The relationship between data quality and data integration

¶ … quality and data integration two different things? Can we have one without the other?

Whether data quality or data integration is more significant is a fair question, and one that is really not that easy to answer. In order to best address the question, it becomes necessary to discuss both data quality and data integration in order to ensure that there is a full understanding of both of them. From that point, it can be seen where they come together and whether one can function appropriately without the other one. There are some who feel that the two are intertwined and others who feel as though they are two separate entities that have nothing to do with one another.

No matter which opinion a person shares, the discussion of the issue is certainly necessary because there are many people who feel as though both data quality and data integration are important concerns, and this is certainly truer each day. The world is becoming more global, and with that globalization comes more technology, more data, and more opportunities for those who work with that data to become either part of the problem or part of the solution.

Data Quality

Data quality is a vital part of many businesses. If a company does not have the right data, how can it hope to survive and compete with others? When companies do not pay close attention to the quality of the data that they receive from other sources and the quality of the data that they put into their system and store, they are harming their company at one of the most important and structural levels. This is due to the fact that the data that they have is what they use to make their hiring and firing decisions and determine whether they are doing right by their customers. They can look at what is being sold, what is being returned, and whether individuals who are happy with their products are buying more from them. They can collect a lot of information very easily, and what people are willing to provide helps them determine whether they want to keep going with their particular strategy or move forward with something else that might be more logical for them.

Where data quality is concerned, however, the specific definition becomes a little bit murky. In other words, what constitutes 'quality' in data? That depends on who the question is asked of. Not everyone sees quality in the same way. If one is talking about quality in the form of data accuracy, that is a different thing than someone talking about quality in the form of what one can do with the data. That requires some explaining. The quality of the data that a company collects can be judged by some people based on whether the data that is being collected is accurate. Does the person who bought something really live where he or she says? Does he or she belong to the demographic group that was indicated? If not, than the data is not accurate, and a person could say that affects quality. It is difficult to have good quality data if there is no accuracy to it because it will not really tell a company what the management of the company needs to know.

Another issue with data quality is what can be done with the data that is collected. If a company collects a lot of data but it does not provide them with useful information, then where is the quality? If a company needs to know what kind of demographic group most often buys their products but they only collect data on where a person lives, that will not help them. To have quality in their data, they will instead need to know what age group their customers fall into as well as other things like their nationalities and whether they have families with children. There are a lot of different things that can be addressed when it comes to demographic information, and what a company chooses to collect has to be up to them. Without studying the issue to determine what they need, the quality of the data based on what they can do with it might be severely compromised.

Getting quality data, therefore, appears to mean that the data needs to be accurate and correct, and it also needs to be data that can truly be used by the individuals who are collecting it. Whether that is a business that will be using it or a person - such as would be collected through surveys for a study - is not relevant to whether quality has been achieved. Once quality has been addressed, though, there is another issue. The data has to be integrated properly. Some people feel that data quality and data integration are the same thing, but they are two different entities. The integration of data, while not the same thing as quality, is another very important issue that is closely tied to it.

Conclusion

In short, data integration and data quality are not the same things, but they are very closely linked. Can a company have one without having the other? Yes, but to what benefit? If a company has high quality data in every aspect but does not use it for anything, the company is losing out. If a company is very serious about data integration but the data that they are using is low in quality, that company is also losing out. While these two areas are not technically the same, they must be used in concert with one another in order to assure the success of a company, both now and in the future. Often, integration takes place throughout a company but the quality of the data is not as good as would have been hoped for. People ignore problems with data, customers fail to correct discrepancies that they see in their addresses or phone numbers, or they provide misleading information so that the company will not contact them. Some of these things cannot be helped, so there will never be perfect quality in data. The companies who store this data, though, must do what they reasonably can to keep their data as pure as possible. It will help them in the long run.

Companies that pay close attention to the quality of their data and make an effort to keep it up-to-date and correct generally do better than companies that ignore quality controls in the face of speed, cost cutting measures, or other reasons. Companies who then take that quality data and integrate it correctly are often the best at what they do, and that shows to their competition and to their competitors. It means a lot less aggravation for those who contact the company more than once, because all of their information is taking down the first time. They can then call any department in the company and their information will be there, and it will be correct. People want to do business with a company like that, because it implies that the customer matters to them. Quality and integration of data are both keys to a strong, successful business.