There is a substantial complexity involved in the process of merging multiple data sources. Here is a list of the difficulties that you can anticipate encountering:
Rising Data Volume
The volume of data continues to increase, and the data sources are always evolving; new ones appear every once in a while. In the same way that the process of integrating data is a continual one, ensuring that your systems are able to manage rising loads and additional data sources is also an ongoing task. If your company does not have a solution that is scalable, the sheer volume of data that you might need to integrate could put a strain on the infrastructure and resources utilized by your corporation.
Compatibility
The most prevalent challenge faced by teams is managing data that originates from diverse sources and is presented in varying formats. To successfully combine different types of data, it is necessary to meticulously convert and align them to achieve seamless integration. It also requires the process of harmonizing different data structures and technologies to facilitate smooth interoperability.
Data Quality
It can also be hard to keep the quality of the info high. You could have problems with data that doesn’t match up with standards, has missing numbers, or is duplicated. Cleaning and changing data to fix these problems can take a long time if it has to be done by hand. These problems slow down the ETL pipeline, which could affect apps and reporting further down the line.
Maintenance
Keeping the data integration process running smoothly is hard because it involves regularly checking and improving the connected systems to make sure they work well and provide correct and up-to-date data. There are problems like this that don’t get as much attention as others. Sources may change over time, new information may become available, and business needs may change. In these situations, the integration process needs to be changed, which is why upkeep is so important.