MathWorks today introduced Release 2016b (R2016b) with new capabilities that simplify working with big data in MATLAB. Engineers and scientists can now more easily work with data too big to fit in memory. R2016b also includes additional features in Simulink; a new product, Risk Management Toolbox; and updates and bug fixes to 83 other products.
Tall arrays now provide a way to work naturally with out-of-memory data using familiar MATLAB functions and syntax, removing the need to learn big data programming. Engineers and scientists can use tall arrays with hundreds of math, statistics, and machine learning algorithms. Code can run on Hadoop clusters or be integrated directly into Spark applications.
R2016b also includes a timetable data container for indexing and synchronizing time-stamped tabular data; string arrays to help manipulate, compare, and store text data efficiently; and new functions for preprocessing data.
“Companies are awash in data, but struggle to take advantage of it to build better predictive models and gain deeper insights,” says David Rich, MATLAB marketing director, MathWorks. “With R2016b, we’ve lowered the bar to allow domain experts to work with more data, more easily. This leads to improved system design, performance, and reliability.”
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