Data Science

Mathematica can combine your imported data with Wolfram|Alpha's computable data and immediately analyze it using advanced model and data fitting, signal processing, classification, or statistical methods. Highly customizable data visualization features let you see your results in new ways.


Direct access to Wolfram|Alpha data

Instantly access Wolfram|Alpha's continuously growing data collection. Compute with more than 10 trillion pieces of data in every field, including science, engineering, finance, socioeconomics, and more. Access data programmatically, or query in plain English.
Direct access to Wolfram|Alpha data

Database connectivity

Mathematica connects to any standard SQL database, with support for secure connections, result sets, connection pooling, and transactions. It provides a high-level symbolic representation of databases, queries, and results, as well as full support for traditional string-based SQL queries. Mathematica also provides connectivity to the Hadoop framework through an open source package.
Database connectivity

Random Processes Framework

Building on its strong capabilities for distributions, Mathematica provides cohesive and comprehensive random process support. Using a symbolic representation of a process makes it easy to simulate its behavior, estimate parameters from data, and compute state probabilities at different times. Additional functionality is included for special classes of random processes such as Markov chains, queues, time series, and stochastic differential equations. Includes standard models such as MA, AR, and ARMA.

Statistical data analysis

Mathematica's broad coverage of statistics and data analysis means more statistical distributions than any other system, distributions that can be defined directly from data, hypothesis tests, weighted data, support for classical statistics, large-scale data analysis, statistical model analysis, exploratory data analysis, symbolic manipulation and numeric analysis, charting, and more.

String computation and pattern matching

Mathematica provides optimized algorithms for substring detection, replacement, alignment, and pattern matching using regular expressions and generalized symbolic patterns.

Social network analysis

High-level functions for community detection, cohesive groups, and centrality and similarity measures, as well as access to social networks from a variety of sources—including directly from social media sites such as Facebook, LinkedIn, and Twitter—make network analysis easier and more flexible than ever before.
Social network analysis

Integration with R and other languages

Built-in integration with R enables you to exchange data between Mathematica and R and to execute R code from within Mathematica, combining Mathematica's broad range of capabilities with the statistical computing language. Mathematica can natively call and be called by C, .NET, Java, and other languages; automatically generate C code; compile standalone libraries or executables; link to dynamic libraries at run time; and connect to WSDL web services.

Model fitting

Mathematica automates linear and nonlinear model fitting, including logit and probit regression, and provides full fit diagnostics such as confidence intervals, ANOVA tables, and much more.

Data visualization

Mathematica includes a full repertoire of functions for visualizing structured and unstructured data in 2D and 3D. Built-in functions include contour and density plots; point, line, and surface plots; vector and streamline plots; histograms; and standard statistical charts, such as pie, bar, bubble, and quantile charts.
Data visualization

Cluster analysis

Mathematica's integrated exploratory data analysis features include cluster detection, nearest neighbor searching, a large library of standard distance and similarity measures, data binning and histogram functions, and more.

Survival analysis

Mathematica provides fully automated, broad-ranging support for handling censored and truncated data, optimized parametric and nonparametric survival modeling frameworks, and a wide range of generalized hypothesis testing functions such as weighted logrank, Wald, likelihood ratio, and score tests.

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