{"id":18871,"date":"2023-06-01T05:23:20","date_gmt":"2023-06-01T09:23:20","guid":{"rendered":"https:\/\/www.sage.com\/en-us\/blog\/?p=18871"},"modified":"2026-01-22T07:02:45","modified_gmt":"2026-01-22T12:02:45","slug":"hidden-cyber-risks-of-financial-data-silos-for-saas-companies","status":"publish","type":"post","link":"https:\/\/www.sage.com\/en-us\/blog\/hidden-cyber-risks-of-financial-data-silos-for-saas-companies\/","title":{"rendered":"Hidden cyber risks of financial data silos for SaaS companies"},"content":{"rendered":"
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\n\t\t\t\t\t\t\tTechnology & Innovation<\/a>\t\t\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t
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\n\t\t\t\t\t\tHidden cyber risks of financial data silos for SaaS companies\t\t\t\t\t<\/h1>\n\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t\t\t

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\n\t\t\t\n\t\t\t\t\"David\t\t\t\tDavid Appel<\/span>\n\t\t\t<\/a>\n\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t<\/div>\n<\/div>\n\n\n\n\n\n

As a SaaS CFO, you know you\u2019re responsible for working with large sums of data\u2013about financial processes, customer behavior, and much more. What you might not know, however, is that putting unnecessary walls up around your data can have terrible consequences for your firm\u2019s productivity and efficiency. <\/p>\n\n\n\n

Finance teams are under increasing pressure to protect sensitive financial data from cyberattacks and comply with ever-evolving regulations. Unfortunately, many organizations still rely on outdated financial management tools and processes that create unnecessary risks. <\/p>\n\n\n\n

Read on to explore what data silos are, why they are problematic for organizations, and how consolidating financial data can improve security and compliance. We will also discuss how you can migrate to the cloud to unlock your data\u2019s full potential and improve data management workflows. <\/p>\n\n\n\n

What is a data silo? <\/h2>\n\n\n\n

So, you might be asking, what is a data silo? <\/p>\n\n\n\n

The term \u201cdata silo\u201d bears a striking resemblance to the term grain silo, the large metal structures that store large quantities of grain. In the same way that a grain silo closes off grain, a data silo is a large accumulation of data controlled by one department and inaccessible to the organization as a whole. <\/p>\n\n\n\n

In simple terms, a data silo is a situation where different teams within an organization are working with different versions of the same data, and there is no integration between these different data sources. For example, different departments within an organization may use different software systems to collect and store data, leading to unintentional data silos. This can cause inconsistencies, errors, and conflicts which ultimately put the organization at risk. <\/p>\n\n\n\n

As cloud adoption rates have climbed for SaaS accounting in recent years, teams have discovered the usefulness of a different method: the data lake. <\/p>\n\n\n\n

RELATED: <\/strong>Unlocking Digital Transformation In SaaS Organizations<\/a><\/p>\n\n\n\n

Data silos vs data lake<\/h3>\n\n\n\n

Data silos and data lakes<\/a> are two different approaches to managing an organization\u2019s data. As we\u2019ve discussed earlier, data silos use the incredibly restrictive approach of putting one team or department in charge of vast quantities of data. Data lakes are a centralized repository for all types of data, which can be accessed and analyzed by different teams within an organization. <\/p>\n\n\n\n

Data silos<\/strong> are collections of data that are stored separately from the rest of an organization\u2019s data. If you do this as a SaaS CFO, your siloed data is likely strategically critical for other teams outside your department. This disconnect between teams creates considerable inefficiency around data gathering, leading many accounting teams to migrate to the cloud and embrace data lakes instead. <\/p>\n\n\n\n

Data lakes<\/strong>, on the other hand, are large, cloud-based repositories of centralized data that are designed to make it easy to store, access, and analyze all of an organization\u2019s data in one place. This data is securely stored within an organization yet remains freely accessible to all departments and people who might need it. <\/p>\n\n\n\n

When it comes to the issue of data silos vs data lakes, there\u2019s no question that data lakes offer several advantages over data silos. The data lake approach saves time and money, prevents manual errors, and helps your organization stay agile. They make it easier to combine and analyze data from multiple sources, and they can provide a more complete view of an organization\u2019s data. Data lakes also make it easier to scale an organization\u2019s data infrastructure as it grows, as new data sources can be added to the data lake as needed. <\/p>\n\n\n\n

What causes data silos?<\/h3>\n\n\n\n

In general, organizational silos<\/a> are created when individual departments lose sight of the broader company goals and instead focus on local goals. Ultimately these issues tend to culminate from a lack of team mentality, poor communication between groups, uncertainty in company goals, and misguided incentives. <\/p>\n\n\n\n

Data silos are natural byproducts of a company\u2019s growth\u2013though, they don\u2019t have to be. As companies expand and take in more information, various teams within the organization tend to get walled off between other departments, unless you\u2019ve opted for the cloud from day one. <\/p>\n\n\n\n

Because of this, siloed data is often a silent threat. It can be hard to spot until you\u2019re already on your way to creating problems for your company. <\/p>\n\n\n\n

Two of the most significant contributors to the creation of data silos include:<\/p>\n\n\n\n