Challenges Faced in the Data Integration Process

In the process of data integration, setting up the pragmatic prospects can become a challenge. For an agency, the primary goal is to set realistic figures and analysis. A unified and comprehensive data is to be presented by conjuring a perfect coordination from diverse databases, sources, and equipment. There must be a smooth functioning alliance of information while operating with data integration solutions.

However, in this field, as the data integration progresses, all the requirement and the challenges can be analyzed in the data requirement stage itself. Some of the common challenges faced are:

1. Heterogeneous data
The coordination of large data files and information from a varied system can become a task at some stage. The production of inheriting systems is completely different from conventional databases. Unlike conventional systems the inherit systems keeps on adding new data in order to increase the value. A system varies for copying data making it hard to get a unified final result.

2. Insignificant data
The quality is yet another concern when it comes to data integration. While assembling data from various sources, there are many misprints and lack of information which can cause serious problems to the agency. The legacy data has to be cleaned before starting its conversion and integration. The legacy data impurities tend to have a compounding effect as it generally gets concentrated around the high volume data users.

3. Lack of storage space
While integration of the data takes place, there are lots of problems faced by an agency concerning its storage. If there is not enough space for storing data, it can cause problems while offering scalability or elasticity of data. Hence the growth of the final data can be hampered due to lack of proper storage. Further adding an additional architecture can add to an expense of the firm and can be a costly deal.

4. Unrealistic costs
The cost involved in data integration is largely fueled by items which are difficult to be quantified. There are labor costs involved especially while the initial planning, programming, and evaluation stage is initiated. Costs can be a real hit hard when there is a suddenly unanticipated change taking place, and also costs involved in data storage and maintained.

5. Lack of manpower
With the increase of load per day, handling the applications can become a task for a limited number of employees. There can be a sudden spike in the demand for the manpower and skilled people to fulfill the demand. The requirement of skilled personnel depends on the type of project. With the development of the advanced databases, the data from the old databases needs to be carried to a newly built project.

However, with an expert data manager and a leader of the project, the data integration process can be handled smoothly. In a modular and a robust environment by choosing well-versed candidates, even a limited number of experts can handle diverse projects.

For an agency, it is essential to note that in reality, a fully functioning data integration system can be much more demanding in terms of maintenance and efforts to be put in. Unrealistic cost estimation can at times lead to an overly optimistic budget, especially in the times of budget shortfalls. With more number of users, there is a higher analysis requirement and the performances are more challenging.

While challenges will always be there, but with systematic planning and preparation, even biggest of hindrances can be tackled with ease. Instead of planning for bigger targets, move ahead while achieving smaller hits. Step by step accomplishments makes it much easier and simpler to deal with data integration process.