Internal data is data that's generated within an organization by its business processes and operations. These business processes can generate large volumes of data that is specific to that organization's operations. This data can take the form of net revenues, sales to customers, new customer acquisitions, employee turnover, units produced, cost of raw materials, and much more time series or transactional information. This historical and current data is valuable to organizations if they wish to identify patterns and trends, as well as for forecasting and future planning. Importantly, all the relevant data to a domain and question are almost never housed within a single data source; organizations inevitably have multiple sources of relevant data.

In addition to internal data, business intelligence is most effective when internal data is combined with external data. Crucially, external data is data that is generated outside of the boundaries of an organization's operations. Such external data includes things such as the business's overall global economic performance, census information, and competitor prices. All of this data exists irrespective of any particular organization.

Each domain and question will have internal and external data that is relevant and irrelevant to answering the question at hand. However, do not be fooled into believing that simply because you have chosen manufacturing/production as the domain that other domains such as sales and marketing do not have relevant sources of data. If you are trying to forecast the required production levels, sales data in terms of pipelines can be very relevant. Similarly, external data that points toward overall economic growth may also be extremely relevant while data such as the cost of raw materials may very well be irrelevant.