In an era where data drives decision-making and innovation, understanding and leveraging data as a service (DaaS) has become crucial for businesses across an exceptional amount of sectors.
Therefore, it’s equally crucial to understand not just the benefits of adopting DaaS to improve organizational data quality, but the challenges inherent in doing so.
So, let’s take it from the top.
Data as a service (DaaS) is a cloud-based model providing scalable and accessible data management solutions. It allows organizations to access, analyze, and utilize data in real time, regardless of geographical location, on-premises hardware, or available IT resources.
DaaS integrates cloud computing with data storage and analytics to serve as a foundational element for a variety of digital initiatives and data consolidation strategies. Its ease of use and flexibility make it a valuable tool in industries where organizations seek to leverage data for informed decision-making and operational efficiency—healthcare, education, financial services, ecommerce, and telecommunications, for example.
Despite the variety of industries that are leveraging DaaS to their advantage, most real-world use cases share some common yet incredibly valuable benefits of leveraging data as a service.
Cost-effectiveness: Out of the box, organizations using data as a service can begin to lower costs associated with their data management. Factors impacted by DaaS commonly include expenses for data storage, software maintenance, and hardware which, as noted by Gartner, shifts the financial burden from capital expenditure to operational expenditure.
Data quality and consistency: Organizations that use DaaS either begin or come to manage all their data as a central, unified data source. Doing so enables more effective data governance, as uniform data standards can be implemented, redundancy reduced, and updates and maintenance simplified.
Improved efficiency: DaaS solutions streamline data processing and analytics, saving valuable time (AKA $) that would otherwise be lost collecting and managing disparate, cross-departmental data.
Data accessibility and flexibility: Centralization through a DaaS platform also results in a wider range of data being accessible anytime, anywhere, and without the traditional constraints of in-house infrastructure.
Scalability: Eliminating the traditional reliance on infrastructure with a DaaS solution also increases operational agility, as it allows organizations to scale data usage up and down based on need.
Data security and compliance: Reputable DaaS providers ensure that data is secure and compliant with all relevant regulations (e.g., GDPR or HIPAA), which are increasingly vital for all business organizations, not only those historically known for handling especially sensitive information.
Enhanced decision-making: With access to consistent, high-quality, real-time data, organizations can make better-informed decisions, leading to better business outcomes over time.
As with many aspects of data management, the benefits of data as a service also bring some common challenges. (Mind you, challenges that can be amplified in organizations that lack effective data governance.)
Here are some key concerns:
Lack of legal protection and clarity: While unfortunate, not all DaaS providers operate under legally binding agreements specifying terms of service (ToS), data usage rights, or responsibilities. In these situations, organizations are operating with an unacceptable lack of clarity, which can lead to costly disputes and legal challenges.
Compliance risks: As noted in our benefits, different industries are subject to a myriad of overlapping and independent regulations, ranging from HIPAA in healthcare to Europe’s GDRP. Any service-level agreement (SLA) worth its salt will certainly outline how the data provided through service will and will not be used. But outlines can’t enforce outcomes. Therefore, organizations using DaaS solutions need to be vigilant in remaining compliant.
Data security and privacy concerns: While comparatively unlikely, contracting with a DaaS provider does expose an organization to additional security and privacy concerns. Due to the risks of data breaches or unauthorized data access, industries that deal in sensitive personal data are particularly vulnerable to these risks.
Uncertain data quality and reliability: Again, despite a well-defined SLA, there may be no guarantees the quality, accuracy, and consistency of the data provided will be to the levels promised. This can be especially problematic in analytics-heavy industries where decision-making hinges on data quality.
Financial uncertainty: As DaaS services are built to scale with demand, their pricing models tend to be equally flexible. However, customizations and integrations with existing systems can require additional investments. Moreover, small to medium-sized businesses should also be aware of any costs associated with data transfer and bandwidth usage, which can become significant if data access frequency is high.
Intellectual property issues: Finally, the rapid adoption of AI and machine learning models is making it clear that contracting with data providers like a DaaS can lead to issues of intellectual property (IP)—namely, confusion regarding the ownership of data and derived insights.
So, all the upsides and potential downsides of data as a service present a bit of a pickle for data leaders and managers. Can the benefits of DaaS outweigh the risks?
They can, but not without the help of a well-drafted contract.
Think of the best possible DaaS SLA as the best possible foundation for a house. It’s essential. But the house built on top of it is where the living takes place. A data contract rests on the foundation of the SLA, but its own respective construction keeps things operating as they should (not just as they could). Bathtubs don’t fall into kitchens. Stairs go up and down between different floors. Hallways don’t lead to brick walls.
When implemented as part of the DaaS sales cycle, a data contract can address the following:
A well-drafted data contract can provide the legal clarity and protection that might be missing in a standard ToS (terms of service) agreement or SLA. It can clearly define the rights and responsibilities of both the provider and the client, including specifics on data usage, handling, and ownership. This reduces the risk of disputes and legal challenges.
Data contracts can be tailored to include specific compliance requirements relevant to different industries. They can outline procedures and protocols to ensure adherence to regulations like HIPAA or GDPR. By explicitly stating how data should be handled to remain compliant, these contracts enforce compliance more effectively than general outlines in an SLA.
Through a data contract, specific security and privacy measures can be stipulated, ensuring that the DaaS provider adheres to agreed-upon standards. This can include encryption protocols, access controls, and data breach response strategies, thereby mitigating risks associated with data security and privacy.
A data contract can include provisions for data quality and reliability, setting clear standards and expectations. It can also provide remedies or compensations in case the data provided doesn’t meet the agreed-upon standards, thus ensuring that the provider maintains high-quality data.
While DaaS pricing models are often flexible, a data contract can include detailed financial terms, including fixed costs, variable costs based on usage, and caps on cost increases. This can provide more predictable financial planning for the client, especially small to medium-sized businesses.
The contract can clearly address issues related to IP, such as the ownership of the data, rights to derivative works, and usage of AI and machine learning models. This clarity is crucial in the modern data landscape where IP rights can be complex and contentious.
This is why we highly recommend integrating the data contact drafting process into what would typically be considered best practices for implementing data as a service within your own organization.
By following these best practices, organizations can effectively choose a DaaS solution that aligns with their needs and strategic goals.
Data contracts, as highlighted in this article, should then absolutely serve as the means to ensure you can get the most out of any DaaS provider you happen to choose.
And for those looking to stay ahead of the curve and embrace the future of data management, make sure you join our product waitlist and be on the right side of data history.
Gable is currently in private Beta. Join the product waitlist to be notified when we launch.
Join product waitlist →