Challenges to Data-as-a-Service
Data-as-a-service, or DaaS, is one of the many available-as-a-service offerings today. It’s a method of provisioning and distributing information to customers and consumers over a given network. In most cases, that network is the Internet. DaaS uses cloud-based connectivity to facilitate many of its data transactions, enhancing speed and mobility for enterprises.
While DaaS is widely known for its ability to improve the accessibility of business-critical datasets and information, it isn’t without its unique set of challenges. From ongoing concerns aboutand governance to security and privacy pitfalls, it’s important to know the applications and limitations of DaaS.
cybersecurity continues to impact the vast majority of technology, any enterprise or organization must utilize secure data management services that prevent breaches, attacks, or infiltration. In many cases, the data parsed by a DaaS platform is sensitive. Key data points may be unprotected if vendor security isn’t well-implemented or maintained. It’s important to capably verify these vulnerabilities before they become a recurring problem. is a cloud-based technique, there are always concerns surrounding data accessibility. While Data-as-a-Service aims to improve consumer accessibility, ensuring that the consumer is the only one gaining enhanced access is important. As
In most instances, this is a conversation you need to have directly with the DaaS vendor. If applicable, request white papers and case studies with concrete examples that solidify the efficacy of the vendor’s data security protocols. Whenever possible, do a live demo to get a feel for any new platform and understand the security tools that back it. Your DaaS selection must give insights into your data delivery methods and performances without compromising your reputation or integrity.
In many cases, it’s difficult to ensure connectivity between your organization’s data profiles and a DaaS platform or solution. As a result, you must find the right-fit applications for your unique enterprise needs. Otherwise, you run the risk of negatively impacting platform integrations. At its core, data governance relates to managing data availability, integrity, and usability. It is also interconnected with data security in many ways as well. When applying effective data governance levels , you do your best to ensure that none of your data is compromised. This helps guarantee that your data is consistent and trustworthy, even if you’re working at scale.
When moving sensitive data into a cloud infrastructure, you may need to take additional compliance steps to ensure your organization remains up to code. Of course, this doesn’t mean that you can’t host data in the cloud or that you can’t rely on cloud integration and management. It simply means that you must follow more precise data compliance protocols to ensure your organizational information meets developing quality standards. Sometimes, you may need to host your Data-as-a-Service modules on cloud servers based in specific countries. This will vary based on location, organizational models, and defined use cases.
In some cases, DaaS may limit the number of tools you have at your disposal. For example, you may be restricted to devices that your DaaS platform hosts itself. In other instances, you may be limited to devices that meet defined compatibility requirements. These are things to discuss ahead of time with your DaaS vendor. While DaaS has many challenges, it’s still one of the best techniques for ensuring a robust data flow. Enterprises and organizations across the world can leverage DaaS for stronger data management.