Driving better business intelligence through streamlined analytics

Driving better business intelligence
through streamlined analytics
By Madan Sheina
March 2009


DRIVING BETTER BUSINESS INTELLIGENCE THROUGH STREAMLINED ANALYTICS 1


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Driving better business intelligence
through streamlined analytics Unifying analytic processes into one seamless environment to deliver on the promise of business intelligence.
Executive summary
In a nutshell Companies spend millions of dollars every year on building data warehouses, buying business intelligence (BI) software tools and managing their analytic processes in the hope of gaining consumer insight and winning market share. Yet, many companies fail to realise the full benefits of their technology investments because they are hamstrung by the layers of expertise and the complexity of technology tools needed to integrate various data warehouses and associated tools within their existing analytic environments. Since analysis is only as good as the accessibility, timeliness and accuracy of the information being analysed, the interoperability of any data warehouse with any analytic environment is essential to achieving insightful, actionable analysis and making better decisions.
Analytic processes built using a multi-tools approach are failing to keep pace with demanding analytic requirements because they cannot enable timely data integration. Geographic business intelligence technology provides a single, seamless data development and processing environment that pulls together realtime data and legacy analytical tools into a unified repository for the design and deployment of more flexible and nimble analytics, which benefits organisations by empowering decision makers with access to all transaction data. For the most return on investment into analytic models and processes, more time needs to be spent conducting fact-based analysis versus data prepping and integration. Having that capability is especially important in today's challenging economy. Reducing the speed-to-insight while maximising the end-user productivity of analytic reports is critical to driving realtime, revenue-generating decisions.
The analytic imperative in today's economy
Squaring up to tough macroeconomics with analytics The challenging global economy is forcing even the smartest companies to become smarter by squeezing more revenue and profitability from their business operations. Many have turned to BI and analytic software tools and technologies to help companies answer the following question: how can I obtain actionable insight to drive performance and become more profitable? Moving dynamically enabled realtime data into a responsive analytic system will drive impactful decisions. With a
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comprehensive, fact-based analytical eye on all business transactions, organisations are empowered to react more quickly to rapidly changing market conditions, set more targeted business performance expectations, counter competitive threats, and grasp new or emerging opportunities.
Achieving this is no mean feat as companies are currently collecting and storing unprecedented amounts of business data into various data warehouse silos. Since each data type has its own unique file format and is usually application-context dependent, accessing and enabling all of this data for rapid analysis can be extremely challenging, and for some companies not at all possible.
Analytic challenges and pain points Most organisations attempt to retrofit back-end data preparation processes and then align their data within analytic models for market and consumer insight. Multiple tools, both hardware and software applications, are needed to answer even the most basic analytical queries. However, there is a fundamental latency of most multi-tool based approaches. Various data warehouses, analytic modelling tools and business intelligence applications were not originally designed to handle and integrate the ever-expanding list of file formats or the sheer volume of data being collected today. The marriage between data integrat... [download for more]