Every business deals with data, whether it’s from patients, customers, or even internal metrics. But are you managing all this data correctly? That’s where we can use a data quality scorecard to help your organization assess data quality across a variety of metrics.
What is a Data Quality Scorecard?
So what is a data quality scorecard? Data quality scorecards measure how well your business handles data. It provides a big picture look at how your organization handles their data and ensures you continue to meet key stakeholders needs.
Data quality scorecards are broken down by individual metrics you can customize to maximize your organization’s data-driven projects and goals. Having all of these scores in one place helps your team identify data quality problems before they become unmanageable, budget-blowing projects.
Data Quality Assessments for Scorecards
Here are some common data quality assessments that you see on data quality scorecards:
Currency
How confident are you that your data is up to date? This may not matter as much for data that doesn’t change, such as when a customer first started shopping with your company. It does matter for things that can change, like customer shopping trends and interests!
Entry Errors
Data entry often results in incorrect or even duplicate entries. Making sure your data set is free of errors and data quality issues means less work for your organization in the future.
Clarity
Even if it’s not a duplicate data entry, certain data elements can seem like it if you’re not clear! Making sure your data is being organized by clear, distinct fields can prevent headaches down the line.
What Are Acceptable Scores?
So how do we go about assessing data quality? Using data quality scorecards can reveal a variety of metrics about your data, including accuracy, availability, and completeness. Using an array of information about your data gives you a more complete assessment of your data’s quality.
Once you determine what metrics you’d like to measure your data’s quality against, you can assign a score to each metric! Scoring should be used as a quick way to determine how your data is helping your business reach its goals.
For example, if your data quality scorecard measures something like availability, you would be measuring how easy it is for those who need it to access the data. Are you able to run reports when you need to interpret data? Does everyone who needs to see this data have the access or security clearance necessary?
How to Implement Data Quality Strategy
To ensure your organization maintains high-quality data, it’s important to develop best practices for all employees. Though engineers are most commonly in charge of the technical aspects of your data quality strategy, every employee will come into contact with data in your organization. Having clear procedures in place enables your organization to use your data to its fullest potential.
Let Geneca Help With Your Score. Connect With Us to Learn More!
Not sure how to start measuring your data? Want some help building and implementing data dashboards and data quality scorecards? Reach out to Geneca today, and let our experts help find the best solution for your problem!
FAQs
What are the KPIs for data quality?
There are many different KPIs that you can use to measure data quality! Some of the most common include clarity, accuracy, and completeness.
How do you measure data quality?
Data quality can be measured against an agreed upon set of metrics. Determining which KPIs to measure your data against depends on what goals you’re trying to accomplish with your data.
What is data quality index?
A data quality index indicates how well your data is servicing your business’s needs, and it can be aggregated into a data quality scorecard.