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What is data analysis software?

Data analysis software is software that runs mathematical processes on large sets of data for statistical, qualitative, or predictive analysis. This software is often used by universities, healthcare organizations, industrial research and development departments, and highly technical companies with large data sets. Researchers, software programmers, and data analysts are the primary user bases, as these tools often require the use of statistical programming language knowledge.

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Types of data analysis software

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Statistical analysis software

Statistical data analysis software processes and runs complex mathematical formulas on large stores of data. These tools use statistical programming languages like R or Python to create statistical models based on data that the statistical engineer, researcher, or data analyst loads into the software.

While initially derived for highly-complex academic, medical, or scientific research purposes, these tools are widely used in industrial and manufacturing industries that need to identify and improve their processes and refine materials to stay competitive.

Qualitative data analysis software

Qualitative data analysis software uses similar mathematical processes to help academics, researchers, and businesspeople understand trends and statistical data points from non-numerical inputs like text, video, audio, and images. The tools also use statistical analysis and machine learning to help users understand their data.

Qualitative data analysis software often lets analysts identify different types of information and non-text data that they can then teach the software to identify on its own. These tools speed how much data individual analysts can digest, improving the speed of research and time to action on data.

What are the benefits of data analysis software?

Big data ingestion

Data analysis software puts data stores from data warehouses or lakes to work for the company. Companies that produce lots of data during daily processes can then use that data to make better business decisions. These tools are designed to access large stores of data before running formulas and analysis. The speed at which software for data analytics can ingest and make sense of large data stores sets it apart from typical business intelligence or data visualization software.

ML and AI tools

Data analysis software is built around complex statistical analysis and mathematical equations, which significantly increases the computing power of a single company or organization. These tools often dovetail easily with machine learning (ML) and artificial intelligence (AI) algorithms that in turn reduce the manual oversight of the data analysis. ML and AI functionality give organizations the freedom to work as data analysis facilitators rather than getting mired in repeating the calculations.

Complex statistical analysis

The main benefit of data analysis solutions is their ability to perform complex statistical formulas on large sets of data. The software comes complete with pre-programmed formulas like Monte Carlo simulation, automatic linear models, cluster analysis, and ordinary least squares regression. In addition, many data analysis software tools let analysts code their own formulas, providing room for customized outcomes.

Choosing the best data analysis software for your organization depends on the needs of the team and the types of data your company deals in. Lower-priced open source options may fit the company’s budget at first glance, but the human resources needed to customize and run the software with little support may quickly outpace the savings.

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