April 27, 2021
The software as a service, also known as SaaS, model has enabled users to access various useful software tools regardless of the capacity to maintain them. In this framework, the software is hosted online and available to the users on demand. But what goes for software can also go for data. This idea gave rise to data as a service, or DaaS, which allows companies to outsource data storing and maintaining services. Businesses now resort to DaaS providers to have all the benefits of leveraging data without the burden of storing it.
Data as a Service is defined as software sold by data providers that provide data to end-users regardless of location or connection to said data provider. DaaS is similar to Software as a Service; however, instead of providing customers with software access, data providers provide their customers with data via raw data or API access. Let's take a closer look at the rise of DaaS.
A technology reminiscent of what we know today to be cloud computing was developed from the middle of the 20th century, primarily for military and scientific community information sharing needs.
However, the term itself was coined for business use in 1996 as the technology was slowly but surely growing into the shape we know today. Cloud computing is broadly defined as the model of utilizing the network to make computing resources available on-demand for the users. This on-demand availability is recognized as one of the essential features of cloud computing, among others as broad network access and resource pooling.
And this is precisely the characteristic that enables data as a service, which is one of the most important opportunities provided to contemporary businesses by cloud computing. DaaS providers are storing large quantities of data useful for business needs while the users only need to choose when and what to assess for their particular purposes.
Software as a service has been utilized by business and private users for quite some time and has become commonplace in computing. However, data as a service grows in importance as the volumes of data produced and used by businesses grow at accelerating rates. This also means that data ages faster, making it harder to collect and store applicable data, which in turn makes the availability of the latest data on-demand more necessary than ever before.
Therefore, there is every reason to expect further developments in data as a service and its role in business.
Data as a service was fast to catch on in business as numerous ways have thus far been found to improve functionality by getting data on demand. And DaaS providers are offering on-demand solutions for every field of business. Here are a few Data as a Service examples as it is utilized in business and finance today.
Companies selling B2B products and services turn to DaaS providers in order to supplement their datasets for better market segmentation. Various firmographic information on-demand allows drawing a clearer and more up-to-date picture of the prospect base. This includes, for example, public record data on companies that have just received certain kinds of funds or opened new locations.
In B2C industries, data as a service is especially useful to find and target customers as soon as they express a level of interest online. For example, furniture retailers can get on-demand data on those who have recently posted on social media that they are looking for an armchair or a couch. This means fresh and usually rather rare information exactly at the right time. Naturally, what works in the furniture industry can very well be adopted by most if not all B2C retailers.
Investors use data as a service to get the early signals of emerging opportunities. Here the on-demand availability means that important market events and signs of growth or decline of particular companies will not be missed. Additionally, investors can choose the needed volume of data to build their investment models or train algorithms.
Finally, this goes for almost every company. Data as a service helps to break down what is known as data silos, that is, the lack of sharing of data between different departments in the same firm. Data collected by one department might be useful to another, yet it is often only accessible within the department. Data as a service removes these constraints by allowing access to all the outsourced data.
As more businesses start seeing data as a service as a suitable way to manage mission-critical data, the DaaS market will continue to grow. DaaS provides a launching point for both business intelligence and the big data analytics market.
- Harriet Chan, Co-Founder of Cocofinder
It’s easy to see that the benefits of DaaS are numerous when properly utilized. However, there are a few challenges that need to be solved in order to use data as a service to an advantage. Below are the main positive and challenging aspects of employing data as a service for business needs.
One of the main advantages of data as a service is that the DaaS provider is charged with maintaining high data quality. Data has to be of high quality in order to extract true value from it and use it efficiently. Thus, quality maintenance is an extremely important part of handling data and also one that can take up a lot of time and resources. Freed from this burden, businesses are available to direct their human and technological potential for tasks aiming at added value and get their data readymade.
This benefit of on-demand data is pretty much impossible to match by using internal data sources. DaaS helps to overcome the limitations of location or infrastructure to access data wherever and whenever necessary. This means that data can be accessed by users that do not themselves have the means to collect and store it at the necessary level. Furthermore, DaaS can be accessed quickly and on multiple devices, making it even more comfortable to use.
Companies can access the types and quantities of data that are needed for their particular purposes. This flexibility makes data as a service cost-efficient, as you only pay for what you need instead of spending money on collecting and storing superfluous data. Additionally, as there is no need to spend money on personnel and infrastructure for data maintenance, the saved resources will usually exceed the costs of acquiring data on demand.
As DaaS requires moving data into the cloud, this raises additional concerns regarding the privacy of important organizational information. When shared over the network, confidential information becomes more exposed than it would be on the internal servers. This challenge may be met by sharing encrypted information, as well as using a reputable DaaS provider.
Similarly, there are some considerations regarding security that businesses have to pay attention to when implementing DaaS solutions. Wider accessibility provided by having data in the cloud also means additional vulnerabilities that may lead to security breaches. Thus, DaaS providers should ensure that strict security strategies are implemented in order to keep data as a service a growing trend in business.
Another issue arises if DaaS providers allow a limited range of tools that can be used to work on the data. In some cases, providers can only offer the tools they host for data handling, which may be very limited compared to the tools needed. Therefore, it’s advisable to choose the provider that offers the most flexibility, which might make this challenge obsolete.
Integrating technologies like 5G and Cloud Computing with proper security protocols around DaaS can be a game-changer in making the vast amount of data and information accessible from anywhere to anyone. They can unlock the true potential of data, eliminate the data silos, democratize data science and its applications better, provide a new level of experience to mankind, and form the basis of the next revolution of software and applications.
Ankush Sharma, Co-Founder of DatatoBiz
The next important chapter in cloud computing and the “as a service” industry is also data-related. Now industry professionals are talking separately about big data as a service or BDaaS as a specific category of cloud services. The addition of “big” to data as a service does not mean that there simply is more data, but rather that the whole data analytics package is available as a service. The providers of BDaaS are offering data and the analytical tools used for handling the data and extracting insights.
It's projected that the BDaaS market value will reach USD 52.75 billion by 2026. Therefore, it’s worthwhile to look into BDaaS as we move forward. But for now, many companies will find that data as a service is the central on-demand solution for business needs.
In conclusion, on-demand services enabled by the cloud provide great alternative solutions for businesses that don’t have the capacity to store large volumes of data on their own servers. Even with such capacities in place, it’s often cheaper and easier to get the data on demand. And even though there are some challenges that come along with implementing data as a service, they are far from unmanageable. Therefore, since the added value so far clearly exceeds the risk, it’s likely that companies will continue to utilize data as a service and invest in its growth potential.