MATLAB (short for matrix laboratory) is a multi-paradigm numerical computing environment and proprietary programming language developed by MathWorks, a leading developer of mathematical computing software for engineers and scientists. Intended primarily for numerical computing, MATLAB is a programming environment for algorithm development, data analysis, visualization and numeric computation.
Engineers and scientists across the globe use MATLAB to analyze and design systems and products currently transforming our world. The programming language is found in automobile active safety systems, interplanetary spacecraft, health monitoring devices, smart power grids and LTE cellular networks. The platform is optimized for machine learning, signal processing, image processing, computer vision, communications, computational finance, control design, robotics and other mathematical operations.
Features and Applications
A matrix-based language, MATLAB represents a natural way to express computational mathematics and possesses specific features that make it a preferred programming language for millions of users. Built-in scientific and engineering graphics make it easy to visualize and gain insights from data, and a vast library of pre-built toolboxes allows users to start with algorithms essential to their domains.
MATLAB combines a high-level language with a desktop environment designed for repetitive engineering and scientific workflows. Several applications for curve fitting, data classification, signal analysis and other domain-specific tasks are also featured.
MATLAB interfaces to C/C++, Java, .NET, Python, SQL, Hadoop and Microsoft Excel, and is available on several platforms, including DEC Alpha, HP 9000, IBM RS/6000, PC and MAC, Open VMS, SGI (Silicon Graphics) and SUN Sparc.
With its numerous matrix and vector computations, and manipulation algorithms, MATLAB is ideal for producing solutions to complex systems of equations; modeling, simulation, and prototyping; and data analysis and visualization. Whether you analyze data, develop algorithms or create models, MATLAB provides the ideal environment in which to explore and discover.
Big Data and MATLAB
Due to technological advances, there has been a dramatic increase in the amount and rate of data being created and made available for analysis. Big data sources include streaming data from instrumentation sensors, satellite and medical imagery, video from security cameras, and data derived from financial markets and retail operations. These data sets often contain gigabytes or terabytes of data. Although larger amounts of information give data scientists an opportunity to gain greater insight and make more informed decisions, it also presents a number of challenges as it pertains to available memory, processing time and storage capacity.
Paul Pilotte, technical marketing manager for MathWorks, was recently featured in Electronic Design. In the article, he stressed the importance of big data analytics tools that support the increasing size of datasets in a wide variety of industries.
“More and more companies are finding that if they can access data from lots of different sources while using more sophisticated predictive analytics tools like machine learning, they can make better and more accurate decisions,” he said. “We’re finding this to be true across nearly all of the engineering disciplines, whether on the medical device side or in aeronautics.”
Predictive Analytics Tools
MATLAB provides a number of these predictive analytics tools to help solve the issues associated with big data. For example, you can use the MapReduce functionality built into MATLAB to analyze data that does not fit into memory. A powerful programming technique, this can be used to analyze data on your desktop or run analytics on big data platforms such as Hadoop.
Another effective MATLAB tool is the “datastore” function, from which you can access data that does not fit into memory. This function also allows you to define the data you want to import from your files or database tables, define the format to apply to your imported data, and manage the incremental import of your data.
Other tools include memory mapped variables, 64-bit computing, disk variables, intrinsic multicore math functions, parallel computing, cloud computing, distributed arrays, image block processing and streaming algorithms.
Due to its functionality, high-level language and graphics features, predictive analytics tools, and a desktop environment tuned for exploration and problem solving, MATLAB is one of the easiest and most productive programming languages for engineers and scientists, and a highly effective data analytical tool.
If you are interested in enhancing your knowledge of MATLAB, consider pursuing a degree in data science.