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Data silos are isolated repositories of data stored in disparate systems within an organization. They’re usually stored in a standalone system in a different and incompatible format from other data stores, and they are not easily accessible to other departments, business units, or users outside the group that owns them. Data silos may be regularly used by members of an organization or sit idle (and unpatched) once a team no longer needs that repository, making it more vulnerable to a ransomware attack.
Data silos form when different departments or business units act autonomously, each possessing its own mission, objectives, and even IT budgets. For example, the HR department will typically have its own employee database optimized for their needs, which it doesn’t share with other parts of the company.
Top reasons data silos form:
Departments within organizations operate independently because they have their own specific needs. Therefore, they end up with a customized or point product that addresses that specific need but doesn’t align with the rest of the business. It then becomes decentralized, managed separately, and not easily integrated.
Without clear data governance strategies, such as policies and best practices, businesses end up with non-standardized processes for managing and sharing data across the organization. This results in the proliferation of data silos.
Old and outdated technology may not be compatible with modern data management solutions. This results in systems being unpatched for the latest cyber threats or data becoming isolated, unable to be used for analysis, re-monetized, or easily recovered.
Various departments have different needs, but using different software systems can lead to data silos because these systems may not be interoperable or able to share data with other systems seamlessly.
An entity acquiring or merging with another business will almost certainly create data silos until all data stores have been adequately transformed or integrated. It’s important to note that in addition to apparent data silos, there will be hidden ones that need to be identified in the new, joined entity.
Because data silos are isolated and not accessible outside of the groups they belong to, they can be difficult to spot. Here are some signs your organization might have data silos:
Siloed data can have negative financial impacts, such as higher data storage and management expenses and renewal costs. These are the most tangible costs businesses can expect from data silos. But data silos also have various hidden costs, including:
When faced with siloed data, users often are forced to find complicated workarounds that are difficult to maintain and can impair data quality. This becomes into a continuous loop in which business processes and productivity deteriorate over time.
When there’s no holistic transparency into what’s happening with problematic processes and reduced productivity—both within and external to the business—organizations can miss potentially lucrative opportunities to increase revenues or cut costs.
Ransomware payments or expensive ransomware recovery time and costs can be another unexpected financial burden of data silos. Disconnected systems or those operated as “shadow IT” can make it easier for cybercriminals to penetrate and exploit them successfully.
Customer costs can also rise when information concerning customer profiles and transactions is fragmented across multiple data silos—say, a point-of-sale (POS) system, a mobile app, and a SaaS CRM system. The business won’t have an informed view of a customer that would enable it to personalize experiences and special offers to maximize customer value.
Eliminating data silos is critical for organizations striving to remain competitive in the digital era. The benefits of getting rid of data silos include:
Without silos, all data collected and stored by the business can be accessed, allowing leaders to identify trends that would have previously been invisible and thus make smarter and faster decisions. Organizations can then seize new opportunities and monitor performance precisely, enabling leaders to rapidly improve margins and identify areas for improvement in real time.
Breaking down data silos and integrating data across the organization also improves both communication and collaboration between users from different departments. It makes it easier to find synergies between them, and collaborate for the business’s good as a whole.
Breaking down data silos boosts an organization’s agility and competitiveness by enabling quick, cross-departmental access to information. This open data flow speeds up decision-making and collaboration, helping teams respond swiftly to market changes and customer needs. Organizations can make better-informed, timely decisions that strengthen their competitive edge by reducing redundancies and improving data accuracy.
Removing data silos allows users to access all the data they need to do their jobs. It also eliminates the need for additional IT management and maintenance of separate data silos, which drives organizational efficiency and reduces costs.
By eliminating silos, organizations can improve customer trust and loyalty while boosting customer-service quality and engagement with personalized offerings and immediately accurate answers to questions.
Getting rid of data silos also bolsters cybersecurity resilience against cybercriminals and ransomware attacks. This allows organizations to more accurately assess risks, maintain compliance, and avoid reputational and financial damage.
To eliminate data silos requires organizations to take a range of actions. These encompass strategies that are technological, process-based, and organizational.
If organizational culture can be responsible for creating data silos, it's logical that changing the culture can eliminate them. Cultural change is difficult, so this is not easy. Critical to success is to tie removing data silos to a tangible data strategy development or data governance initiative. Communication is key: spreading the word about collaboration and sharing resources with others—even people in other departments—and garnering some quick wins that leaders can use to evangelize cultural change throughout the organization.
A gold standard for breaking down data silos is to gather all data into a cloud-based data repository where data from different sources can be stored (plus analytics performed on that data), and access can be given to users as appropriate, given security and compliance concerns.
Bringing together data stores is the most popular way to break down data silos. For example, extract, transform, and load (ETL) tools extract data from sources, consolidate it, and load it into another system. A variation on ETL is extract, load, and transform (ELT), which is more suitable for more complex and unstructured data. Writing scripts in SQL or Python can also integrate data silos, but it is time-consuming and ultimately more costly.
When data is centralized and stored in the cloud, the opportunity to give users self-service tools to access and analyze it without IT gatekeepers goes a long way to preventing new data silos from forming—and for achieving a data-driven business.
A robust data security and data management strategy helps break down existing silos while also preventing new ones from being created. An enterprise data strategy aligns data with business needs and cybersecurity best practices while establishing standardized, proven data policies and processes.
Data silos are part of a larger problem facing organizations today, which is massively fragmented data. The increasing proliferation of data across numerous locations, infrastructure platforms, and management systems not used every day represents the vast majority of an organization’s data and often has to be stored for a particular length of time to meet compliance mandates.
Teams that have yet to break down data silos can’t use all of their valuable data. They can’t fully digitally transform, moving to hybrid or multicloud environments to achieve objectives.
When fragmented data (also known as “dark data”) is scattered across an environment, the enterprise doesn’t know where all of its data is located, let alone what that data is—structured or unstructured, objects or files, or more. This can make siloed data an operational nightmare and a potentially serious compliance or security risk.
Three key factors contribute to massively fragmented data:
With Cohesity, organizations achieve business goals fast by:
The proven Cohesity approach eliminates data silos while dramatically simplifying infrastructure through an on-prem or SaaS solution. With Cohesity, organizations dramatically improve CapEx and OpEx and can use all of their data for competitive advantage.
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