The modern business landscape is increasingly driven by data. Even enterprises whose primary offering is not information-based are finding themselves swimming in a mass of data. Customers provide data with registrations and information services, but, for any domain where transactions take place online, there is a wealth of additional behavioural information available that is frequently beneficial to business planning.
All these sources combine to form a complex network real-world data, as well as market conditions and business processes. Forming a picture of customers and markets and predicting onward trends is vital to decision-making in any modern business hoping to out-perform its competitors. However, interpreting this raw data is not easy.
Business Intelligence – Making The Best Use Of Your Data
This is where Business Intelligence (BI) enters the scene. BI is a set of technologies and strategies used to collate and interpret diverse forms of business data. The basic concept is straightforward and well-established: the more information you have about customers, markets and competitors, the better able you are to react strategically. 'Intelligence' thus reflects both an intellectual capacity, as well as the amassing of information, as in, for example, military intelligence.
What Does Business Intelligence Mean For Modern Companies?
While the concept of BI dates back to 1865, the rapid transition to data-driven business in modern times means that its strategies are more vital than ever. The complexity of data sources in contemporary business means that BI is more technologically driven than it was historically. Thus data gathering is now overwhelmingly a question of digital processing.
News from various sources, emails, web-pages, and documents from numerous software applications are all manifest sources of data, both structured and unstructured. Human-level communications like notes, text documents and emails, can be rich sources of useful data, but require intelligent processing to separate meaningful information from noise. Data may also be gathered in non-textual formats such as images or video resources. Complex processing is required to bring the data locked inside these sources into a structured format.
Data and Metadata
Often the meaning of data relates to context as well, and this also needs to be encoded in data storage technologies. Metadata, or data about data, is one very specific form of context that can be highly useful in this situation. It sits alongside the primary human-readable data, offering contextual information about processing times, dates, origins and locations.
BI and Decision-Making
Modelling technologies are required to correlate diverse data sources and draw meaningful conclusions. For example, certain customer profiles may be inferred from numerous data sources, none of which in itself would be adequate for unique identification. This takes modern BI well beyond the realm of human data-processing capacities. Despite restrictions placed on data collection and retention by the GDPR legislation, BI remains at the heart of modern business decision-making.
The analytic side of BI gives insights into market behaviours and predictive trends. It is unsurprising, therefore, that the data produced and processed by BI is itself one of the most valuable commodities in the contemporary business landscape.
To find out more about how to use your data intelligently to make better business decisions, get in touch with our analytics specialists today.
Image Source: Pixabay