What is Data as a Service (DaaS)?
Data as a Service (DaaS) outsources complex services to help organizations use data to drive their decision making, turning big data into actionable customer insights.
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Data as a Service (DaaS) is a strategy that enables you to gain insights from your sprawling, complex IT environments and use data to drive decision making. DaaS simplifies the process of harnessing big data and turning it into actionable, customer-centric insights.
Instead of hosting and managing complex data solutions, such as data aggregation, analysis, cataloging, looping, mapping and virtualization, DaaS delivers these services through third-party providers.
How does the DaaS model work?
Like Software as a Service (SaaS) that delivers applications to end-users over a network, removing the need for users to run their own apps locally within their environment, the DaaS model works by outsourcing the storage, integration, analysis and processing of data to third-party providers. By doing so, it removes the need for the end-user to perform such operations locally.
Using this model for data is a relatively new concept that has only recently become widely adopted. Traditional cloud computing services weren’t designed to handle massive data workloads, and networks didn’t have the bandwidth required to process them.
But now? Lower-cost bandwidth and cloud storage, in conjunction with cloud-based platforms explicitly built to process large-scale data management, are making Data as a Service highly beneficial in a number of ways.
What are the benefits of DaaS?
Data as a Service can have a massive impact on organizations in terms of both revenue and broader business benefits. Critical advantages of DaaS include:
Data monetization: Gathering enough data is no longer a concern for most organizations. The larger issue is organizing and understanding the vast amounts of information they need to process daily. DaaS enables you to increase the accessibility of data and gives you the tools you need to gain full value from it.
Improved decision-making: Getting maximum value from all your data sources helps improve your decision-making accuracy. Combining customer and partner information with open data sources and purpose-built analytics offers a comprehensive view of your business. This allows you to spend more time analyzing and taking action on data rather than searching for it.
Rapid innovation: By putting data at the center of your business, you’re able to grow faster with better-informed strategies. This is crucial to encouraging innovation and enabling teams to take new initiatives from the idea stage to production rapidly.
Reduced costs: Gaining extra insight helps avoid wasting time, money and resources on bad decisions and ineffective processes. DaaS helps you to lower the risks of incomplete or poor-quality data sets.
Simplified setup and maintenance: You can immediately start processing and storing data as soon as your DaaS solution is up and running. The services and tools are then managed and updated by your DaaS provider, which removes the need for your employees or users to manage them.
Improved customer experience: DaaS enables you to run predictive analysis on your data, which can help you better understand consumer behavior and patterns. This allows you to offer more personalized experiences and build customer loyalty.
Establishing a data-driven culture: The DaaS model helps you break down data silos and deliver the information your employees and teams need — when they need it. This is crucial to fostering a data-driven culture, which helps you put data at the heart of your decision making, practices and processes.
What are the challenges associated with DaaS?
Despite all the clear benefits, Data as a Service isn't perfect. This approach, like almost anything, can present your organization with several common challenges, including:
Data complexity: DaaS involves handling data from across your entire IT environment rather than just one department or problem. This type of project, therefore, requires a comprehensive roadmap that can be time consuming, especially when dealing with massive data sets.
Senior executive involvement: Given the complex nature of DaaS and rolling out a data-driven culture, this journey often demands an enterprise-wide strategy that requires direction from senior executives. This can present challenges when it comes to delivering the process and ensuring everyone is on the same page.
Security considerations: Keeping data secure is a key priority given the evolving, increasingly sophisticated nature of the cyberthreat landscape. This is especially challenging when dealing with vast volumes of data and moving that information into the cloud. This makes it even more important to implement appropriate data governance, privacy and security policies that can ensure quality control. It's also critical to use tools that encrypt data when it’s in transit to the cloud. No matter what, your DaaS strategy needs to include processes that can make sure all your data assets are locatable and well documented.
Compliance challenges: Moving sensitive information into the cloud can create significant concerns around compliance. For example, you may need to ensure your DaaS program is only hosted on cloud servers located in specific countries to ensure regulatory compliance.
Maximize the value of your data with DaaS
While every approach comes with both positives and negatives, at the end of the day, DaaS enables your organization to get the most out of your data by outsourcing the process of analyzing, managing and processing information to third-party providers.
For many organizations, this makes it a very valuable tool.
Discover how WWT can help you unleash the power of your data with technology that enables you to understand, manage and leverage information.