Businesses have understood the importance of data quality and the impact that it has on the current process and the future of the business. In this article, we answer the most frequently asked question, “How do I measure data quality issues?” We will provide you with all the information you need to understand the intensity of the data issues. And, give you a solution that can be adopted to resolve them.
There are a series of metrics that can be used to identify data quality issues. But, the question that should be asked is, “What is bad data?”
Here are some of the most common issues that are identified as bad data, which could invariably diminish data quality.
- Erroneous data
- Uncontrolled data
- Noncompliant data
- Unsecured data
This is one of the few areas that could be attributed to bad data, and this often takes place over time due to missing information such as spelling errors, incorrect numeric, and blank areas, as well as long-term neglect of data.
Why is good data quality important?
Data quality invariably plays an important role in factors such as decision-making and when seeking insight through data. But, there is an inaccurate analysis of data quality, which would invariably lead to negative results in terms of incorrect communication details, inaccurate personal information, and product measures.
How should data quality be viewed?
The analytical approach that is used should produce an analysis that is accurate enough for further action to be taken. With the right tools and a professional team, data quality can be archived. The solution to this is to integrate data from across multiple platforms and proceed further to choose the right tool to achieve a thorough analysis of data quality. This is where uArrow steps in.
uArrow has the capacity to perform data profiling and deliver on data quality.
Why does uArrow stand out?
uArrow allows data to undergo a series of checks that ensure the accuracy of the analysis and data quality.
The added features are
- Integrity checks that cover the primary key, foreign key, and bridge key, which is a unique feature specifically driven by uArrow.
- Attribute checking includes dictionary, range, and pattern checks.
In order to achieve results that are easy to understand with pictorial representations, a creative dashboard is a unique feature that uArrow’s product delivers through a data profile summary.
Conclusion
In this article, we have discussed and answered the question, “How do I measure data quality issues?” Besides this, we have additionally provided information on the effects of bad data and the benefits of choosing uArrow to deliver on data quality. Get in touch with uArrow to know more about their data management platform.