Data silos Syncler-Glossar

Data silos are a common phenomenon in companies. They occur when different departments such as sales, marketing, or customer service store their data separately, and other departments have no or limited access to this data. These silos are similar to agricultural silos where different types of grain are stored.

Problems of Data Silos

Data silos may seem harmless, but they hinder the exchange of information and collaboration between departments. This leads to data inconsistencies and impairs data quality. Data silos prevent leaders from having a holistic view of company data. In short, data in silos are an obstacle to healthy, usable data.

How do Data Silos arise?

Data silos arise due to an organizational structure that promotes silo formation, a company culture that encourages departments to act separately, and the use of technically different applications.

Disadvantages of Data Silos

  • Limited View of Data:
    Silos prevent the sharing of relevant data and limit the analyses of each department.
  • Threat to Data Integrity:
    Isolated data often lead to inconsistencies in different databases, e.g., different contact details of the same person in various applications.
  • Waste of Time:
    Employees spend time searching for information in different applications.
  • Impeded Collaboration:
    Separate data storage hampers collaboration between departments.

How to break down Data Silos?

To eliminate data silos, both technical and organizational solutions are required. Integration platforms, like Syncler, help automate the data flow between data sources and thus homogenize it. A change in company culture, supported by the management, is also important to promote the shared use of data.


Data silos are an obstacle to productivity and gaining insights. By consolidating and optimizing data for analysis, companies can fully leverage the benefits of digital transformation. Integration platforms with predefined connectors offer possibilities to effectively break down data silos and enable centralized data analysis.