs to ensure data quality and data integrity. Of course, it is important to start with data quality. Still, data integrity is the key to enhancing the usefulness of the data to an organization and ultimately driving better business decisions.

Data quality may be the first step toward data fidelity. In all their data-driven initiatives, companies that make proactive efforts to fix data quality issues see better results.

With Qualityze Forms Management Software, enterprises can significantly improve data accuracy, consistency, reliability, and safety. Furthermore, you can leverage the advanced integration capability to improve the data quality and fidelity across all the systems organization-wide.


If you have questions about Qualityze Forms Management Software, you can contact our customer success team. We can be reached at [email protected], or you can give us a call at 1-877-207-8616, and our team will reply as soon as possible.

The post Data Fidelity and Quality Management: What’s the Connection? appeared first on Qualityze.



This post first appeared on CAPA By Filtering – It’s Not Everything That Requires A CAPA!, please read the originial post: here

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Data Fidelity and Quality Management: What’s the Connection?

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