Data-as-a-service is a data management strategy built on the premise that data can be delivered to users on-demand via the cloud. Also known as “DaaS,” it joins the slew of as-a-service offerings that originated from the concept of software-as-a-service (SaaS), including Platform-as-a-service (PaaS), RPA-as-a-service (RPaaS), Testing-as-a-service (TaaS), Security-as-a-service, and Cybercrime-as-a-service (CaaS).
With data-as-a-service, users no longer have to install software locally for data storage, integration, and processing. Instead, data management is done in the cloud, like in all the other as-a-service technologies.
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Instead of downloading different types of data, storing it locally and processing it to become useful for your organization, DaaS makes it possible for companies to access the data they need as a ready-made product.
The DaaS vendor prepares the data, which can be used as-is or integrated into a larger data set for further analysis.
DaaS is like buying a cake instead of baking one. All you have to do is go to a cake shop, choose the flavor or variant, and pay for the cake. In contrast, when you bake a cake, you need to buy all the ingredients, and sometimes, go from one store to another to find everything you need.
With DaaS, companies don’t have to download data from different sources since the product can give them the data they need. That is reflected in the image below where DaaS gets data from varied data sources and organizations from different industries obtain data from DaaS.
On top of that, employees can access the data using any device, regardless of their location. All they need is a network connection to access and analyze the data.
Data-as-a-Service Examples
DaaS vendors can provide data for a specific industry, such as Oracle’s DaaS for Marketing, which is explained in the video below.
DaaS providers can also focus on providing threat intelligence to cybersecurity professionals. Other providers help real estate investors gain insights into pricing, crime data, and other factors in a specific area.
Data-as-a-service can also come in the form of data marketplaces where organizations can access third-party data. An example of this is Snowflake. Data for specific industries, such as insurance, retail, and life sciences, are available, ready for analysis or integration. In this setup, it’s not usually the DaaS provider who processes and owns the data, but its third-party data sources.
Benefits of Data-as-a-Service
Enterprises have long known the value of data, with experts even dubbing it “the new oil.” However, it’s only fairly recently that DaaS has been commercially adopted. Thanks to the availability of cheaper cloud storage and bandwidth, DaaS solutions have gone mainstream.
With DaaS, organizations enjoy the following benefits:
- Portability: Data is not locked into a single platform to be moved from one platform to another.
- Data integrity: Since you can implement access control, data integrity is preserved.
- Ease of access: The data can be accessed and managed anywhere using any device.
- Cost savings: Companies can allocate a specific budget for data management and processing and adjust the DaaS solution’s data workloads.
- Automatic updates and maintenance: The DaaS vendor manages the solutions, so you don’t have to worry about maintenance.
- Fewer human resources: There’s no need to have in-house experts to manage the solution, and data analysts can focus on their main tasks.
Challenges of Data-as-a-Service
Among the major challenges in implementing DaaS solutions are security and compliance. Storing data in the cloud and accessing it over the network exposes the company to cybersecurity risks. Encrypting the data using the latest encryption standards can help lessen risks.
Also, the DaaS provider would be part of your supply chain and, therefore, should be included in supply chain risk management and monitoring.
Moving and storing sensitive data in the cloud could also require additional compliance requirements for certain organizations. Before implementing DaaS solutions, it’s best to check data privacy regulations governing your industry and country.
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Simply put, data-as-a-service turns data into a product, so organizations can readily consume it. Data-based decisions can be made a lot quicker since data integration and management are simplified.
