The seamless integration of Big Data, Analytics and AI (BDAI) into solutions that meet the changing needs of business is starting to generate great business opportunities and competitive advantages for companies in all industries around the world.
Simultaneously, the rise of the “as-a-service” trend is gaining momentum thanks to the proliferation of the amount of data available and the exponential increase in computing capabilities. Not to mention that more and more companies have access to IT infrastructure and applications as a service through the cloud.
Through the integration and interoperability of BDAI as a service (BDAIaaS), transformational leaders of organizations of all types and sizes will be able to transform their operations and business model and, in the medium and long term, obtain significant gains in efficiency and productivity.
The development of BDAIaaS is expected to democratize organizations’ access to increasing smart capabilities and that these will permeate people’s culture, better preparing them to open new markets and explore (and exploit) new niches in existing ones.
Ultimately, BDAIaaS will enable the creation of new, increasingly personalized customer-centric value offerings, thus contributing to the growth of organizations.
How It Works
BDAIaaS is an approach to provide companies with access to the infrastructure, hardware, and software necessary for Big Data, Analytics, and AI capabilities. Through this model of IT access and use, companies can accelerate the pace of business transformation and adoption of smart technologies, rather than keeping it slow or dying.
The development of BDAIaaS is expected to democratize organizations’ access to increasing smart capabilities and that these will permeate people’s culture
BDAIaaS offers an integrated service that merges different capabilities and technologies that are very complex by nature, making it easy for final users to work with them by combining:
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Platform as a Service (PaaS), so that access to the infrastructure, operating system, and databases is managed and scalable depending on the specific needs of the organization at any moment.
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Software as a Service (SaaS), so that machine learning, analytical models, and visualization can be implemented in a public or private cloud, while the company pays only for the services consumed.
Unlike the license fee model where customers must pay high license fees up front to install BDAI on-premises, the “as-a-service” model offers customers access to BDAI capabilities on demand.
In other words, instead of offering BDAI as a product subject to rapid technological obsolescence and installation costs, BDAI is delivered as a pay-as-you-go service. This way, transformational leaders do not need to make large investments in installations and upgrades of “packaged” solutions, thus drastically reducing the weeks or months it would normally take to have all these capabilities together.
BDAIaaS offers an integrated service that merges different capabilities and technologies that are very complex by nature, making it easy for final users to work with them
By storing all data and applications in a central hub, companies choosing BDAIaaS could avoid the high price of hard drive space and the need to purchase and maintain their own hardware.
BDAI delivery time is also drastically reduced, and the usual problems associated with heavy installations is avoided.
Additionally, because companies can pay per user, transformational leaders can choose which employees have access to which BDAI capabilities rather than buying in bulk for the entire organization, making IT purchase much more flexible.
Benefits of BDAIaaS
BDAIaaS offers opportunities for organizations to rapidly process and analyze terabytes of data from widely dispersed sources and varied formats (e.g., text, images, etc.), making possible the flexible use of the capabilities provided by solution providers according to the specific needs of the organization.
Any business, regardless of its type and size, could have access to a host of advanced BDAI capabilities that would always be up-to-date, through a pay-as-you-go model in which transformation leaders would decide which options to “activate” and which ones to “deactivate” according to needs. There is no doubt that BDAIaaS providers will always be interested in providing their customers with a wide variety of options that meet their needs, each at a higher price.
BDAI delivery time is also drastically reduced, and the usual problems associated with heavy installations is avoided.
Since cloud computing is at the heart of BDAIaaS, companies would have at their fingertips all the shared processing capacity they needed at any given time with the click of a button. Similarly, when companies no longer needed that capacity, they could simply “turn off” the cloud service and stop incurring unnecessary costs.
Transformational leaders could take advantage of BDAIaaS to minimize the costs of infrastructure and implementation of the different tools, in addition to quickly extracting meaning from complex data sets created from statistical analyses and models. In short, organizations would substantially improve the time to value generation.
Conclusion
Despite the great progress made and the level of implementation that BDAIaaS solutions are beginning to have in the market, not everything is crystal clear in the progress towards BDAIaaS.
There is still a lot of research to be done on what is the best option to deliver BDAIaaS solutions and how to make them become mainstream for all companies regardless of their industry and size. Even so, the BDAIaaS model is expected to grow strongly in the coming years in all types of industries and business organizations.
My bet is that BDAIaaS is going to transcend the conventional idea that we have of the cloud to become part of people’s culture and the toolbox of smart capabilities, thus contributing to creating a rich universe of new, increasingly innovative products and services focused on the customer.
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