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Introduction To Data as a Service (DaaS)

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By: Nihad Hassan

June 1, 2021

In today's Information Age, most data is created digitally and not on paper; the sum of digital data is massive to the extent that no one can predicate its accurate size. According to Statista, the volume of data/information created, captured, copied, and consumed worldwide has reached up to 59 zettabytes in 2020. Handling the massive amount of data, special tools and technologies were invented. Utilizing cloud storage to store data outside organizations' local data centers has become the norm. Today, terms such as Big Data have become widespread to help organizations analyze the large amounts of data stored in digital format, thus assisting organizations in making data-driven decisions.

The ongoing spread of the Coronavirus has forced most global organizations to change their operating philosophies. The most noticeable change was in the work environment, transitioning to working remotely. This led to an increase in the adoption of cloud services to cope with the growing number of people accessing an organization's online resources. The new working scenario has shifted a significant amount of data to become stored on cloud services; this cloud deployment model is known as Data as a Service.

Implementing cloud services is projected to increase explosively within the next few years. According to markets and markets, the global cloud computing market size is expected to reach $832.1 billion by 2025, making it occupy the number one rank in IT spending among all other IT sectors. The growth of the cloud computing market has significantly accelerated during the height of the COVID-19 crisis.

This article will shed light on the Data-as-a-Service model, describe its benefits and implementation challenges.

What is Data-as-a-Service?

Data as a Service (DaaS) is a type of cloud deployment model where data is stored in cloud data centers instead of storing it locally on-site. DaaS data can be deployed either on a hybrid, public or private cloud.

DaaS was developed as a response to the massive quantity of data generated in today's digital interactions. Organizations can now utilize different software solutions to analyze their data while stored in cloud platforms without managing and maintaining the data locally.

Although DaaS offers numerous benefits, it presents various privacy risks as data must be managed by a third-party provider, who may have access to the data in one way or another.

Benefits of DaaS

DaaS brings many advantages to its users, such as:

  1. Reducing data management costs: As with any cloud computing model, transferring the burden of managing an organization's data to a third-party provider will significantly reduce the cost of managing, maintaining, and securing this data.

  2. Improves data quality: in DaaS, data is accessible only via data services; this improves the data quality and increases its security, as data is accessed through one connection point.

  3. Reduce data confusion: By implementing a cloud platform to store data, all users will see the same version of data when accessing it from any geographical location instead of having multiple versions stored in different places.

  4. Improve data security: By protecting the cloud with passwords and encryption, only authorized users can access it.

  5. Simplify data administration: By having all data stored in one location, administering it becomes easier.

  6. Global accessibility: Cloud data is accessible from any place worldwide.

DaaS challenges

As with any technology, there are some challenges when implementing it. The following list the main challenges that concern users:

Privacy concerns

The privacy of cloud data has been under hot debate since the creation of cloud services. When an organization chooses to move its data to cloud providers, users and other parties will have concerns about their data privacy. DaaS data is not considered bound to any business-critical applications. Instead, the data is placed there for extended storage or later processing.


One of the benefits of using the DaaS model is the ease of data accessibility from any geographical location. While this is considered a good thing (streamlining user experiences when working with data from different remote areas), it generates security concerns. For instance, no one can guarantee that DaaS providers will not fall victim to hacking attempts, data breaches, and other malware attacks like ransomware. Clients of DaaS providers cannot manage the security controls, making it difficult for them to view their data's security. Also, the ease of access to DaaS data makes the data susceptible to various cyberthreats. For example, if a user accesses cloud data via an endpoint device and is infected with ransomware, the infection can automatically spread to the stored DaaS data.


DaaS is data stored in cloud servers; these servers do not always exist in one geographical location. Most cloud providers place their cloud servers in various geographical locations (across a country or several countries) to serve their client base who live in different regions. It isn't easy to guarantee that your cloud data is stored in one server. This makes cloud data subject to additional data protection and compliance requirements. For example, the EU's General Data Protection Regulation (GDPR) is a legal framework that creates guidelines for collecting and processing personal information from individuals who live in the European Union (EU). This regulation in EU law is implemented in any organization that stores or processes EU citizens' data. If an organization does not have a presence in the EU but deals with European customers, it is subject to the GDPR.


As with any cloud computing model, there are benefits and disadvantages when using it. Cloud computing has become a pivotal technological tool for managing countless digital transformation tasks. Organizations should consider the security and privacy implications of DaaS services before moving any sensitive data to the cloud and create security controls to protect their data from malware attacks.

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