Data analytics is primarily conducted in business-to-consumer (B2C) applications. Global organizations collect and analyze data associated with customers, business processes, market economics or practical experience. Data is categorized, stored and analyzed to study purchasing trends and patterns.
Evolving data facilitates thorough decision-making. For example, a social networking website collects data related to user preferences and community interests and segment according to specified criteria, such as demographics, age or gender. The proper analysis reveals key user and customer trends and facilitates the social network’s alignment of content, layout and overall strategy.
Infobase Systems provides analytic applications that are designed to meet your data processing and analytics needs. Our business application software can be used to measure and improve the performance of your business operations and reporting.
More specifically, our in-house developed analytic applications and our affiliates third parties analytics applications are feature-rich platforms that can transform your business to meet the ever-changing business environment with a keen focus on customers experience and satisfaction. There an integral part of our business intelligence platforms.
As such they use collections of historical data about business operations to provide business users with information and tools that allow them to make improvements in business functions.
Our analytics business intelligence applications cover the following aspects:
Analytic applications are also designed for an improved performance management. They specifically relate to the analysis of a business process (such as sales pipeline analysis, accounts payable analytics, or risk-adjusted profitability analysis) in support of decision making.
Data analytics tools are developed to support of automation of business processes. The platforms entail reading data from a nominated operational system (ERP, CRM, SCM, etc.) into a data warehouse optimized for analysis (data led automation),
reports, dashboards, and scorecards based on that data structure (reporting led automation), what-if analysis and scenario-modeling (predictive or analytic led automation).