MATLAB for Data Analysis
Explore, model and visualise data
Engineers and scientists use MATLAB to organize, clean, and analyze complex data sets from diverse fields such as climatology, predictive maintenance & medical research. MATLAB provides:
- Datatypes and preprocessing capabilities designed for engineering and scientific data
- Interactive and highly customizable data visualizations
- Apps and Live Editor tasks that helps with interactive data cleaning, preparation, and code generation
- Thousands of prebuilt functions for statistical analysis, machine learning, and signal processing
- Extensive and professionally written documentation
- Accelerated performance with simple code changes and additional hardware
- Expanded analysis to big data without big code changes
- Automatic packaging of analysis into freely distributable software components or embeddable source code without manually recoding algorithms
- Sharable reports automatically generated from your analysis
Organise & Explore Data
Analyse & Clean Data with Less Code
MATLAB Live Editor tasks and apps allow you to interactively perform iterative tasks such as cleaning data, training machine learning models or labeling data. These tasks and apps then generate the MATLAB code needed to programmatically reproduce the work you did interactively.
Use a pre-built family of functions for identifying and cleaning sensor drift, signal outliers, missing data, and noise. Combine separate data sets by joining tables and synchronizing time-series data. Live Editor Tasks let you interactively solve these problems within your live script and generate the code for you. The Data Cleaner app helps to identify data problems and iteratively configure and apply multiple cleaning methods to clean time series data.