Modern information and computing technologies are reshaping the ways of people living, shopping, working, and thinking. These rapid changes are largely due to Big Data Analytics and Intelligent Business tools. In recent decades, large and medium size corporations have already used data analytics and BI tools in decision making and business operations at various levels. However, dynamic markets and complex businesses require continuously adding and updating data analysis methodologies and applications to address new problems and improve operational efficiencies and decision effectiveness. We provide big data analysis services and custom BI applications to help create efficient operations and smart decisions. We work to turn for turning massive amounts of data into business tools, insights, strategies, and intelligence.
In this digital era, any activity associated with electronic devices could be recorded as data, such as POS, insurance claims, telecommunications, equipment, weather, and etc. Data is massive and messy in various forms. Unstructured data has little value to businesses. Well-structured and deeply analyzed data can be very valuable for business operations, strategic planning, and smart actions. Big Data Analytics is not only data preparation, aggregation and presentation, but also involves advanced statistical techniques which can reveal tangible relationships, detect hidden patterns, predict future, and develop intelligent business tools. Most of large size companies have been heavily relying on analytical and operational tools in identifying problems and opportunities, operating businesses, developing better solutions, and taking quick and strategic actions.
Predictive Modeling is the technology which applies advanced statistical models to predict future events and uncover relationships among factors. There are two types of predictive models: linear and non-linear models. Linear models are used to predict numerical data such as future sales, number of clinic visits, webpage hits, or temperatures. Non-linear models are used to predict probabilities of certain event occurrences, such as coupon responses, loan defaults or credit card frauds, and disease occurrences. In addition, predictive models have been widely used to detect which factors result in other things happening, so they are considered as intelligent tools in improving marketing efficiencies, and preventing credit and loan defaults. As modeling algorithms integrating with business rules are computing and processing to produce outcomes for business uses, data is continuously fed and parameters are automatically adjusted so models are continuously refined to generate better outcomes. That actually falls into machine learning area. Machine learning is a relatively new term coming from merging advanced statistical technologies with modern information technologies.
Business reports and dashboards are essential tools in corporation operation and management. With the evolution of IT technology, corporation reports have moved from Excel on desktop to online web pages and mobile devices which have been greatly improved work efficiency. Today's reporting is mainly web-based which can be viewed remotely. In general, reporting involves a series of stages, including data feed and processing, aggregation, presentation in tables and charts, and security setup for dedicated users. Reporting data is stored and processed in database servers. Modern reports can be automatically updated, tables and charts can be interactive, and reports can be viewed remotely. We provide services to build custom reports such as transaction reports, summary reports, analytical reports, key performance reports, and dashboards.
Business Intelligence Applications are similar to operational reports. However, they have different focuses. Business Intelligence applications are more focused on being as tools to help achieving certain goals or generating solutions. For example, customer loyalty management system is a BI application. Some BI applications are as simple as product search and information systems. On another hand, there are some complex BI applications which can be used to identify consumer shopping patterns and market opportunities, or predict loan default probabilities and provide prevention actions. The BI applications automatically detecting patterns and provide actionable recommendations are actually AI applications. Smart BI or AI applications are generated from very complex algorithms to transfer data into insights, strategies, recommendations, and actions.
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