Data Integration Patterns: Developing A Stronger Understanding

PC Network Solutions Managed IT Services & Solutions for Healthcare Industry

Staffers for IT Support for Healthcare have a number of concerns that must be addressed on a regular basis. There are also a wide range of data integration tools [] that staffers for IT Support for Healthcare have to consider. Some may need time to choose the proper platform as well [].

IT Computer Support for Healthcare: Data Integration Patterns

There are four key data integration patterns that are currently being used today. These patterns help healthcare organizations by giving them the tools they need to streamline the standardization of data process. Let’s take a closer look at these patterns and how they affect healthcare organizations….

1. Broadcasting/Correlation/Bi-Directional Synchronization

If different systems are in need of updating, these are the processes that are going to be employed. When broadcasting takes place, a system’s data is stored in one location and it is moved to a variety of other locations.

With bi-directional synchronization, the data is moved to two separate systems in two different directions. The two systems come together to act as one. Correlation involves bi-directional synchronization and the process is performed at the intersection of two different data sets.

2. Virtualization of Data

This is one of the fastest rising data integration patterns. When a healthcare organization needs to combine data from several different databases into one physical database, this is the method that is most commonly used.

For healthcare organizations that are looking for the best way to remap their data, data virtualization is the way to go. The method is also useful for any organization that needs to strike a coordination between their data analytics and their sales transactions.

3. Migration of Data

Data migration is one of the most significant data integration patterns that is currently being discussed. As the name would suggest, data migration is all about the process of transferring data from one location to the next.

This process is streamlined and the data set’s final transformation is decided on before the process. The results that are obtained are then compared to the desired results that have already been discussed, to make sure that the process has gone smoothly.

4. Data Replication

Last but certainly not least, we have the replication of data. This is a technique that is utilized on a consistent basis and for good reason. Once data is being moved from one store to the next, it is time for the data to be replicated.

This ensures a smooth transfer and keeps healthcare organizations from being forced to scramble after the fact. With this method,the data can be moved from the database to the cloud without any difficulty. It is important to note that the structure of the data will change during this process, though. A mechanism is used to conduct the process and make the necessary changes to the data integrator.