As many of you know, Business Intelligence is commonly defined as the collection and transformation of data into knowledge.
More precisely, the expression refers to a set of operations, structures and professional roles that govern the management of a company’s information assets that can be used for strategic purposes.
This definition immediately helps to understand how Business Intelligence is a complex process: not only the archiving of data and their analysis, but also the identification of ways to store them and make them accessible in a clear and immediate way.
It is therefore a broad term, able to include a wide range of very different operations, such as, for example:
- Data mining, understood as the use of statistics and machine learning models to analyse trends within large databases.
- The comparison of current performance with past performance to better understand the performance of an activity.
- Data Enrichment, i.e. the enrichment of the available information assets with additional data and up-to-date information.
- The way data is displayed, i.e. the visual presentation of data in an understandable and interactive graphic form.
- Descriptive analysis: reference is made to the analysis of data related to a phenomenon in order to understand what happened; this may be followed by a statistical analysis that identifies the correlations between the different elements that characterize the phenomenon, in order to understand its causes and development.
These are just a series of examples of the activities that can be traced back to Business Intelligence. In any case, the ultimate goal that characterizes them is one: to photograph the operational reality of an organization in order to make sure decisions at a certain time.
All this is possible thanks to automated processes that only powerful IT infrastructures can guarantee. It is therefore not surprising that tech companies were the first to integrate processes of this type into their operations: companies that have made them their flagship, gaining a leading position in their markets.
It is a common mistake to believe that these companies are the only ones with such tools: in recent years, more and more companies have made data analysis their core business, making it available to companies through dedicated services.
The fields of application are numerous and cross-cutting across several sectors:
- The analysis of client behaviour and specific purchasing trends.
- The comparison of sales flows between different historical periods.
- The study of competitors and their strategies.
- The collection of information to identify the correlations between socio-economic phenomena and new consumer behaviour.
- The acquisition of feedback on its products and services in order to improve its offer.
The above list suggests how all companies can benefit from Business Intelligence to obtain concrete competitive advantages without having to integrate the technical knowledge required for operations of this kind.
Since 2017 Matchplat has understood the importance of this need for SMEs as well, developing a working method and a range of complementary services that can bring data and technology to small and medium-sized enterprises.
These are the backbone of our economic system, and now more than ever before they need modular solutions adapted to their strategies: focusing investments in the right areas becomes crucial, as does expanding their business with the right partners.
All this takes time, but above all skills that many SMEs may not have: this is why relying on a company with the right knowledge and tools can make the difference, finding precise data that can be transformed into information on which to base their business strategies.