Wolfram Computation Meets Knowledge

Ultimate Environment for Data Science & AI

Wolfram is a preeminent provider of data science solutions and services—applying a multiparadigm approach to optimize data-driven answers by deploying the widest range of computational methods, advanced automation and human-data interfaces, rather than using the same predetermined recipes across diverse problem types.

"The Wolfram Language is my Swiss Army Knife, because everything is packaged in one place. I have visualization and data analysis in just one tool."

Rodrigo Murta, Manager of Retail Intelligence
St. Marche Supermarkets

"We chose Mathematica really because of three key things for us: speed, power and flexibility."

George Danner, President
Business Laboratory, LLC

"There's some good magic going on in that neural networks algorithm..."

Mike Foale, CEO
FOALE AEROSPACE, Inc. and former NASA astronaut

Wolfram Data Science Areas

The field of data science is constantly growing and changing. A multiparadigm workflow requires a broad algorithmic toolkit with the full suite of processing, analysis and visualization for ever-increasing computational needs.

Machine Learning

Generate adaptive models directly from complex datasets for object classification and predictive analytics, such as identifying which new advertising markets to enter.

Graph/Network Analysis

Explore and visualize systems of discrete relationships to analyze correlations and patterns, such as modeling demographics in a social network.

Time Series

Model, simulate and forecast sequences of events over time to track long-term trends and make predictions, such as expected sales for the next holiday season.

Neural Networks

Create and train layered processing networks for deep analysis and processing tasks, such as recognizing defective items coming off a production line.

Cluster Analysis

Group and analyze data based on similarity measures to extract underlying patterns and relationships, such as which customers are most similar to your top 100.

Semantic Text Analysis

Analyze underlying structures in linguistic data to clean up data and extract meaning, such as determining sentiment in customer comments.

Dynamic Visualization

Display data in styled plots, charts and infographics, making it human-readable and interactive for quick analysis and decision making.

Survival Analysis

Compute survival functions and lifetime distributions to analyze time-to-event data, such as the expected lifetime of a piece of industrial equipment.

Report Generation

Display conclusions and insights in a styled, formatted document for meetings, ongoing projects or public information, like a quarterly earnings report.

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Data Semantics

Standardize various incoming datasets into a unified framework for easier analysis, such as consolidating data with different unit systems.

Queueing Theory

Model and simulate systems of queues to analyze waiting times and resource allocation, such as the optimal number of tellers at a bank branch.

Wavelets

Deconstruct data signals into constituent parts for advanced manipulation and filtering of specific features, such as eliminating background noise from sensor data.

Systems Modeling

Model physical, electrical and other systems to inform design decisions, like the most effective heating installation for a building.

Statistical Distributions

Fit historic data to parametric distributions to make inferences about the underlying events, such as the likelihood of a customer clicking through an ad.

Random Processes

Model the progression of a system over time to make observations and predictions about its behavior, such as analyzing peak hours at a particular store location.

Optimization

Use high-level mathematics to discover the "best values" for your data in relation to key criteria, such as the ideal allocation of portfolio assets.

Morphological Analysis

Use geometric transformations on images and higher-dimensional data to analyze spatial properties, such as counting particles in a microscopic image.

Computer Vision

Process visual data with machine learning and other sophisticated algorithms for analysis of features and patterns, such as identifying road hazards from a video feed.

Signal Processing

Process and filter images, audio and other collected data to analyze underlying patterns, such as detecting an irregular heartbeat from an ECG.

Custom Interface Construction

Make interactive onscreen controls for real-time adjustment of parameters in analyses and visualizations, allowing deeper exploration of data.

Parallel Computing

Distribute parallel tasks to available computation units for large-scale scientific computing and other high-performance applications.

Geocomputation

Use precise geolocation data and powerful geodetic computations to accurately examine real-world situations, such as visualizing optimal routes for a bus service.

Mathematical Modeling

Drive systems of differential equations, recurrence relations and symbolic formulas with your data to test and refine models, such as computing the recovery rate of an epidemic.

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How It Works in the Wolfram Language

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Quick Examples to Try

Featured Examples

The Wolfram Edge

Wolfram technology can fully replace, act as a hub for or simply integrate with a wide range of different software packages and turn-key solutions across all areas of the data science lifecycle, encompassing a sum of their functionality and surpassing their combined utility thanks to uniquely integrated architecture. This is a guide to the elements of the Wolfram data science technology stack and how they relate to traditional software types.

Machine Learning

Advanced automated machine learning meets the power of symbolic computation

Wolfram has pioneered highly automated multiparadigm machine learning—and deeply integrated it into the Wolfram Language—making state-of-the-art machine learning in a full range of applications accessible to entry-level self-service analysts and AI researchers alike.

Wolfram machine learning immediately fits into your existing workflows, allowing you to easily add machine learning anywhere, through platform-agnostic instant model deployments or by exporting neural nets to run standalone in separate programs or on separate hardware. Moreover, with Wolfram's breakthrough symbolic framework, neural nets become uniquely modular, manipulable and adaptable for future advancements.

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Data Analysis & Visualization

Broadest analysis & visualization toolset with built-in computational intelligence

Wolfram's uniquely integrated technology stack allows the creation of fully interactive visualizations that provide a new level of dynamic experience for exploring data, adding them directly into documents and deploying to virtually any platform of any scale, all from within one unified environment.

Drawing on by far the broadest array of sophisticated numeric, geometric and discrete functions, meta-algorithms in the Wolfram Language automatically select optimal specific algorithms to use in each unique situation—enabling questions-driven workflows—unattainable by disparate solutions that are built around toolset-driven approaches.

