- Data is the New Oil, and DaaS is the Drill
- The Evolution of DaaS
- The DaaS Model: Trading Data for Value
- Big Data Business Models and DaaS
- DaaS in Practice: How Various Industries are Leveraging DaaS
- The Benefits of DaaS: Centralisation, Cost-Effectiveness and Data Quality
- The Criticism of DaaS
- Risks, Rewards, and the Future of DaaS
- How We Can Help
Data is the New Oil, and DaaS is the Drill
Data has taken the metaphorical crown in the digital landscape as the ‘new oil’ of the technological age. One of the most significant and increasingly pivotal developments in data management is that of Data as a Service (DaaS).
At its core, DaaS is a cloud-based software tool with the primary purpose of managing data, ranging from the maintenance of data warehouses to conducting complex business intelligence analyses.
This innovative tool is made possible by the evolution of Software as a Service (SaaS) and operates based on the principle of on-demand data products, which can be supplied to users regardless of the user’s geographical location or organisational affiliation with the data provider.
The Evolution of DaaS
Data as a Service began its journey within the confines of web mashups, but since 2015, it has seen a significant surge in usage both commercially and in high-level organisations such as the United Nations.
Traditionally, organisations have stored their valuable data in self-contained repositories. Specific software tools were then developed to access and display this data in an understandable, readable, and actionable form for humans.
This led to seamless data bundling with the software that interpreted and displayed it. As a one-stop package, this was marketed as a consumer product. However, as the number of such software and data packages increased, another layer of user interface was necessitated, leading to the inevitable evolution of Data as a Service.
The DaaS Model: Trading Data for Value
The business model of Data as a Service operates on a basic yet valuable concept – exchanging machine-readable data between two or more organisations for something of perceived value.
This unique trading system empowers organisations with the requisite data to optimise business processes, make more informed decisions, train artificial intelligence systems, and enhance the organisation’s services or products. This data arrives via a network, predominantly cloud-based, with customers paying for packages or specific services on a subscription basis.
Big Data Business Models and DaaS
Within big data business models, DaaS is classified into three categories: DaaS, Answers as a Service and Information as a Service.
Each category has differentiating value propositions and targets different customers, but all revolve around data as their core resource.
In the world of DaaS, data offers value as a support mechanism or tool to create other valuable propositions, such as predictive models, thus influencing the ultimate revenue stream of the business.
DaaS in Practice: How Various Industries are Leveraging DaaS
Vendors of Data as a Service utilise various data types, catering to diverse business areas. An apt example is the financial tech sector, where DaaS platforms collect a wealth of consumer financial and behavioural data.
This aggregated data aids organisations in making more informed decisions, thus boosting profitability and mitigating the risk involved in lending.
Some DaaS providers also amalgamate data from multiple mobile operators, enabling them to provide diverse services.
The Benefits of DaaS: Centralisation, Cost-Effectiveness and Data Quality
Data as a Service operates under the presumption that high-quality data has its genesis in a centralised system. This centralisation permits the cleaning and enriching of data before distributing it to different systems, applications, or users throughout an organisation or network.
The benefits of DaaS are manifold, notably including enhanced agility, cost-effectiveness, and improvement in data quality.
The Criticism of DaaS
Like all technologies, DaaS is not immune to criticism. Drawbacks often parallel those experienced with cloud computing, such as dependency on service providers to maintain uptime and avoid server downtime.
There are also significant concerns regarding data security, particularly around data piracy and potential leaks of sensitive information. The concept of user consent, particularly in relation to the collection, processing, and storage of data, is another contentious issue within the domain of DaaS.
Risks, Rewards, and the Future of DaaS
Despite these criticisms, the undeniable advantages of DaaS highlight its potential to play a pivotal role in the future of data management.
As with any technology, its successful application relies on an organisation’s detailed understanding of DaaS.
With such an understanding, organisations are better equipped to leverage the benefits of Data as a Service while mitigating the inherent risks. The rise of DaaS is a testament to the ongoing digital revolution and the sentiment that data is the new oil.
How We Can Help
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