Data as a Service (Daas): Definition, Benefits, Challenges & its Future
As more and more companies turn to the cloud to improve their infrastructure and workloads, data as a service, or DaaS, is becoming a more popular solution for data integration, management, storage, and analytics. By including DaaS, companies can improve the agility of data workloads, decrease time-to-insight, and increase the reliability and integrity of their data.
Table of Content:
- What is Data as a Service (Daas)? and Example of Daas.
- Benefits of Data as a Service (Daas).
- Challenges of Data as a Service (Daas).
- Future of Data as a Service (Daas).
What is Data as a Service (DaaS)?
Data as a service (DaaS) is a data management strategy that utilizes the cloud to deliver data storage, integration, processing, and/or analytics services via a network connection.
DaaS is similar to software as a service, or SaaS, a cloud computing strategy that includes delivering applications to end-users over the network, rather than having them run applications locally on their devices. Just as SaaS removes the need to install and manage software locally, DaaS outsources most data storage, integration, and processing services to the cloud.
While the SaaS model has been famous for more than a decade, DaaS is a concept that is only now starting to see widespread approval. That is due in part to the fact that generic cloud computing services were not originally designed for handling massive data workloads; instead, they catered to application hosting and basic data storage (as opposed to data integration, analytics, and processing). Processing large data sets via the network was also hard in the earlier days of cloud computing when bandwidth was often limited.
Now, however, the advent of low-cost cloud storage and bandwidth joined with cloud-based platforms designed specifically for fast, large-scale data management and processing, has made DaaS just as effective and useful as SaaS.
Example of Daas:
DaaS offers convenient and cost-effective solutions for customer- and client-oriented companies. For instance, Fidelitone, a supply chain, and logistics management company, employed ARI’s DataStream DaaS solution to deploy parts catalogs into the customer channel.
Some other examples of DaaS providers include:
- Urban Mapping, a geography data service, provides data for customers to embed into their own websites and applications.
- Xignite is a company that makes financial data available to customers.
- D&B Hoovers provides customers with business data on different companies.
Benefits of Data as a Service (DaaS)
Compared to on-premises data storage and management, DaaS provides several key benefits with regard to speed, reliability, and performance. They include:
- Capability to transfer data easily from one platform to another.
- Data accessibility is controlled through data services, which increases data quality, as there is a single update point.
- Avoidance of the confusion and struggle that can occur when many “versions” of the same data exist in various locations.
- Because data is easily available, customers can take quick action and do not need an in-depth understanding of real data.
- Outsourcing of the performance layer, decreasing the overall cost of data maintenance and delivery. This helps build very affordable user interfaces and allows more feasible presentation layer change requests.
- Protection of data integrity by implementing access control devices such as strong passwords and encryption.
- Avoidance of “vendor lock-in.”
- Ease of administration and collaboration
- Unity among different platforms.
- Global accessibility
- Automatic updates.
Challenges of Data as a Service (Daas)
While DaaS offers various advantages, it also creates special challenges.
Unique safety considerations:
Because Data as a service requires companies to move data into cloud infrastructure and transfer data over the network. It can create security risks that would not exist if data remained on local, behind-the-firewall infrastructure. These challenges can be alleviated using encryption for data in transition.
Additional compliance actions:
For some companies, compliance challenges may also occur when sensitive data is moved into a cloud environment. This does not mean that data can’t be integrated or managed in the cloud. But simply that companies subject to special data compliance demands must ensure that they meet those demands with their DaaS solution. For example, they may need to host their DaaS on cloud servers located in a specific country in order to remain compliant.
Possibly limited abilities:
In some cases, DaaS platforms may limit the number of tools possible for working with data. Users are able to work only with the tools that are hosted on or compatible with their DaaS platform, rather than being able to use any tools of their choice to set up their own data-processing solutions. Choosing a DaaS solution that offers maximum flexibility in choosing tools mitigates this challenge.
Data shift timing:
Shifting huge volumes of data into data as a service platform can take time due to network bandwidth restrictions. Depending on how regularly your business needs to move data into a DaaS platform. This may or may not pose a serious challenge. If data bandwidth is limited, data compression and edge computing plans can help to accelerate shift speeds.
Future of DaaS
Information management experts believe that as more businesses figure out which data assets they can rent for competitive advantage. The DaaS market will continue to grow. DaaS is expected to be a launching point for both business intelligence and big data analytics markets. Gartner also still sees the Data as a Service market growing as more businesses start seeing data as a service as a suitable way to manage mission-critical data.
Data as a Service is nearly related to Storage as a Service and Software as a Service (SaaS). And maybe combined with one or both of these provision models. As is the case with these and other cloud computing technologies, Data as a Service adoption may be hindered by concerns about security, privacy, and proprietary issues.
Some companies are already leveraging DaaS to speed and explain the process of gaining insights from data, and to achieve larger data integration and governance. In turn, those companies are in a position to maintain an edge over competitors and streamline their internal operations through more efficient data governance and increased data integrity.
Hir Infotech offers an advantage of cloud-based data solutions (in addition to on-premises infrastructure, when desired) in order to collect, govern, transform, and share trusted data.
Try Hir Infotech today to start using a reliable and secure cloud-based data solution that performs at the speed of your business.
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