With data becoming a major buzzword, data quality has been a point of interest for most data specialists.
With that being said, let us take you through the biggest reasons bad data is still an issue even in 2021.
Data duplication is a situation when an exact copy of a data point is created. To those unaware, this issue seems simple. However, data duplication is a widespread concern and can get pretty tricky to fix.
Thus, in healthcare, duplicate medical records are growing at a fast pace. This leads to patients often being mistreated.
The human factor. You are likely dependent on your employees to fetch valuable data for you. We humans get tired quickly and cannot press on with the same task for a long time. As a result, fatigue makes your workers enter multiple copies of the same data piece.
Data duplication happens when you compile data from various websites. To keep search engines happy. listings may be slightly altered. Therefore you won’t be able to detect duplicates unless you turn to an advanced querying tool.
Inconsistent data formatting is another issue that haunts most organizations. If the data is saved in inconsistent formats, the systems used to analyze the information may not interpret it as needed.
If the company collects the database of their consumers, then the format for basic data pieces should be specified. It may be especially challenging for systems to differentiate the US and European-style dates and phone numbers, especially when some have area codes and others don't.
If it weren’t a common pain, this issue wouldn’t make it to our list. Inaccurate data is generated for a number of reasons.
Human error cannot be cured. But if you embrace clear procedures that are followed consistently, your data analysis will be accurate and likely super effective at helping you produce the results you seek.
Also, automation tools help decrease the risks of mistakes by exhausted and bored workers. Do your data justice!