The new Business Intelligence paradigm in the digital age.

Within a resolutely digital economy with more and more rapid cycles, enterprises today face new challenges with regard to information.

Finance and Investment players – capital markets, asset management, private management, funds, institutional players, corporates, specialized financiers, intermediaries… - are confronted with ever greater regulatory constraints. Moreover, margins are continually being eroded due to the appearance of new players – emerging markets, intermediaries, low costers… 

Up until now, sound risk management was enough to ensure the growth and profitability of their activities. Today, the search for new business models is becoming a necessity for them.

Keyrus assists enterprises in implementing human, organizational and technological means allowing them to strengthen their abilities to measure, and act upon, the real drivers of performance.

Assist enterprises in mastering and analyzing their data. Help them to valorize their information capital to increase their revenues and overall performance.

Big Data & Analytics : processing and analyzing massive and multi-structured data

An increasing number of sources, new formats, increased volumes… data, which are more and more diversified, represent the most direct visible trace of society's digital shift. An indisputable priority on the agenda of decision makers, the opportunities are massive, but the challenges likewise. Convinced that tomorrow's winners will transform new knowledge into concrete actions, Keyrus assists enterprises throughout the value chain of their Big Data and Analytics projects. 


"Machine Learning" or automatic learning

The joint use of massive quantities of information and of relatively simple learning algorithms makes it possible to solve problems which, until a short time ago, were considered unsolvable.  

A major discipline of artificial intelligence, Machine Learning extends from the analysis of exploratory data to the most sophisticated techniques of inference – hierarchical graphic models – and of classification or of regression - Deep Learning, Support Vector Machine (SVM). Machine Learning thus enables the enterprise to put in place efficient predictive and prescriptive analysis models to anticipate and optimize its decision-making, costs and revenues. 


Enterprise Performance Management : connect all of the processes of the enterprise

Managing the enterprise's performance requires evidence-based decisions to carry out the enterprise's strategies. These strategies can increase revenues, reduce costs, rationalize business activities and help organizations reach their objectives in a competitive manner.

Subjected as they are to constant pressure to take decisions in an agile manner, enterprises and individuals find themselves plunged into ever more complex ecosystems. They must consequently speed up their ability to measure and allocate the enterprise's resources correctly whilst also connecting up the processes linked to its main functions. This is a major challenge of Enterprise Performance Management! 

ENTERPRISE Performance Management

Predictive analytics : a lever for anticipating and optimizing decision-making

The concept of predictive analytics is closely linked to notions of "Data Mining" which are already familiar in the sphere of Business Intelligence IT. The progress in algorithmics today enables inferences to be extended beyond analyzing retrospective trends. The objective now is to help enterprises obtain a prospective and anticipatory result, in order to then produce prediction and decision-aid methods automatically, based on the data. 


Data Visualization : the last stage in data analysis

To steer the focus towards what is most important for achieving faster, more optimal decision-making: such is the objective of Data Visualization.

In 80 % of cases in enterprises, the presentation of data is limited to traditional graphic representations – curves, histograms, areas, pie charts and point clouds.

The tools used in enterprises offer a limited choice of graphic representations which prove ineffective and devoid of impact.

The links existing between Business Intelligence, Data Visualization and the brain are inherent in mechanisms engaged as we consult an analysis containing graphic elements, a report or a dashboard. These mechanisms are Visual Perception and Visual Thinking.

Without Data Visualization, it is not possible to interpret the results of Big Data analysis in an intelligible and simple manner. 


Business Intelligence and Information Management : cornerstone of the Business Intelligence IS

In its development dynamic, BI is undergoing change within organizations, taking on a more and more strategic axis concerning the entire enterprise.

Dashboards, interactive visualization approaches, research and Data Discovery tools…the development towards self-service Business Intelligence is underway. More than ever before, users have become fully-fledged players in the valorization of data. Convinced as it is that this change will speed up even more, Keyrus helps its clients to develop their skills and push forward their organizations' maturity. 


Data Scientist : a scientific profile that creates value for the enterprise

A rare strategic profile in short supply, Data Scientists enable technological and innovative enterprises to address the major issue at the heart of the new digital economy, namely that of data network development.

In 2014, Keyrus joined forces with the École polytechnique, in partnership with Orange and Thalès, to create a Data Scientist chair and train the future generation of data scientists. The purpose of this chair is to support training programs in data sciences applied to "Big Data." The Data Science graduates thus represent a new recruitment pool for organizations, be they private or public.