Understanding Data-as-a-Service (DaaS): Challenges, Benefits and Scope

DaaS is akin to Software-as-a-Service (SaaS), a cloud computing strategy, which includes delivering applications to end-users over the network, compared to having them run locally on their devices.

While the SaaS model has been well-known for more than a decade, DaaS is a concept that is witnessing a widespread adoption of late. This is because generic Cloud computing services were not primarily designed for managing enormous data workloads; instead, they were designed to provide application hosting and basic data storage (as against data integration, analytics, and processing). Moreover, in the earlier days of Cloud computing, processing huge data sets via the network was also difficult due to bandwidth restrictions.

However, today, the emergence of low-cost Cloud storage and bandwidth, coupled with cloud-based platforms designed specifically for rapid, large-scale data management and processing, has made DaaS just as pragmatic and beneficial as SaaS. Just as SaaS eliminates the necessity to install and manage software locally, DaaS deploys most data storage, integration, and processing operations to the Cloud.

What is DaaS?

Data-as-a-service (DaaS) is a data management strategy that utilizes the Cloud to deliver data storage, integration, processing, and analytics services via a network connection. DaaS, also called Data Services, illustrates several data-on-demand products available to business organizations. The benefit of the DaaS model of obtaining data is that the supplier manages data storage and preparation at the same time, ensuring data quality and data cleansing. They provide the data in a usable state and bear the cost of both time and money.

Some of the DaaS products available in the market include Oracle DaaS, IBM Watson Discovery News, SAP HANA Cloud, Snowflake, LegalVIEW, ISG InformX, Parrot Analytics, SamplePlus, Scout Vision, to name a few.

Features of DaaS

DaaS offers the following features:

Data prepared by a supplier and is delivered in an instant use format.
Can be blended into larger data set to enhance analytic validity.
Can be incorporated into a CRM, or other sales or marketing systems.

Benefits of DaaS

Compared to on-premises data storage and management, DaaS offers numerous significant benefits concerning speed, reliability, and performance. They include:

Least set-up time: Organizations can start storing and processing data almost instantly utilizing a DaaS solution.

Enhanced functionality: The probability of cloud infrastructure failure is very less, thereby ensuring DaaS workloads are less vulnerable to downtime or disruptions.

Higher flexibility: DaaS is more scalable and flexible than the on-premises alternatives since more resources can be assigned to cloud workloads immediately.

More cost-effective: Data management and processing costs are easier to maximize with a DaaS solution. Organizations can assign just the exact number of resources to their data workloads in the cloud and expand or limit those allocations according to the requirements.

Automatic maintenance: The tools and services on DaaS platforms are automatically managed and kept up to date by the DaaS provider, thereby excluding the need for end-users to self-manage the tools.

Low to no monitoring required: When using a DaaS platform, organizations do not need to maintain in-house staff specializing in data tool set up and management, as such tasks are managed by the DaaS provider.

Challenges with DaaS as a Solution

While DaaS provides many advantages, it also creates unique challenges as mentioned below:

Special security considerations: Since DaaS requires business enterprises to transfer data into Cloud infrastructure and over the network, it can cause security risks that would otherwise not exist if data stayed on local, behind-the-firewall infrastructure. These challenges can be checked using encryption of data in transit.

Additional compliance steps: For some business enterprises, compliance challenges may also crop up when sensitive data is transferred into a Cloud environment. This does not imply that data cannot be added or managed in the Cloud, but it just implies that organizations subject to special data compliance requirements must ensure that they meet such requirements with their DaaS solution. For instance, they may require hosting their DaaS on Cloud servers located in a particular country to remain compliant.

Possibly finite capabilities: In certain cases, DaaS platforms may restrict the number of tools available for working with data. Users can work only with the tools that are hosted on or compatible with their DaaS platform, compared to using any tools of their choice to set up their own data-processing solutions. This challenge, however, can be addresses by choosing a DaaS solution that provides optimum flexibility in selecting the tools required.

Data transfer timing: Transferring large volumes of data into a DaaS platform can be time-consuming. Depending on the organization’s frequency of transfer of data into a DaaS platform, this may or may not pose a serious challenge. If data bandwidth is limited, data compression and edge computing strategies can aid expedite transfer speeds.

Steps to Get Started with DaaS

The key steps to follow to get started with DaaS includes the following:

Factors to consider when choosing a DaaS offering include:

Price
Scalability
Reliability
Flexibility
Ease of its integration of the DaaS with present workflows and how it absorbs data into it.

Sign up for and activate your DaaS platform.
Move data into the DaaS solution. The time required for data migration depends on the volume of data you want to migrate and the speed of the network connection between your local infrastructure and DaaS.
Begin taking advantage of the DaaS platform to deliver faster, more reliable data integration and data insights.

Pricing Information

DaaS is priced as per the following criteria:

DaaS products are generally priced by volume; more data available equals a higher price. However, some data is of higher value than others.
Data services may also be priced according to the perceived value they offer. Therefore, pricing depends on the industry and the purpose of usage of the intended data.
Some data-on-demand services are priced by calls. Users of the data are charged when they access data in this case.

Final Thoughts

Given the widespread focus on the Cloud spanning numerous industries, and among both large and small business enterprises, there is strong reason to believe that DaaS adoption will continue to further rise simultaneously with other Cloud services. Considering how DaaS solutions help in streamlining business operations and obtaining better insights from data, companies across various sectors have already started leveraging the many benefits of DaaS. Supporting the growing trend of DaaS adoption is a statistics report from Market Research Future that states – “Data-as-a-service market is estimated to grow at a CAGR of 39% reaching $12 Billion by 2023.”