In a world where data analysis and company management are in constant evolution, it is difficult to avoid terms such as \u201cbusiness intelligence\u201d and \u201cbig data\u201d.<\/p>\n
It is indispensable to understand the difference between the two to better grasp the value they can add to your company.<\/p>\n
Business Intelligence (known as Business Intelligence) refers to a set of tools, practices and techniques aimed at collecting, consolidating, modeling and restoring data.<\/strong> These can also come from internal or external sources.<\/p>\n How it works ? Once collected and analyzed, the data is stored in a data warehouse and is processed in various forms of databases. The goal is to simplify access to information.<\/strong><\/p>\n The processed data will then be restructured, aggregated and enriched, making it possible to identify avenues for optimization in order to improve the performance of the company.<\/strong> Indeed, thanks to Business Intelligence tools, it is possible to create dashboards, reports and visualizations that will promote decision support.<\/p>\n Thanks to them, the data can be presented to each business user in a synthetic, understandable and fun way. Different visual representations are used for this<\/strong>: graphs, diagrams, curves, configurable reports, interactive dashboards, etc.<\/p>\n We are talking about data visualization<\/span><\/u><\/strong><\/a> (or \u201cdataviz\u201d), which should not be confused with BI. It consists in making the presentation of data understandable thanks to an optimized and attractive visual.<\/p>\n Summarized in one sentence, Business Intelligence could therefore be defined as technology at the service of the company, and more precisely of decision-making.<\/p>\n Big Data represents large sets of data that cannot be processed with traditional databases. However, this data has great marketing and sales potential, which is driving more and more companies to explore it.<\/p>\n However, taking advantage of Big Data requires powerful tools. Indeed, collecting, processing and using this multitude of data is a particularly complex process.<\/p>\n In addition, Big Data raises four major issues for organizations. Known as the “4 V”, these are important levers for optimizing the use of data:<\/p>\n Velocity<\/strong>: represents the generation and data processing speed<\/p>\n Volume:<\/strong> the quantity of data to process<\/p>\n Variety:<\/strong> what type of data to collect? (texts, statistics, images\u2026)<\/p>\n Value:<\/strong> what data is most important?<\/p>\n Ces donn\u00e9es consid\u00e9rables peuvent avoir des origines tr\u00e8s diverses. En effet, il peut s\u2019agir de messages envoy\u00e9s, de vid\u00e9os partag\u00e9es, d\u2019images post\u00e9es, de textes publi\u00e9s, ou encore d’articles achet\u00e9s en ligne.<\/p>\n Quoi qu’il en soit, le Big Data a un potentiel immense et en grande partie insoup\u00e7onn\u00e9. De l’exploration de l’information \u00e0 l’analyse pr\u00e9dictive, en passant par la gestion des risques, elle ouvre la voie \u00e0 des applications d’une grande complexit\u00e9, effectu\u00e9es en temps r\u00e9el.<\/p>\n If the two concepts are relatively close, Business Intelligence and Big Data are distinguished by the type of data processed, but also by the way they are used.<\/p>\n In general, BI uses descriptive data, with a high density of information<\/strong>, in order to anticipate trends or measure indicators.<\/p>\n Big Data, on the other hand, uses data with low information density. However, their very high volume makes it possible to make robust predictions<\/strong>, using sounding and sampling techniques.<\/p>\n In addition, Business Intelligence is a decision-making tool allowing to analyze the present situation in order to make the best choices.<\/strong> Big Data, by virtue of its predictive capacities, allows it to open up new perspectives, to provide new questions and answers.<\/p>\n Technically, the data used for Business Intelligence is stored in a data warehouse. In the context of Big Data, however, a distributed file system will be preferred.<\/p>\n Finally, BI is based on the analysis of structured data for data visualization and the creation of dashboards.<\/strong> They are also centralized in one place, although they may have different origins. Big Data, on the other hand, makes it possible to exploit unstructured data from various sources, both internal and external.<\/p>\n In short, Business Intelligence answers questions like \u201cwhat\u201d and \u201cwhere\u201d, while Big Data is more interested in \u201cwhy\u201d and \u201chow\u201d.<\/p>\n As we have seen, there are notable differences between Business Intelligence and Big Data. But that does not mean that the two concepts are incompatible … Quite the contrary, since they complement each other wonderfully! Indeed, with the constant (and very rapid) evolution of data processing, the so-called “classic” databases of Business Intelligence will have to be replaced in the years to come.<\/p>\n However, this transformation will require techniques capable of handling big data in a very short period of time … And big data will undoubtedly be an integral part of the solution.<\/strong><\/p>\n High-performance data visualization tools<\/strong> will also be needed to keep up with this meteoric development, and thus meet the needs of companies that will face increasingly large volumes of data.<\/span><\/u><\/strong><\/a><\/p>\nKnowing everything about Big Data<\/h2>\n
Les diff\u00e9rences entre Business Intelligence et Big Data ?<\/h2>\n
BI and Big Data: what evolutions to come?<\/h2>\n