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Descriptive Analytics

Applying knowledge along with business acumen to make better decisions

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Descriptive analytics help us describe what things look like now or what happened in the past.

The idea is to use that information to better understand the business environment and how it works and to apply that knowledge along with business acumen to make better decisions going forward.

Descriptive analytics can take the form of simple aggregations or cross tabulations of data, simple statistical measures, more sophisticated applications of descriptive statistics or advanced association or clustering algorithm.
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Technologies that we use

We use a variety of software tools that help us master data management, metadata management, data quality and data analysis and visualization, such as:

  • R
  • Python
  • SPSS
  • Tableau
  • XLMiner
  • OpenRefine

R Algorithms

Python Algorithms


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Application areas

There are a wide variety of sales, finance, supply chain, logistics, and transportation applications where the value, location and movement of objects are critical to the function of a business, and where there is need for data analytics.





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