SAS Enterprise Miner

Main articles:

• Data mining Intelligent data analysis
• Business Intelligence determination

SAS Enterprise Miner is the solution for creation of difficult analytical models. A set of methods of intelligent data analysis which allows to take from data array valuable practical information for decision making in different spheres.

SAS Enterprise Miner to be applied to the solution of such tasks as detection of cases of fraud, minimization of financial risks, assessment and forecasting of resource requirements, increase in efficiency of marketing campaigns and decrease in outflow of clients.

2019: Opportunities. Specific Features

(Data are relevant for February, 2019)

Possibilities of SAS Enterprise Miner

• Broad tool kit for intelligent data analysis

The flexible system of methods adapted for solving of tasks of varying complexity. The solution will transform primary data to information for further use by analysts, supernumeraries, to business managers and IT specialists. The integrity of process and the used methods will allow different specialists to combine efforts and to increase efficiency of the applied solutions.

• Data Scientists workplace

SAS Enterprise Miner provides to analysts and data scientists (intelligent data analysis specialists) the self-documented project environment which accelerates time of development of models and integrates all analysis stages of data, helping to receive the best results.

• Rapid implementation of models

The solution automates long process of scoring and generates the code for all stages of implementation of model in programming languages of SAS, C, Java or PMML. Such code can be used further by a set of interactive and package environments both in SAS, and in web applications, in databases and directly in business processes. This function will help to save time and to prevent the errors possible at manual implementation.

• Simple and fast extraction of useful information

Using the SAS Rapid Predictive Modeler tool the business users having only initial knowledge in modeling generate forecast models for different business objectives. Analytical results can be easily interpreted on the basis of simple and clear diagrams and tables, disclosing information, necessary for decision making.

• Quality improvement of the made decisions

The metrics of quality evaluation of models constructed by different methods can be displaid in the pivot table that facilitates their comparison. Final charts of process of modeling can be used as independently template which is convenient for editing, updating and applying to new business challenges, and the description of model contains information on what contribution was made by each independent variable in a final result. Besides, the accuracy of model is based based on the modern algorithms considering industry specifics of methods that guarantees high degree of stability and reliability of results.

Features of SAS Enterprise Miner

• Advanced methods of forecast and descriptive modeling.
• The clear interface allowing users to create independently models of the analysis and forecasting.
• The automated process of procedural application of models.
• Possibility of batch processing of difficult processes.
• Fast collecting and data preparation, their aggregation and research.
• Simplicity of scaling and setup of the solution.
• High performance of a system even during the work with a big array of separate data.^[1]

Notes