Application Security

Data Silos

What are Data Silos?

A data silo is a repository of information in a department or application that is inaccessible or not fully accessible by other departments or applications in an information system. An example of siloed data is an information system that has finance, administration, HR, and marketing departments storing their data in different locations. This may seem understandable, as these departments need different information to do their work, but as the quantity and diversity of data assets grow, this siloed data can lead to a number of problems such as:

  • Poor trust and collaboration across teams
  • Higher costs due to redundant IT and application infrastructure
  • Wasted resources
  • Slow data-driven decision-making
  • Reduced data quality
  • Poor customer experiences
  • Limited views of data
  • Duplicated work and effort
  • More difficult data analysis
  • Compromised data security

Data silos are commonly caused by an organization have multiple applications and sources of data, organizational growth that outpaces the growth of their infrastructure, and organizational structures such as access control systems and permission systems that make it difficult to share data company-wide. Technological and organizational solutions can help in data silo dismantling efforts, as well as following these tips:

Data silo sources. Investigate where the data silos originate. This might be easier to uncover in a smaller organization while an investigation may require more effort in a larger organization. Consider using questionnaires and interviews to understand where data silos originate and are causing the most damage.

Change management. Promote a positive change culture in your organization by encouraging a culture that values data sharing and data integrity. This culture shift will help in the process of dismantling data siloes as well as preventing their creation in the future.

Address technological factors. While some data silos are created due to human behavior and hierarchical HR structures, others are caused by incompatibility between technological applications. Unify your data on a modern platform designed for collaboration and sharing with an easy-to-use interface.

Integrate data. Several methods can be used to integrate data:

  1. Scripting. IT can be tasked with writing scripts in SQL, Python, or other scripting languages to move siloed data to a data warehouse.
  2. On-premises ETL tools. Extract, transform, load (ETL) tools automate the process of moving data to a data warehouse.
  3. Cloud-based ETL tools. Cloud-based ETL tools make the ETL process easier and faster by using tools designed for cloud infrastructure.

Data governance. Once data is centralized and integrated, design robust data access policies that make data easily accessible for those with access permissions.