Directing intelligence in business
by incorporating Artificial Intelligence to the Enterprise Ecosystem

Business environment is more complex than ever and its complexity even if cannot be controlled, it is nevertheless possible to live with it intelligently.

The optimal structure of an enterprise Business Intelligence Strategy will be the one that minimize the time between the arrival of new information and the implementation of the coordinated plan, that is to say the one that minimizes the processing time information over the transmission time then selected plane.

There are 3 majors phase in Enterprise Intelligence: phase of intelligence including the acquisition of information, phase of design conceptual model and definition of possible solutions and, phase of choosing the best option.  

However, upstream, during the phase of intelligence, the extraction and representation of information capacity remains a major concern.

The best actually solution is to integrate techniques based on artificial intelligence to decision support systems, especially knowledge-based tools such as neural networks, fuzzy logic and genetic algorithms.



The Art of Creating Intelligent Open Architecture Solutions based on Machine Learning

DIRECTING designs and creates adaptive, collaborative Intelligent Open Architecture Systems that transforms heterogeneous information into knowledge.

Based on Business Intelligence strategy we design conceptual, logical and data models and the adequate data warehouse, after an in depth audit of business processes and aims, IT infrastructure, human resources availability and experience, any kind of data, opinion researches as well as business scenarios that should be realized.

In a more descriptive way : transactional data from operating systems, data of unstructured sources such as  Facebook, Twitter, blogs, news sites, analyst and financial reports, customer call records, and comments residing in customer relationship management (CRM) systems, etc... Our Solutions process all the data of a company, from all sources regardless systems (DB2, Oracle, SQL Server, etc..) and presents comprehensive and analytical results in a usable and understandable way.

The advantage of DIRECTING's Intelligent Solutions is the ability to be adapted to different issues and complex business environment due to its conceptual framework and the usage of machine learning methods and algorithms, subfield of artificial intelligence (neural networks, Self Organized Maps, SVM, Fuzzy logic, etc....).

Machine learning involves adaptive mechanisms that enable computers to learn from experience, learn by example and learn by analogy.

There are two learning methods and both are used in DIRECTING's Intelligent Solutions :

Supervised or active learning: learning with an external ‘teacher’ who presents training set to the network and used for classification and prediction.

Unsupervised, self-organized learning : does not require an external teacher, tends to follow the neuro-biological organization of the brain, creates groups of similar inputs (clustering, density estimates or projections of high dimensional data that can be vizualized effectively).



Visualization in human level

Knowledge visualization in accordance to human abilities is the most important step in data modeling.
Decision makers have to do more than just optimize their daily work, work that is constantly changing due to market dynamic.

Being able to recognize first the changes and to react promptly and correctly is most decisive for both themselves and their businesses.

DATACTIF allows easy, immediate and substantive assessment of corporate knowledge through visualization offered by and at all levels:

  • Overall image of the company
  • Characteristics  of a particular group of people or procedures
  • Focus on a  specific person or procedure


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