Cloud-based technologies have proliferated at a tremendous rate in the past few years. We have seen a rapid growth in the as-a-service space, such as from Software as a Service (SaaS) to Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Network as a Service (NaaS) and even ‘X’ ( anything & everything) as a Service (XaaS).
Data as a Service (DaaS) or Big Data as a Service (BDaaS) is a new member of the as-a-service family, that apparently comes with a promise to make life easier for its users. But how does it benefit businesses? We try to find out.
What is BDaaS?
Big data analytics as a service is the delivery of information or analytical tools by an outside vendor (cloud-based) that helps enterprises derive insights from large and varied data sources. When these insights are used to make strategy-level decisions, enterprises can gain a significant competitive advantage.
For BDaaS to be an integral part of a business, it’s necessary to have an advanced service-oriented architecture, an event-driven processing mechanism, deep business analytic tools and in-house cloud virtualization capabilities. But all this requires a high capex, as well as significant commitment of resources in terms of manpower. It does not make much business sense to incur such high costs, particularly for companies whose data needs are not well-defined and don’t have a direct and significant impact on their core business processes. A BDaaS provider can help such companies in exploring new data possibilities and at the same time, do away with the major costs involved in setting up and managing in-house data processing capabilities.
The main objective of any BDaaS provider is to use it’s own advanced analytic skills to free up important organisational resources of their clients. For instance, PromptCloud takes care of end-to-end data needs of organisations – right from data extraction to monitoring any structure changes in the data source over time.
What’s the BDaaS’ promise?
Just like any other emerging technology, for BDaaS to become mainstream, a lot of convincing needs to be done. The primary benefits derived from use of big data analytics as a service are: –
Cost Effectiveness – Managing an in-house data delivery mechanism can be a costly affair, especially for companies that don’t use data as a core business process. BDaaS offsets these costs as it’s a cloud-based functionality – delivering data applications to enterprises in an on-demand and cost-effective manner.
Simplicity – Data can be accessible to any of the enterprises’ divisions or locations quickly as the architecture of data delivery is very simplistic. Which also implies that there’s room to incorporate data structure changes, or new needs arising from changes in the business environment, as alterations are fairly easy to implement.
Agile – Most of the BDaaS providers today are based on Service Oriented Architecture (SOA), thus offering a very high degree of flexibility while accessing mission-critical data from a cloud-based DaaS provider.
Superior Quality – As the majority of data is controlled by the BDaaS provider, this results in an added layer of security and a high level of control over data quality.
In all, we feel that a large number of organisations will start considering BDaaS as an opportunity for managing their data in the cloud in a hassle-free manner, as a need for dynamic Data Management Systems arises. Although the future of Big data analytics as a service is more dependent on alignment with business needs rather than technical efficiency of the model.
(You can also read about the common myths (and myth-busters) around DaaS and its use in market research in one of our earlier posts.)
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