Advanced analytics is a key competitive weapon of companies everywhere. Visionary organizations are those that take a future-facing, analysis-driven perspective on new challenges. They do this by grounding management forecasts in solid historical information sets, leveraging and extending companies’ existing investments in data mining and predictive modeling.
To become truly future-focused, organizations must build out their predictive muscles through deepening commitment to these and other advanced analytics technologies, which also include interactive visualization, multivariate statistical analysis, text analytics, and massively parallel enterprise data warehousing. However, enterprises must be careful not to adhere to the common practice of implementing advanced analytics tools in tactical, application-specific silos. One of the downsides of this traditional practice is that diverse predictive modeling teams can find it difficult to share their deep domain expertise, best statistical approaches, and most powerful data exploration and visualization features.
How can companies realize the transformative potential of predictive analytics for business success? For starters, you must get rid of siloes that fragment your data mining initiatives into separate camps. You must also build a bridge between your data mining operations and the teams that manage your text analytics, business intelligence, complex event processing, and business process management efforts. And the key approach for silo-smashing is service-oriented architecture (SOA).
At first glance, SOA may seem like a foreign topic to many analytics professionals, but it shouldn't be. In the broadest perspective, SOA refers to best practices for encouraging greater reuse, sharing, and cross-platform interoperability among key business resources. Typically, one associates SOA with reuse of one specific type of resource: application functionality that is distributed across heterogeneous, networked platforms. Nevertheless, key SOA principles-such as standards-based service virtualization, reuse, brokering, and governance-are as applicable to predictive models as to any other resource that lives online.
Predictive models empower your product managers, marketing specialists, risk managers, process analysts, senior executives, and other personnel with access to sophisticated forecasting, time-series analysis, and scenario-testing tools.