How to identify and solve common data collection issues

Your data analysis is only as good as the quality of your data, so let’s look at the most common issues and how to deal with them.

Why are data collection issues important?

Business data is a critical tool for business. Whether working alone or with a data analysis company such as https://shepper.com/, incomplete, duplicate, and orphaned data can be a nightmare, impacting the customer experience and your marketing initiatives.

Poor quality data has hidden costs that affect business growth; however, solving the most common problems is relatively straightforward.

How to solve common data collection issues

Duplicate data

Perfectly matching and fuzzy data can be weeded out using rules-based data management tools.

Inaccurate or missing data

Start with a thorough audit of your data collection practices and make the most of automated data collection for greater accuracy.

Outdated data

Collected data can rapidly become obsolete, so review and update your information regularly.

Irrelevant data

Systems easily fill up with irrelevant data. Start by defining your project’s data needs, then use filters and visualisation tools to identify the critical information you need.

Inconsistent data

Inconsistencies such as data formatting can degrade your data. Data quality management tools flag up inconsistencies and catch discrepancies at the source to ensure your data is trustworthy.

Orphaned data

Orphaned data is unusable information that exists in one database and not another. Data quality tools will identify discrepancies and restore orphan data’s usability.

Hidden or dark data

Your business only uses a fraction of the data it holds; however, hidden or dark data could be vital in developing new markets and innovative products. Data cataloguing is an excellent way to mitigate the problem.

Human error

Data entry relies on human input, and any errors render your data useless. Human error can occur at any point in the data journey, but training sessions and digital literacy workshops can improve your staff’s skills.

Data quality can have significant implications for your business. Performing an audit, creating and implementing a data quality plan, and monitoring data quality can improve data quality for lasting results.