Data Analysis Software
Data analysis software refers to a set of tools that support the analysis process of datasets with a wide set of implemented algorithms. They often also enable a variety of often necessary data preprocessing steps such as sampling, data format conversions, feature selection or distinct feature enhancement techniques. This article provides a short survey of data analysis software in order to obtain an overview of existing tools in the field. A small note is given whether the software is commercial or free alongside certain tag information.
Tags: data analysis, parallel computing, deep learning
One of the best known and often highly rated data analysis software is Matlab from Mathworks. It is a mathematically oriented programming environment for data analysis, visualization, numerical computation and offers a wide set of existing algorithm libraries. The Matlab software also supports the development of deep learning models such as designing a Convolutional Neural Network with just a few lines of code. With respect to big data processing, Matlab offers the Parallel Computing Toolbox that can be combined with certain algorithms in order to use multi-core processors and clusters as well as many-core processors such as GPUs.
Tags: data analysis, platform, hadoop, spark, deep learning, keras, tensorflow
Another broadly known data analysis software is RapidMiner that is a fast platform for data preparation, machine learning, and predictive model deployments. Besides the RapidMiner Studio and Server software tools there is also a RapidMiner Radoop software that enables the parallel execution on Apache Hadoop and Apache Spark infrastructures. RapidMiner Studio provides deep learning functionality through its Keras extension that is in turn using the TensorFlow backend. Please refer to our article on RapidMiner for more details.
Statistical Computing with R [free]
Tags: data analysis, GUI
A free and often used data analysis software is Statistical Computing with R also named as ‘R’ for short. The functions of this software are very extensible and there are many CRAN libraries where new and innovative algorithms can be downloaded. There is also an interesting Rattle GUI for R Tool that enables various data visualizations and easy analysis of data.
The above list is not necessarily complete as new tools and software is being developed and finished almost on a daily basis especially when considering the momentum of ‘big data’ today. Comparisons of the above mentioned data analysis software and tools can be performed using their various functions and characteristics. One interesting Web page that compares a number of tools is Capterra that lists the best statistical snalysis software from a business perspective.
Data Analysis Software Details
Have a look at the following video with more details: