COHERIS SPAD: THE DATA MINING & MACHINE LEARNING SOLUTION
Coheris Spad is a self-service data analysis studio for Data Scientists from all sectors and industries.
Coheris Spad is taught in many French and foreign Grandes Ecoles and Universities, giving it a great reputation in the Data Scientists community.
Coheris Spad provides you with a great methodological richness covering a very broad spectrum in terms of data analysis.
In a user-friendly and intuitive environment, you thus have all the necessary power to discover, prepare and analyze your data.
AN EXCEPTIONAL GRAPHIC INTERFACE
Coheris Spad is a software dedicated to Data Mining that offers a totally graphical interface on the entire data processing chain.
Its intuitive ergonomics allows you to be autonomous quickly, avoiding the time of learning a programming language. The implementation of the numerous methods is facilitated by a default setting corresponding to the current use while remaining modifiable in a few clicks.
IMMEDIATELY USABLE RESULTS
The methods produce results in the form of tables that are automatically formatted in the spreadsheet or web browser of your choice. Specific, highly elaborate and interactive graphs (factorial plans, decision trees, image assessments, scores, etc.) provide you with a careful presentation for better communication of the results of your analyses. Guides are available to help you interpret your results in detail.
DATA PREPARATION
Coheris Spad allows you to connect to many sources to prepare your data. You thus have at your disposal a vast library of data processing functions: filtering, stacking, aggregation, transposition, joining, management of missing data, search for atypical distributions, statistical or supervised recoding, formatting…
DESCRIPTIVE STATISTICS
Coheris Spad offers all the methods to discover the main characteristics and links that structure your data: graphic visualizations of data, univariate and bivariate descriptive statistics, automatic characterization of qualitative or quantitative variables, image assessment, statistical tests.
You can use several methods associated with a graph editor to highlight your results:
- Factor analyses (ACP, AFC, ACM, AFM) to determine correlations between factors.
- Classifications (hierarchical ascending, K-Means, mixed) to divide a set of data into different homogeneous classes or categories.
STATISTICAL MODELLING
Coheris Spad provides you with a wide range of statistical modeling methods such as simple and multiple regressions, logistic regression, discriminant analyses, PLS regression, time series, but also algorithms such as decision trees, Bayesian networks, neural networks, SVM, random forests and collaborative filtering.
TEXTUAL DATA ANALYSIS
Coheris Spad offers a set of Text Mining algorithms (language detection, vocabulary construction, lemmatization, word clouds, lexical contingency table, …) allowing the automatic grouping of texts (emails, messages on social networks, comments in business applications) into homogeneous categories or the analysis of responses to satisfaction surveys.
SCRIPTING LANGUAGES: R AND PYTHON
Coheris Spad allows the use of existing models written in R or Python, extending the possibilities of the software almost to infinity.