It is commonly said that the basic reason behind data integration failure is that people fail to follow the correct procedure or do not have a clear idea of how data should be collected, processed and aggregated. These reasons are very common among companies as these kinds of problems usually crop up once or twice in a lifetime when using data for decision-making purposes.
However, these problems can also occur due to a lack of resources or expertise on the part of the company or, at times, miscommunication between the organization and the professionals. The process involves collecting relevant data from various sources, analysis of data, proper identification, proper disposal and action for compliance management etc. This article will discuss the reasons for data integration failure.
Lack of data source
The first and the foremost reasons for data integration failure are the lack of data sources. Before you start the data integration process, make sure that the required information is available and it is updated regularly. It means you should update your employees regularly about the sources where new data files are available for them. You can collect this information from different places such as human resources, a CRM system etc.
Data extraction failure
Another major reason for the failure of data integration failure is the failure to extract accurate data from different sources. Sometimes it happens that while collecting data from different systems, you may get inaccurate or incomplete data. This may result in the wrong usage of data, which in result may create several risks for the success of the entire process. So, always try to gather all the relevant information before starting with the process.
Data cleansing failure
The integration process itself is not complete without the data cleansing process. If data cleansing is not properly followed, the chances are high that the final product may not be accurate and up to the mark. So, you should ensure that proper data cleansing procedures are carried out while doing the data integration process.
Data cleansing failure
No data is required initially when you are doing the process of integration. Data should be available at first instance, and only then should you proceed further with the data integration. The data received from different sources cannot be combined until an adequate amount of data cleansing is done. If the data integration process is not followed properly, the integration process may become lengthy and complex. Delays are a very common reason for data integration failure. Also, the quality of data is not maintained properly, resulting in huge data losses.
Data corruption failure
This is also one of the most common reasons for the failure of data integration. Data corruption is caused due to various reasons such as improper maintenance of data, corruption of file, bad sectors on the hard disk drive, virus attack etc. If the data is corrupt, it cannot be used in the integration process for various reasons. Similarly, the application needs to be restarted or reinstalled for the data to be imported again. Also, check for the application compatibility with the windows server. Make sure that you have the latest version of the windows server installed.
Data migration failure
If the data has to be imported in the form of reports, it may fail due to improper inputting of information. Sometimes people do not follow the procedures strictly. Other than these, improper usage of data fields, improper formatting, and data duplication are also some of the main reasons for data integration failure.
Finally, one of the most common reasons for data integration failure is that the software is not properly set up. If the files are saved as a PDF file, and later on, you want to import them again, then it is impossible to do so. You may have to reinstall the software again. The same thing can happen when you try to save data as an XLS file, which cannot be imported without proper re-saving.
Data integrity is also important for a company because it helps them build a strong relationship with the customers and clients. Data integrity also enables a company
in making decisions related to their customers. Therefore, a business organization should work intelligently and effectively to provide maximum benefit to its customers and to increase sales and revenue. All the data integrity activities performed by a company should be well planned and implemented as per the requirements.
In the case of organizations that are not performing well to maintain data integrity, it becomes important for them to look for some external factors that can impact their performance and make their data integrity fail. This will help them in improving their performance and maintaining a high level of data integrity. This is why a company should be highly motivated to maintain a high level of data integrity. It can be achieved by performing various effective activities like correcting any errors in the system, regular backups of the entire system, checking the entire information, storing it safely on backup servers, etc. Therefore, ONPASSIVE
always keeps in mind that the above are some of the top reasons for data integrity failure and can play an important role in improving data reliability and security.