A data silo is a collection of data held by one group that is not easily or fully accessible by other groups in the same organization. Finance, administration, HR, marketing teams, and other departments need different information to do their work. Those different departments tend to store their data in separate locations known as data or information silos, after the structures farmers use to store different types of grain. As the quantity and diversity of data assets grow, data silos also grow.

Data silos may seem harmless, but siloed data creates barriers to information sharing and collaboration across departments. Due to inconsistencies in data that may overlap across silos, data quality often suffers. When data is siloed, it’s also hard for leaders to get a holistic view of company data.

In short, siloed data is not healthy data. Data is healthy when it’s accessible and easily understood across your organization. If data isn’t easy to find and use in a timely fashion, or can’t be trusted when it is found, it isn’t adding value to analyses and decision-making processes. An organization that digitizes without breaking down data silos won’t access the full benefits of digital transformation. To become truly data-driven, organizations need to provide decision-makers with a 360-degree view of data that’s relevant to their analyses.  
 
Data analysis of enterprise-wide data supports fully informed decision-making, and a more holistic view of hidden opportunities — or threats! Plus, siloed data is itself a risk. Data that is siloed makes data governance impossible to manage on an organization-wide scale, impeding regulatory compliance and opening the door to misuse of sensitive data. 

To better understand if data silos are holding back your potential for holistic data analysis, you’ll need to learn more about where data silos come from, how they hinder getting the full benefit of data, and your options for data integration to get rid of data silos. 

Download The Definitive Guide to Data Integration now.
Read Now

Why do data silos occur?

Data silos occur naturally over time, mirroring organizational structures. As each department collects and stores its own data for its own purposes, it creates its own data silo. Most businesses can trace the problem to these causes of data silos:

Siloed organizational structure

Before big data and the cloud revolutionized business, it wasn’t considered a bad thing for different departments to create and manage their own data. Each department has its own policies, procedures, and goals. Teams developed their own ways of working with and analyzing data in ways that suited their needs. Silos still build up around company departments because that’s how the data is collected and stored.  

Company culture

Related to the above, in many organizations departments are accustomed to working in their own worlds. Each has its own lingo, processes, and challenges. If they work in physically separate areas, with their own processes and goals, each department naturally considers itself as a separate business unit, distinct from other teams. This culture of separation carries over to data. Even if the sales team and marketing team both work with customer data, company culture may encourage them to keep their data separate, without even questioning it. Since company-wide data sharing is a relatively new goal, departments haven’t been motivated to unify their data.  

Technology

The very tech tools and data management systems that many organizations use have pushed them into data silos. Different departments tend to support their operations using different technology solutions and tools, such as spreadsheets, accounting software, or a CRM like Salesforce. Most legacy systems were not designed to easily share information. Each solution stores and manages data in different ways — these are often proprietary to the vendor that created the solution, which makes it hard to share data sets with stakeholders in another department.  

4 ways data silos are silently killing your business

Each department exists to support a common goal. While departments operate separately, they are also interdependent. At least some of the internal data that the finance department creates and manages, for example, is relevant for analysis by administration and other departments.

Competition, the need to cut costs, and the desire to seize opportunities are driving organizations to do more with their data. Access to enterprise-wide information is necessary to maximize operational efficiencies and discover new opportunities.

But at some point, data silos will pose a barrier to success. Here are four common ways data silos hurt businesses:

1. Data silos limit the view of data

Silos prevent relevant data from being shared. Each department’s analysis is limited by its own view. There’s no hope of discovering enterprise-wide inefficiencies without an enterprise-wide view of data. How can you find hidden opportunities for operational cost savings, for example, if operations and cost data aren’t consolidated?

2. Data silos threaten data integrity

When data is siloed, the same information is often stored in different databases, leading to inconsistencies between departmental data. As data ages, it can become less accurate, and therefore, less useful. For example, if medical data on the same patient is stored in different systems, this data can become out of sync over time. 

3. Data silos waste resources

When the same information is stored in different places, and when users download data into their personal or group storage, resources suffer. Streamlining data into one source frees up precious storage and relieves IT stress in buying and maintaining storage that may not be needed. For example, if many workers download data to analyze in a spreadsheet, each download is a redundant copy of existing data.

