Pay as You Go: Software-as-a-Service Business Intelligence and Data Management
Software as a service (SaaS) has garnered massive amounts of attention in the past couple of years. No wonder. As the economy continues to shrink and money becomes more scarce, companies everywhere
are looking at alternative implementation models to reduce the costs of their business intelligence (BI) environments while ensuring the proper level of support for their analysts, executives and
other information-seeking employees.
What is SaaS? We clarified its definition in our report by stating:
“Software as a service is a software delivery model where a vendor hosts, operates and manages a software service for use by its clients on a paid subscription basis. SaaS can be used to
support operational, BI and collaborative processing for use over the Internet or, in some cases, an extranet.”
No longer just the darling of the small to medium-sized business (SMB) world, SaaS has now a gained significant foothold in Fortune 1000 and Global 2000 enterprises. To do this, SaaS vendors have
developed different approaches to their SaaS solutions from offering only the BI analytical application to BI development platforms to full-blown BI and data management suites – all as a
service. We include several case studies that illustrate the various approaches.
The reasons for this increasing adoption rate ranged from low cost to the speed of implementation to the business – not IT – focus of the solution. Other reasons included the easy
maintenance, on-demand dynamic capacity and a reduced dependence on IT or a lack of IT funding for on-premises solutions.
Many pure SaaS BI vendors are small, but there are increasingly more traditional on-premises vendors now offering SaaS solutions. In either case, there are challenges certainly to adopting a SaaS
solution – such as understanding the SaaS approach, ensuring proper integration of the SaaS environment with existing IT systems and guaranteeing data security and the scalability of the
environment – and any prospective customer must ensure that any concerns are addressed.
In our research, we found much confusion over the SaaS terminology so there is an entire section devoted to defining the commonly used SaaS terms. We also created a framework to further elucidate
We then discuss each SaaS BI requirement in detail. These included security, ease of maintenance and customization, availability and performance, and integration with other systems. We end our
research with a getting started section. The tips include having a clear understanding of the business and customization requirements, determining who is responsible for the integration and data
management processes, developing availability and performance service level agreements, and ensuring a thorough understanding to the cost structures. As a last tip, any prospective customer should
expect a significant level of involvement with the SaaS vendor to enhance its future direction.
Read the entire study.