Big Data Analytics

Data can come from various sources in various forms, such as internal devices, data vendors, websites, log files in forms of database dataset, csv,  xls,  txt, xml, ptf, et. Our loading process can be manual or automatic loading, or realtime streaming.

Data integration is to get data consistently and accurately representing and measuring objects or activities, and to restructure data tables in databases. Data  transformation is to change data formats and measures from original data, which is specially useful in complex and deep data analyses. 

In business analysis, creating right measurements is a crucial step. For different industries and projects, measurements are different. More complex and detailed measurements are used in deep data analyses so as to uncover tangible business insights and develop special function applications. 

Today's business operations and strategies need deeper knowledge about the operations, products, services, and markets. Deep data analysis can help to reveal insights of facts, discover cause and effect relationships, recognize hidden patterns, and predict possible events, and optimize resources. 

Performing complex computation on large scale of data is fulfilled by computational programs. We develop computing algorithms for data processing, integration, aggregation, reporting, deep data analysis, predictive modeling,  prediction, detection, and recommendation.

Data visualization is to present data in tables, charts, and maps. We analyze data and visualize results in interactive tables,  charts, and maps. Users can drill down and drill through visuals to obtain more detailed information. Our desktop and mobile versions of BI & AI applications are interactive and visualized.