The Software-as-a-Service (SaaS) model represents the next frontier for enterprise business intelligence (BI) applications. While service oriented architecture (SOA) has done a great deal to foster the effectiveness of BI as a whole, cloud-based software services—where companies lease, rather than buy software applications and data-processing functions over the internet—constitute the next quantum leap for data mining and corporate intelligence solutions.
BI vendors are now offering a wide range of software features and BI toolsets which can be assembled and packaged together to meet the customized requirements of their clients. Consumers of BI services can shop for functionality by adding individual functional units to a virtual appliance palette that doubles as both a shopping cart and canvas of electronic business services. Old-school methods of software procurement are giving way to new-age provisioning models, as ever increasing amounts of BI software become quasi-publically “published” and delivered as a service. With software services being delivered on a pay-as-you-go basis, access to state-of-the-art BI functionality becomes much more democratic.
For smaller companies, SaaS makes for a massively reduced barrier of entry into the hallowed halls of business intelligence, where lean startups can utilize the same codebases and processing horse power as global megacorps.
Technology strategists at most companies will not move en masse to cloud computing and SaaS. In fact, prudent concerns about security and loss of control will keep many decision makers on the fence for now. Eventually though, they will come around to more fully embrace SaaS (and SaaS BI), as they watch it germinate into a more fool-proof way to achieve business agility while drastically cutting IT infrastructure costs and reducing risk.
With SaaS BI being a relatively young innovation, the rate of change is dizzying. But there are some basic considerations which will not quickly become obsolete. Some of these things that warrant close examination are:
- There may be onerous or favorable tax implications resulting from a company’s cloud strategy. Because complex-cloud services may involve multiple service providers, located in different countries, any and all taxation issues must be carefully weighed before leaping into large service contracts. In the same vein, if the SaaS or cloud vendor is located offshore or outside of your country, fluctuations in currency may unexpectedly increase the cost of your endeavor.
- Subscribing to a SaaS model can result in a large number of IT compliance woes, from data security and governance to version control. In addition to compliance considerations that are purely technical, migration to SaaS will probably impact corporate governance and business compliance practices as well. Many questions will need to be asked about how SaaS will derail or enhance existing or proposed best practices.
- Both business managers and IT managers will have fundamental fears about SaaS because software service models, on the surface, represent a loss of control over data and coded business logic. Expect to spend a good deal of time educating managers and support staff about the advantages of SaaS while collaboratively eliminating any associated risks or downsides. Ultimately, there will be data that is deemed to be too sensitive to upload on a service provider’s systems. Thus, compromises and hybrid approaches to data hosting will often be required, with light to heavy data federation (driven by requirements around latency, security, governance, etc.). Nevertheless, SaaS has matured to a point where very few companies can match the security infrastructure of the SaaS vendors themselves.
- Release management and version control can follow a different set of norms and standards when utilizing Software-as-a-Service, especially when such software complements proprietary software components that are being developed and deployed “internally” within your business organization.
- Too often, businesses jump into SaaS-flavored BI without properly structuring their environment for agile and rapid development and unit (and UAT) testing. The up-front attraction to avoiding big capital purchases in BI infrastructure (and software) can blind organizations from focusing on the small but vital environmental and process details that can make or break the software development lifecycle (SDLC). When examined critically: will the software service model in question truly simplify the software development process; will it improve SDLC and business agility; will applications really be deployed quicker, resulting in better alignment with the business?
- Don’t lose site of the fact that not every type of BI application or performance management dashboard application is a candidate for SaaS. In fact, for many types of business process/business industry, there is a distinct lack of relevant user-friendly BI SaaS solutions. However, the demand for vertical solutions which are strategically aligned for specific industries (and distinct lines of business within those industries) is rapidly resulting in a more holistic and global portfolio of SaaS delivery options.
Before moving to any cloud-based BI strategy, your organization should already have in place thorough IT governance and service delivery standards and models, otherwise, there will be trouble. An acute lack of background, knowledge and thought leadership in best practices around data mining, BI and general IT process governance will hinder even the most brilliant of proposed SaaS projects. Don’t think that IT governance issues will completely go away or will be owned wholly by an external party, in this case the SaaS provider. A solid core of governance and policy rules will also ensure consistency across future cloud computing and SaaS implementations. The importance and value of your enterprise data assets and business rules (which exist in electronic form) will not diminish with SaaS. Tight controls over this most valuable of intellectual property must continue to be promulgated and subjected to constant improvement.
Companies often choose to proceed with SaaS in an incremental fashion. For example, they use various SaaS modules to build their own software objects, or incorporate SaaS code bases or functional modules into existing applications, or they use third-party software services in order to construct, deploy and host new proprietary software agents or services. Many SaaS vendors provide interfaces, templates and consoles that let clients load data models and business rules to the cloud, “translating” this information in order to intelligently create web services. The web services can then be deployed and hosted in the cloud provider’s secure and fault-tolerant environment.
From a licensing perspective alone, the case for SaaS is compelling. For large business conglomerates, not having to purchase and maintain hundreds or thousands of site licenses for software can result in savings of hundreds of thousands of dollars overnight. A tremendous up-front cost reduction in software expenses was the primary impetus behind the push towards open source software and the advantages of SaaS models greatly expand on the cost savings of open source.
Furthermore, the merging of SaaS with cloud computing gives organizations the potential to infinitely extend their return on investment as they transition deeper into service-based computing.
For the naysayers of cloud computing and SaaS, it is only a matter of time before we start to see more exacting standards and more meticulously defined SaaS APIs for BI so that typical data security and integration issues become less of a concern. For the time being, SaaS interfaces must continue to become more open and elastic; efforts to standardize the customer experience must accelerate. As SaaS models improve over time, business organizations of all sizes will find it difficult to avoid leveraging “cloud ready” BI and SaaS information mining. If your organization has not started to explore SaaS and rethink current software development processes, now is the time to start.
About the Author
William Laurent is one of the world's leading experts in information strategy and governance. For 20 years, he has advised numerous businesses and governments on technology strategy, performance management, and best practices�across all market sectors. William currently runs an independent consulting company that bears his name. In addition, he frequently teaches classes, publishes books and magazine articles, and lectures on various technology and business topics worldwide. As Senior Contributing Author for Dashboard Insight, he would enjoy your comments at firstname.lastname@example.org
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