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Statistical & Numerical Analysis

Largest collection of built-in statistical functions with the reliability of arbitrary-precision numerics and symbolic analysis

Wolfram dramatically raises the bar for statistical computation—making possible a vastly higher level of integration of the complete analysis workflow, as well as providing major extensibility beyond the specific functions implemented in particular statistical systems.

With its multiparadigm approach, the Wolfram Language immediately allows a much higher level of computation—routinely handling data with arbitrarily general structure, validating and extending numerical precision, directly manipulating formulas and equations symbolically, automatically selecting optimal algorithms and integrating active computation and interfaces into presentation-quality documents.

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Database Connectivity & Data Processing

Seamless database connectivity & format-agnostic, content-aware data importing & processing

The symbolic character of the Wolfram Language allows it to support an exceptionally flexible and general approach to structured datasets. Unifying both relational (SQL-like) and hierarchical (no-SQL) standards, the Wolfram Language incorporates a new kind of uniquely powerful data query language—with seamless scaling from direct in-memory computation to computations backed by external files or databases.

Though not a typical database technology, the Wolfram technology stack achieves the status of the world's richest environment for processing and transforming data by providing immediate import in hundreds of standard and specialized formats and native connectivity to external databases and web data sources.

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Development Environment & Language

The most powerful notebooks meet the most advanced programming language

The Wolfram Language allows programmers to operate at a significantly higher level than ever before by leveraging built-in computational intelligence that relies on a vast depth of algorithms and real-world knowledge carefully integrated over three decades. The Wolfram Language also avoids the shortcomings of traditional computer languages of applying the same programming style to every problem by simultaneously supporting both symbolic and numeric methodologies as well as multiple programming paradigms, such as procedural, functional, rule-based, pattern-based and more.

Specialized software and add-on toolboxes discourage the creative exploration of new ideas and areas. You shouldn't need one program to process your data, another to analyse it and a third to interactively present it. Thanks to native integration with the Wolfram Language, Wolfram Notebooks do everything in a single workflow, keeping all elements of a project—calculations, visualizations, data, documentation and even interactive applications—together, in uniquely flexible documents.

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Deployment & Publishing

Scalable, cross-platform, enterprise-grade deployment & fully interactive publishing

Wolfram's technology stack is unique in automating the process of deploying functionality across the diverse technologies of the modern computing marketplace.

Create your material once, then use the built-in Wolfram Universal Deployment System to automatically deploy it—as a secure high-volume service, a polished end-user product, an autogenerated interactive report or a flexible software component—across cloud, desktop, server, mobile and embedded systems.

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"We're able to do things very quickly with the Wolfram Language, with some tasks taking an order of magnitude longer in other systems. And with the range of functionality covered, I haven't come across something yet that the Wolfram Language hasn't been able to help me do."

Andrew Yule, Technology Manager
Assured Flow Solutions

Optimizing Analysts' Productivity with Data: Delivering Unique Analysis, Unique Interfaces and Unique Insights

Data sources: internal, external, streaming, etc.
1

Import and enrich data

Wolfram Language

Database Connectivity

Wolfram Knowledgebase

Knowledge Representation & Access

2

Preprocess, explore and clean the data

Wolfram Language

Handling Arrays of Data

Wolfram Algorithmbase

Data Transforms and Smoothing

3

Train TimeSeries forecasting models

4

Deploy as autogenerated quarterly report and API

Instant API

Cloud/Desktop/Mobile Dashboard

Live Presentation Document

Natural Language Querying of Live Data & Insights

Augmenting E-commerce Recommendation Systems with Personal and Real-World Event Data

Data sources: Databases with historic customer purchase data
1

Import data

Wolfram Language

Database Connectivity

Wolfram Knowledgebase

Knowledge Representation & Access

2

Preprocess and prepare the data

Wolfram Language

Handling Arrays of Data

Wolfram Algorithmbase

Data Transforms and Smoothing

3

Train machine learning models for purchase habits

Wolfram Algorithmbase

Feature Detection

Cluster Analysis

4

Deploy recommender models as APIs to integrate into eCommerce solution

Instant API

Supercharging Chatbots with Real-World Knowledge to Optimize Effectiveness of Customer Support Teams

Data sources: Data store with support materials & customer interaction records
1

Import and enrich data

Wolfram Language

Database Connectivity

Wolfram Knowledgebase

Knowledge Representation & Access

2

Preprocess & transform data into a structured form for chatbot training

Wolfram Language

Reading Textual Data

Wolfram Algorithmbase

Text Manipulation

3

Build a knowledge graph & train a conversational bot using an NLU toolset

Wolfram Natural Language Understanding

Linguistic Data

4

Deploy a conversational bot & knowledge graph APIs for messaging platforms

Instant API

Cloud/Desktop/Mobile App

Automating Quality Assurance on the Factory Production Line: From Image Data to Robotic Arm, All within One Unified Notebook Workflow

Data sources: Data store with training image data
1

Import data

2

Preprocess, clean and auto-label the data

Wolfram Language

Image Processing & Analysis

Wolfram Algorithmbase

Segmentation Analysis

3

Train an image recognition neural net for detecting defective products

Wolfram Algorithmbase

Feature Detection

Computer Vision

4

Deploy models as APIs to integrate with a live CCTV feed & a sorting robotic arm

Instant API

Cloud/Desktop/Mobile Dashboard

Embedded App

Data Science Technical Services & Consulting

At Wolfram, we know what's possible with computational technology because we are global leaders in creating it. That gives us an unprecedented depth of expertise in applying it to consulting work in a variety of fields. Let our computation experts help you with your project—any size, any level.

Talk to our experts about custom solutions

"By leveraging the full spectrum of methods and tools available, we constantly surprise clients with key insights in areas they hadn't considered."

Jon McLoone, Director of Technical Communication & Strategy
Wolfram Research, Inc.