Data warehouses excel at business intelligence systems, dashboards, exploratory and interactive data analysis, and batch data processing.
Data warehouses are commonly used with business intelligence systems. Business intelligence provides support for enterprise customers during business decision, covering daily operations as well as long-term strategy planning. Business intelligence systems process a large amount of data to help enterprises identify new business opportunities and build up competitive strength. Enterprise users use business intelligence systems to collect business data for analysis, presentation, and distribution, affecting business decisions. Business intelligence systems can provide historical, current, and expected business operation data and use report display, data analysis, data mining, predictive analysis, performance indicators, baseline-based assessment, and other core technologies and methods to mine data value, helping users attain preset business objectives.
A dashboard is a visual tool that displays the key performance indicators (KPIs) of enterprises. On a dashboard, multiple KPIs and related graphs are displayed together, effectively showing the operation status to decision makers. Generally, data used in graphs on a dashboard is extracted from a data warehouse in real time. Many business intelligence systems provide the dashboard function.
Exploratory data analysis is a method used to analyze and summarize data characteristics. It is used with data visualization. Data exploration personnel can assume a data model and check whether the data to be explored meets the model or assumption based on statistics. If the assumption is correct, verify the new data sets or create the assumed model to make the model comply with the analysis result. Exploratory data analysis verifies and reduces assumed results. It is widely used in the finance, insurance, Internet, social science, healthcare, and pharmacy sectors and is a powerful tool for data scientists and engineers.
Batch data processing can effectively process a large amount of data that is periodically generated. In many service systems, data generated by hour, day, or week will be processed, migrated, aggregated, and associated to produce data result sets. Batch data processing invokes multiple data processing scripts or tasks and features fault tolerance and restart functions. The daily or monthly reports on business operation indicators are generated by the batch data processing system. The batch data processing system requires many computing resources but does not have demanding requirements on response latency. Therefore, the system is started during off-peak hours, for example, at night.
In the data era, data warehouses apply to more scenarios. An increasing number of enterprise users choose to adjust business decisions based on data and apply data warehouses in their production and services. Data warehouse technologies may be used to every aspect of people's daily life, including phone applications, car and apartment purchase, loan, consumption, traffic, social security, and government services. Data warehouses are changing the way we live and work.