Quality and Data Integration Two

¶ … 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.

Data Integration

Integrating data is not always an easy task, but new technologies and methodologies have worked to make it easier in recent years. Data integration means taking the data from all across your organization and putting it together. There are a lot of ways that this can be done. Data needs to be integrated in the sense that everyone who needs it across the organization will be able to access it and do what needs to be done. It also needs to be integrated in the sense that someone should be done with the data. Just collecting it does a business no good if it is not analyzed and the business does not learn from it. If the data is not showing them what they need to know, then they know that they need to collect new data, and that requires making modifications to various areas of the business so that they can continue on their quest to collect what they need to know.

With data integration, someone in customer service and someone in the accounting department should both have access to the same information. Ditto the people in sales. If they cannot get to the data on a particular customer when he or she calls, writes, emails, or otherwise contacts them it is possible that customer will be lost. The frustration of not having integrated data is something that most customers do not want to take the time to put up with, and most companies do not want to deal with it, either. Thankfully, the technologies of today allow for a lot of data integration. If a person calls into a company, he or she can be routed around to various departments and people and deal with all of the concerns that he or she has with one phone call. Since this can involve talking to several different people, making sure that they can all get to the customer's data becomes a necessary part of doing business. Without it, customers are stuck with a lot of aggravation.

Data that is integrated across the company should also be looked at from a customer service and company improvement standpoint. If the data is only used to help customers this is certainly important, but there is more that it can do. With that in mind, companies who are interested in moving forward need to make sure that their data is integrated in such a way that they can use it for their growth. If they analyze customer records they can find patterns that go across the entire company as opposed to just one department, and that will help them determine whether there are problems with specific products, problems with specific departments, or other areas that they need to address when it comes to future products, services, and changes that they will need to look at creating.

Conclusion