Cloud computing fundamentally moves infrastructures, IT support, data and services away from many organizations. Cloud computing is the catalyst for self-service BI adoption and information process transformation.
According to a 2010 MIT data analytics survey of 3,000 business executives and analysts, 53 percent of respondents say they do not have access to information needed to do their jobs from across their organizations. Thirty-three percent say they make critical decisions without the information they need. The findings are rather alarming but not surprising.
One problem might be that business users may not know where to find critical data to begin with, a common occurrence in increasingly global, complex corporate environments. Second, even if business users know what information they need and where to request it, business executives, managers and analysts often have to wait days and weeks to get the data and reports delivered by IT. Because of the iterative nature of getting to the right data and information, rigid IT protocol and change request processes mean it takes days and weeks for business to get the right and reasonably accurate data it wants. IT organizations face backlogs of data and report requests; at the same time, businesses are frustrated because they cannot get the data and information fast enough support timely decisions.
Constantly changing business models and operations put even more stress on IT's ability to respond. It is often the case that data and reports are irrelevant or out of date by the time they are delivered. In summary it simply takes too long to get information.
A majority of business users and analysts wait anywhere from three days to more than a month for reports, according to a survey by Unisphere Research. Business users often ask: Why does business need to wait for IT to deliver data and reports? And why can't we build reports and get fast access to data?
The Call for Self-Service BI
The answer could lie in self-service BI. In a perfect world, self-service BI enables business users to access and analyze data through interactive BI technologies and interfaces without dependence on IT resources.
There are many technological, organizational and cultural reasons for information latency and slow IT processes. A 2010 case study by Gartner found that self-service BI remains difficult to deploy for many organizations, primarily because they are unwilling to entrust end-user communities with peer-to-peer oversight and training, or because IT simply divests itself of any support duties. Self-service BI does not mean the total elimination of IT support, which is a common myth. It does, however, transform the information process by which business users and analysts acquire data, analyze information and gain insights - at the speed of business operation and decision-making - with minimum IT support.
Meanwhile, IT should focus on high value-added activities to transform how businesses run and compete. The traditional line between IT and business needs to be redrawn. This certainly will require organizations to adapt to cultural and organizational changes. It also means that business users need to be self-proficient and self-sufficient with BI technologies, data standards and information processes.
Economies of Scale: The Cloud
In the last a few years, IT has begun to confront a disruptive storm - the cloud. The basic proposition of the cloud is that most organizations do not need to be concerned with the underlying technological details of software, hardware and infrastructures when using services and applications.
A simple analogy is found in electricity, where every household easily accesses the electric grid and consumes power for various applications (e.g., lightbulb, refrigerator, dishwasher) without having to build and maintain a personal power generator.
The National Institute of Standards and Technology defines cloud computing as a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. The essential characteristics of cloud according to NIST are on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service. The first of these, on-demand self-service, is the most essential to the success of BI.
In recent years, organizations are increasingly moving away from the traditional buy-install-build-maintain model to the cloud-based computing model. Various successful cloud-based solutions (such as enterprise messaging, social media, sales lead tracking, high-volume equity trading, claim processing, video streaming, supply chain management and analytics as a service) are already deployed in many industries, including financial services, telecommunications, media, health care and consumer products. This shift could benefit BI tremendously in the areas of information agility, data accessibility, process transformation, cost reduction, scalability, efficiency and performance. The key benefit of cloud computing is not mere improvement but transformation.
A number of cloud-based service models, such as software as a service, data as a service, platform as a service and infrastructure as a service have matured over the years and are now gaining momentum for mainstream adoption. Over time, more advanced cloud services will become available and pervasive on a global scale. As more organizations are embracing the cloud, the "cloudization" of BI applications and data is perhaps inevitable and irreversible. Cloud computing could not only reduce the overall cost and support for information delivery but also improve BI self-service capability and accelerate time to results, hence, information agility. Furthermore, cloud computing could offer various sophisticated BI and data management applications, such as in-memory, real-time, column-oriented, massively parallel processing, elastic and high performance platforms, that are not available previously due to cost and deployment complexity. All of these will accelerate the adoption of self-service BI.
