Data Analytics


Data Cleaning and Pre-Processing

Once your data has been brought into the MATLAB environment, it often requires a significant amount of pre-processing or cleaning, before it can be used for analysis or modelling. MATLAB allows you to pre-process your data in the same environment that you use to explore, visualise and model it. MATLAB’s high-level array oriented language helps simplify what can otherwise be time consuming tasks, such as:

  • Cleaning data that has errors, outliers, or duplicates
  • Handling missing data
  • Removing noise from sensor data with advanced signal processing techniques
  • Smoothing, reducing or expanding data sets
  • Merging and time-aligning data with different sample rates
  • Feature selection to reduce high-dimension data to improve model predictive power
  • Feature extraction and transformation for dimensionality reduction
  • Domain-specific techniques such as signal, image, and video processing

The MATLAB language is built for efficient handling of multi-dimensional arrays of data at a low level, making it a natural choice for dealing with the otherwise challenging tasks associated with cleaning and preparing raw data for analysis. For domain-specific analysis, MathWorks offers an array of toolboxes containing functions aimed specifically at processing certain types of data, such as image data, video data or signal data. Our consultants can advise you on best practices for data cleaning and pre-processing, or assist you with the automation of these tasks, so that you don’t waste time on repeatedly performing the same steps each time you obtain new data.