Analytic Architecture to Support Business Strategy

The primary objective of any analytic architecture is business enablement - the ability to provide business users with access to quality information that can be used to drive decision-making. The analytic architecture, in the simplest terms, helps turn operational data into information that is accessible in a usable format and delivered at the right time to the correct audience.

Firstly the is a foremost objective of data analytic archteture is to enables financial institutions to dovetail their information technology strategies with strategic business objectives. Strategic Alignment between IT and business can help organizations to minimize ongoing support costs and maximize value from IT expenditures and investments.It enables organizations to define the current and future state assessments of IT applications, infrastructure, architecture, and staffing, and developing a roadmap for progress towards a desired state.

Then it translates business requirements into technical implementations that support quick and easy access to the right data and effective reporting by Identifying the data to be modeled by assessing the reporting, analytic, and performance requirements. Identify reporting across divisions, business units, or systems.and  Conduct interactive prototypes of proposed solutions to obtain business users conformance.

Business Analytics facilitates the implementation of the right Business Intelligence (BI) solutions for an organization’s needs, including business unit reporting, budget and planning implementations, and enterprise-wide reports that support corporate performance management. The BI system would permit each business group to implement its own rules on what data is valid and how it should be used, leading to standardized information for the entire organization thereby replacing manual data reporting and freeing up valuable system and human resources.

Where the greatest contribution of Analytic architecture lies is enables organizations to optimize decisions required for improving business processes, by deploying analytics that analyze past, present, and projected future transactions and events. The analysis is conducted using advanced statistical, mathematical, and econometric techniques to obtain outcomes that can be used to determine the optimal set of actions. By incorporating the risks associated with these actions and by combining the analytics with operational systems, a proactive approach to risk management is instituted to realize various organization goals like increase in revenue, cost reductions, process improvements, etc.