4. Data silos discourage collaborative work

Culture creates silos, and silos reinforce culture. Data-driven organizations are embracing collaboration as a powerful tool to find and leverage new insights. In order to encourage collaboration, departments need a way to share their data. When data is difficult or impossible to share, the ability to collaborate suffers.  

How to break down data silos in 4 steps 

The solutions to silos are technological and organizational. Centralizing data for analysis has become much faster and easier in the cloud. Cloud-based tools streamline the process of gathering data into a common pool and format for efficient analysis. What once took weeks, months, or years can now be accomplished in days or hours.

1. Change management

If company culture can create data silos, it’s also the key to breaking data silos down. Communicate the benefits of data sharing and data integrity so that workers understand the shift. Also communicate the problems with silos, including data quality problems and the need to stay competitive. Culture change is a big undertaking, so management must show commitment. 

2. Develop a way to centralize data

In the realm of data management systems, the best way to bust silos is to pool all corporate data into a cloud-based data warehouse or data lake — a central data repository optimized for efficient analysis. Data from disparate sources will be homogenized and consolidated, and access can be easily granted to individuals or groups to balance business need against privacy and security.

3. Integrate data

Integrating data efficiently and accurately is a guaranteed method to preventing future data silos. Organizations integrate data using one of several methods:

Scripting 
Organizations can task IT with writing scripts in SQL, Python, or other scripting languages to move data from siloed data sources and into the warehouse. The downside to scripting is it can be complex. As data sources grow, complexity grows. Changes in data sources require scripts to be updated. Maintenance of hand-coded integration becomes a cost and time burden for IT professionals. 
 
On-premises ETL tools 
ETL (extract, transform, and load) and ELT tools automate the process of moving data from various sources to the data warehouse. These tools extract data from sources, transform data into a common format for analysis, and load the result into a data warehouse located in the organization’s data center. 
 
Cloud-based ETL 
The cloud and data go hand in hand, and sophisticated cloud providers are making the ETL process easier and faster. Cloud-based ETL takes advantage of the cloud provider’s infrastructure — including a data warehouse and ETL tools designed to work efficiently in their environment. ETL breaks down silos by providing the technological means to gather data from different sources into a central location for analysis. ETL helps handle data integrity issues so that everyone is always working with fresh data. 

4. Establish governed self-service access

When data is centralized and integrated, you also create the opportunity to centralize data access and control with a data governance framework. Robust data access policies facilitate self-service analysis, so business users with permission can easily access the data they need, without the headaches or delay necessary when IT personnel must serve as gatekeepers. 

Download The Definitive Guide to Data Governance now.
Read Now

The cloud and the future of data storage 

The cloud has emerged as a natural way to centralize data from diverse sources to make it easily accessible from the office, at home, on the road, or by branch operations.

Cloud data solutions help eliminate the technology barriers to collaboration and offer a ready solution for connecting siloed data. Using an established ETL process to strip away irrelevant data and eliminate duplication, organizations can quickly add new and updated data to a cloud data warehouse. This enables different departments to work collaboratively with fresh, clean, and timely data in a single, accessible platform that scales to meet demand.

Cloud technology and cloud data warehouses connect disparate business units into a cohesive ecosystem. Data analysts get a better view of how their work affects the whole organization, and how everyone’s work affects each other. Access to enterprise-wide data gives analysts a 360-degree view of the organization. 

Tearing down data silos 

Data silos undermine productivity, hinder insights, and obstruct collaboration. But silos cease to be a barrier when data is centralized and optimized for analysis. Cloud technology has been optimized to make centralization practical.

Thousands of organizations worldwide choose to centralize data in the cloud with Talend Data Fabric, because Talend simplifies data integration ETL, data governance, security, and regulatory compliance while providing silo-busting access to data by every department. For example, Covanta — a sustainable waste-to-energy supplier — prioritized overcoming data silos so they could better collect, govern, transform, and share data. Once departments across the company were communicating in real time with a shared source of truth, they could easily find and cut inefficiencies. Convanta slashed the cost of maintenance activities alone by 10% per year.

Talend Data Fabric enables users across the organization to collaborate using a comprehensive suite of apps — one solution for simplifying the process of busting silos forever. You can try Talend Data Fabric to see for yourself how Talend can partner with you to banish silos, improve operations, and boost profits across a variety of use cases. We’ll help you break down data silos and ensure that decision-makers across your organization always have a full understanding of company data.