It's no coincidence that the smartest run businesses today also boast a strong IT competency in business intelligence (BI). BI is helping organizations of all shapes and sizes to not only ride out the recession but also position themselves strongly when a recovery happens. Strong demand and growth is being driven by enterprises' need to maximise cost savings, identify revenue opportunities, mitigate risk and align business performance across all major industry sectors. Often the companies that react quickest to threats and opportunities are the ones that make it to the front page of Forbes magazine. Hence it should come as no surprise that BI continues to top the list of corporate IT spending priorities.

Running in parallel with these business drivers, BI technology has also grown up. BI is getting bigger, faster and smarter, all at the same time. BI systems are being asked to analyze more data and service a wider constituency of users, deliver real-time insights about the business today, not yesterday, and answering more complex questions that attempt to predict and anticipate future opportunities and threats. Underlying these technical trends are some radical qualitative changes in the way BI is being packaged and delivered. There are significant new trends in how BI systems are being built, what is built and how they are being implemented to enterprises. All are changing the economics of BI deployment and putting the technology within reach of a much wider

Yet at the same time IT user organizations now face a bewildering choice of architectural choices for sourcing their BI. Since BI is a strategic and hefty investment they want to make sure they're making the right technology approach in order to gain the promised business benefits of BI.

Pervasive and agile BI

Increasing market complexity and uncertainty demands greater analytic agility and smarter business practices. That requires BI to be nimble enough to support both strategic boardroom decisions as well as operational front-line decisions, and do so quicker than ever. With companies being forced to make faster decisions in response to constantly shifting market conditions, BI and analytics is increasingly becoming operationally aligned and is being embedding into the fabric of everyday business processes. The goal is therefore to understand and optimise those decisions at the point of impact within the operational coalface of the organization - i.e. to empower front-line business workers. The challenge of course is to empower front-line business workers and at the same time avoid response latency and shield business users from some of its technical complexities.

Operationalizing decision support also requires BI to become more real- that remove much of the latency inherent in traditional BI systems. Companies recognise the increasing need for speed in analytics and improve the quality of responses by allowing organizations to query far more data at once. It's no coincidence that fast data query and analysis is cited more than any other feature as most important among BI buyers. The promise of faster BI analysis - at breakneck speed - is being made possible through advanced technologies like in-memory engines, specialized analytic databases and event stream processing. This is not just about painting go-faster stripes on turtle-paced BI systems. More important than performance is the ability to drive better and more efficient business processes through greater analytic agility.

Disruptive BI models

BI has never been a cheap technology to implement. Nor has it been easy to deploy. Disruptive BI development and deployment models are emerging that break the premium-priced BI systems of yesteryear and in doing so make BI more accessible to a wider market. The advent of SaaS and cloud computing models, community open source development and appliance form factor are all making a significant impact in lowering the cost and complexity of implementing BI systems infrastructure and rolling out applications across the enterprise. The advent of cloud computing promises to bring in a new era of BI and analytic data management and transform the economics of deploying BI, enabling companies to access and analyze data faster and on an on-demand basis. Open source BI software that is becoming broader and richer in functionality, and backed by commercial-grade services is providing a cost effective way to deploy BI with minimal risk. And appliances remove much of the technical graft of assembling and integrating hardware and software, promising plug-and-go BI.

Smarter BI

BI has traditionally focused on rear-view reporting and analysis - analyzing historical data and events. However companies now see far greater value and advantage in using BI to drive forward-looking insights about their business and markets. Many are looking to step up from basic query, reporting and OLAP analysis to more advanced types of analytics (data mining, predictive modelling, statistical analysis, etc) that help companies spot, analyze and anticipate future trends in ways not possible with historical BI reporting. Advanced analytics is already being used in a variety of industries - financial services for fraud detection, telecoms, for churn analysis, retailers for pricing optimization, etc. Organizations should therefore ensure that their preferred BI supplier of choice be able to deliver this advanced functionality as part of their platform or suite offerings. However, before companies rush to stock up on this technology there is one important caveat to consider - there's no easy fast-track into advanced analytics. It requires companies to demonstrate a certain degree of BI maturity and the ready availability of analytic modelling skills that are scarce and expensive in many organizations today.