What is Data as a Service (DaaS)?

Table of Contents

As the amount of data companies are faced with snowballs, the need for efficient data governance grows. An increasing number of organizations are turning to cloud service providers for data management. In this context, data as a service, often referred to as DaaS, is becoming an essential tool for managing data integration, data storage, and data analytics.

In this article, we'll take a closer look at what DaaS is and how it can help you improve the manageability and accessibility of big data in real-time.

Data as a Service Defined

So, what is data as a service? It's basically a cloud-based data management strategy for delivering data sets, data storage, processing, and analytics services. Just like software as a service (SaaS), it is a cloud computing strategy that runs applications over the network instead of on-premises. Again like SaaS, DaaS removes the need for the local installation and management of software.

Related reading: How to Transition to the Cloud – the Basics

Use Cases for DaaS

There is a wide variety of use cases for Data as a Service; the three use cases listed below are just a sampling:

Benchmarking

DaaS is a valuable tool for comparing your organization's performance against others. With Data as a Service, you can access global data and easily benchmark attributes such as financial performance, turnover, and other metrics with percentile breakdowns.

Business Intelligence

For internal users, DaaS can facilitate business intelligence by streamlining data standardization, unifying data sources, and automating analytics. With access to real-time information, data scientists can perform transformations and integrations dynamically and then use the insights gained to improve decision-making.

Data Marketplaces

Data marketplaces are another use case for DaaS. These platforms let users buy and sell data in one place. Data marketplaces facilitate the exchange of all kinds of data, such as demographic data from business intelligence platforms and consumer data from customer relationship management (CRM) systems). The ability to buy and sell all this data quickly is a valuable asset for data scientists.

Five Benefits of Data as a Service

While the SaaS business model has been around for more than a decade, it is only recently that businesses are adopting it on a broader scale. Not designed to handle large data quantities, cloud computing services are good for application hosting and basic data storage. The processing of larger data sets in the Cloud used to be more challenging when bandwidth was often more limited.

However, as price-efficient cloud storage and bandwidth have developed, DaaS has become a user-friendly and convenient solution that is just as beneficial as other SaaS services.

The benefits of DaaS:

Cost-optimization: The DaaS model is cost-effective. The flexibility of DaaS pricing ensures companies can devote the exact amount of resources to their data workloads and easily scale up or down those allocations as needs change. Plus, all you need is an internet connection. The DaaS model lets you access the services of a cloud provider, and you don't have to invest in expensive equipment like computers and servers.

More accessible data: A DaaS solution makes complex data available to more people, reducing organizational information silos. Teams can share data insights and make better decisions together.

Improved business intelligence: Quick and easy access to critical data; you can make decisions based on the correct data instead of gut feelings and hunches.

Automated maintenance: Your DaaS platform updates automatically, which frees up your dev teams to focus on more value-adding activities. Teams can access data insights from the cloud wherever they are in the world.

Less need for staff: When using DaaS platforms, there is no need to train people in-house to specialize in the data tool setup and management — the Daas provider can handle this.

Getting started with DaaS

Even though DaaS is a relatively new kind of solution, getting started is actually quite simple. Once you execute the initial setup and preparation, you will find the DaaS model eliminates much of the work associated with data management in your organization. Plus, the simplicity of DaaS solutions (and the technical support you can get from DaaS providers) means you can get your DaaS system up and running without having specialists in-house.

Getting started with DaaS includes the following steps:

Pick your DaaS solution. Consider pricing, reliability, scalability, flexibility, and integrations.
Sign up and activate the DaaS platform.
Migrate your data into the DaaS platform.
Start enjoying the benefits of DaaS.

Related reading: On-Premise vs. Cloud Data Warehouse

Cloud Services As a Competitive Advantage

The Daas solution easy to scale and highly flexible, allowing you to change and adapt your processes and experiment with new things. Compared to on-premises data solutions, DaaS has many advantages, ranging from easy setup to lower costs and higher reliability.

Whether your company already has experience with cloud services or has not yet migrated to the Cloud, DaaS can be a way to leverage the speed, reliability, and scalability that the Cloud offers. Interested in learning more about Integrate.io and the opportunities of cloud-based data management? Contact our team to book a 14-day demo and experience Integrate.io for yourself.

Cloud Integration

What is Data as a Service (DaaS)?

Data as a Service Defined