All About Data Silo

Introduction

A data silo is a collation of data that is not easily or fully accessible to other groups of the same organization. A data silo generally consists of stored information or data available to only some parts of an organization, such as teams, departments, or even individual employees. This data is not available to the whole organization. Data silos are opposite to the approach of a data warehouse. There has been a lot of discussion for the need to break down data silos for effective and faster results in the modern data landscape.

Why Data Silos Occur?

Data silos occur naturally over time, reflecting organizational structures. Each department collates and stores data for different purposes, it builds its own data silo. Administration, finance, marketing teams, HR, and other departments require different information to do their work. These departments tend to store their data in separate locations known as data or information silos.

How Problematic are Silo?

Data silo stores are generally created automatically as data collates, or because someone in an organization creates them. They keep growing over time and then the amount of storage space required to store these silos also grows. Data silos may seem harmless; however, data silos generate barriers to information collaboration and sharing across departments. Due to discrepancies in data that may overlap across multiple silos, quality of data often suffers. Data silos make it hard for leaders to get a holistic view of the company data.

In this age of digital transformation, data is continuously collecting everywhere, without anyone noticing. This is not financial data but operational data that offers valuable insights on business performance and reveals opportunities for optimization. However, the data needs to be up-to-date, centrally available, and consistent to provide valuable insights.

Following are a few ways of how data silos hurt the business:

  • Data silos limit the view of data

Silos prevent sharing of important data. Each department’s analysis has a limited view. There is no hope of discovering enterprise-wide inadequacies without an enterprise-wide view of data.

  • Data silos threaten data integrity

With data silos, the same information is stored in different databases, leading to discrepancies between departmental data.

  • Data silos waste resources

When the same information is stored in different places and as users download data into their group or personal storage, resources suffer.

Steps to Break Data Silo

Centralizing data for analysis has become easier and faster in the cloud. Cloud-based tools organize the process of collating data into a common pool and format for efficient analysis.

  1. Change management

If company culture can generate silos, it is also the key to breaking data silos down. State the benefits of data integrity and data sharing so that workers understand the shift.

  1. Develop a way to centralize data

The most efficient way to break silos is to collect all corporate data into a data lake or a cloud-based data warehouse — a central data repository enhanced for efficient analysis.

  1. Integrate Data

Integrating data efficiently and accurately is a certified method to preventing future data silos.

  1. Establish governed self-service access

Centralize the data access and control the data with a data governance framework.

Conclusion

The cloud is a natural way to centralize data from various sources to make it easily accessible from home, office, road, or branch operations. Cloud data solutions help remove the technology barriers for collaboration and provide a ready solution for connecting data silos. Organizations can quickly add new and updated data to a cloud data warehouse by using an established ETL (extract, transform, and load) process to remove inappropriate data and duplication.