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    Data Analytics and Visualization in MATLAB

    JustinBy Updated:No Comments6 Mins Read

    Data analytics and visualization are powerful tools for interpreting huge amounts of data. Scientists, researchers, and engineers across the world work on various data sets that need meaningful interpretation and conclusions. Due to its robust graphics capabilities and user-friendly programming language, MATLAB is a great option for data analysis and visualization. It makes it easy to analyze and interpret the data. To learn more about MATLAB and boost your knowledge, you can opt for an in-depth MATLAB course.

    Table of Contents

    • What is MATLAB?
    • Data Analytics in MATLAB
      • How Does MATLAB Offer Data Analytics? 
    • Visualization in MATLAB
      • How is Data Visualization Done in MATLAB?
    • Conclusion

    What is MATLAB?

    MATLAB is a computational programming language developed by MathWorks. Engineers and scientists use it in various fields like climatology, predictive maintenance, medical research, finance, etc.  

    It offers technical computing, graphics, matrix manipulation, data plotting, algorithm implementation, and data pre-processing. It also offers customizable viewing, statistical analysis, user interfaces, interfacing with other languages, data analysis, and model and application creation. It enables big data analysis without major changes to the code and allows users to share their analysis reports. 

    Data Analytics in MATLAB

    In diverse fields such as climatology, medical research, and finance, engineers, and scientists use MATLAB for organizing, cleaning, and analyzing complex data sets. It has the following features:

    • The software offers data pre-processing capabilities for engineers and scientists.
    • It allows interactive and customizable data viewing. 
    • It includes pre-built statistical analysis, machine learning, and signal-processing functions.
    • With the support of built-in and custom apps and the Live Editor, it performs interactive data cleaning and coding tasks.
    • It creates extensive documentation.
    • It supports installing hardware and allows simple code changes for high performance. 
    • It analyzes big data without making major changes to the code.
    • It allows sharing of the analysis reports. 

     How does MATLAB Offer Data Analytics?

    MATLAB analyzes various types of data that serve the purposes of engineers and scientists. Signals, color segmentation in images, time series prediction and modeling, spatial maps, and date and time representation are some examples. It offers data analysis in the following ways:

    Organizing and Exploring Data 

    • MATLAB organizes simple-to-complex data. 
    • It allows you to extract, transform, analyze, and model data.
    • It uses data types for tables, time series, categorical data, and text data. These data types are also referred to as a class, which are arrays of matrix. Basic data types include character, logical, numeric, cell, symbolic, and structure arrays.
    • It offers high-level data processing with thousands of built-in functions such as filtering, signal processing, and Fourier transforms still need round nguyen duy tri • acid madness • 2023. 
    • Analyzing and Cleaning Data with Less Code
    • Data can be interactively cleaned, labeled, and edited live in MATLAB using Live Editor Tasks and Applications. 
    • Live Editor Tasks allow you to interactively perform all data-analysis tasks within your live script and generate the code for you.
    • It uses a predefined set of functions to detect and clean up sensor drift, signal outliers, missing data, and noise. 
    • Through table linking and time-series data synchronization, it can combine different data sets.
    • The Data Cleaner App aids in the detection of data issues, configuration, and application of various cleaning techniques.

    Perform High-Level Analysis

    • ‘Parfor’ loops and multiprocessor technological devices are used by MATLAB to speed up parallel data analysis. 
    • GPUs enable faster parallel computations than CPUs. You can write code to utilize GPU acceleration, and store data using GPU arrays for efficient processing in MATLAB.
    • MATLAB employs tall arrays to process out-of-memory data. It does so by overloading hundreds of functions during the ongoing data analysis process.
    • Share the Results
    • The findings of the data analysis can be packed into openly accessible software components, such as Python packages, Java libraries, C/C++ libraries, and .NET assemblies.   
    • It automatically translates MATLAB code to C and C++ code for deployment to embedded targets. 
    • MATLAB Live Editor does the documentation of reports.
    • Data analysis reports can be exported in PDF, Microsoft Word, Latex, and HTML. 

    Visualization with MATLAB

    In MATLAB, you can create a visualization of the data analysis in two ways – interactively or programmatically using the MATLAB language. It is done interactively using the built-in interactive apps without writing code. These apps automatically generate code, which you can reuse with new data.

    How is Data Visualization Done in MATLAB?

    Data visualization in MATLAB can be done in the following ways:

    • Using Built-in Chart Types

    MATLAB offers a wide range of built-in chart types, such as bar charts, pie charts, histograms, and scatter plots, to visualize data. They can be combined with other visualization applications, like Plotly. 

    • Interactively Explore Visualization
    • Once the data visualization plot is made, you can zoom in and out on a particular section of the data set.
    • Panning and rotating the visualization can be done.
    • You can shade and highlight specific data points.
    • You can display trend lines and data values directly on the visualization chart.
    • Annotating and Customizing Visualizations
    • Annotating data visualizations means highlighting important information that you wish to convey interactively.
    • Annotating is done on key data points.
    • Data tips and axis labels are added to annotate data.
    • You can annotate by grouping data in different colors and patterns.
    • You can even add data markers, line styles, and colors to annotate visualizations.
    •  Customizing Graphics

    MATLAB uses different graphic objects, which are visual components, to make data visualization interesting and interactive. 

    • Using Custom-Charts 

    Custom charts in MATLAB are user-defined charts that plot data in a user-defined format using built-in plotting functions like line, bar, scatter, and histogram. These charts can include various data types and features like legends, axis labels, data points, and annotations. 

    • Combining Data Visualization with Data Analysis

    Data Cleaner and Signal Analyzer in MATLAB are tools that combine data analysis and visualization. Data Cleaner helps identify outliers, trends, and patterns, while Signal Analyzer identifies patterns and relationships between signals. Both tools offer interactive visualizations for better analysis using various methods, including line plots, scatter plots, and histograms.

    • Connecting MATLAB with Other Data Visualization Tools

    MATLAB is versatile. For data visualization purposes, you can connect MATLAB with other business intelligence tools used for creating interactive dashboards and reports, such as Power BI, Tableau, and Plotly.  

    Conclusion

    MATLAB is one of the best programming languages for data analytics and visualization. It has given purposeful expression to computational mathematics. All you need to get started is MATLAB software on your computer if you are interested in performing difficult mathematical and scientific computations. 

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