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Glossary
Data Infrastructure

Software as a Service (SaaS)

SaaS (Software as a Service) is a model in which the software is hosted over the Internet and made available as a subscription service.

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What is Software as a Service(SaaS)?

In contrast to traditional software models, where the software is installed on the user's own computer, SaaS users access the software via a web browser or a mobile app.

The SaaS provider assumes full responsibility for providing, maintaining and updating the software, while the user only has to pay for using the software.

As part of the data infrastructure or the data strategy Let's focus on the right solution together with our customers.

What are the benefits of SaaS?

  • Lower initial investment: No high upfront costs for software licenses and hardware.
  • Lower operating costs: The provider takes care of maintenance and updates.
  • Scalability: Easy to adapt to changing business requirements.
  • Accessibility: Accessible from any device with an Internet connection.
  • Constant update: The provider always guarantees the latest version.
  • Lower maintenance costs: Updates and bug fixes are provided by the provider.
  • Mobility: The software can be used from anywhere.
  • Convenient collaboration: Easy data sharing and editing.

What are the disadvantages of SaaS

  • Data security and control: The user's data is stored on the provider's servers.
  • Dependency on provider: The user is heavily dependent on the provider.
  • Lack of flexibility: SaaS solutions are standardized and offer fewer customization options.
  • Performance and availability: Depends on the Internet connection and provider's performance.
  • Long-term costs: Subscription fees may exceed the total cost of on-premises software.
  • Hidden costs: Additional costs for functions or data storage are possible.
  • Contract commitment: Cancellation periods and contract terms can make it difficult to switch to another provider.
  • Possible integration issues: integration with other systems can be difficult.
  • Potential reliance on proprietary interfaces: Switching to another provider can be complicated by proprietary interfaces.

Applications for SaaS

SaaS is an important topic in the area of data analysis, as it enables companies to use data analysis tools and platforms without large upfront investments or ongoing maintenance costs.

Note: Our team benefited from the support of AI technologies while creating and maintaining this glossary.

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Data Architecture

The right tools in the right place. Update the existing infrastructure or renew most of it.

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Data Organization

So that the handling and responsibility of data is structured and everyone knows its responsibilities.

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Data Strategy

When what happens how and why — that explains the data strategy.

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