Analytics

How efficient are your processes? How efficient is your Industry? How does this year compare to other years? 
Our GIS and Analytics team at PAQ have experience working with large sets of complex data and turning them into meaningful information. 
We can use real data to produce information that helps you decide where and when to best apply your resources. 
Our PAQ Team will help you locate, collect, analyze and summarize the data needed to answer the questions you have. 

Analytics Projects

Fertilizer Sales Data Analysis

PAQ has developed a fertilizer product sales database to support the IPNI NuGIS project. This database compiles 23 years worth of fertilizer sales data from the American Association of Plant Food Control Officials (AAPFCO) and each record details the product sale by County, Year, Season, Product, Container, intended use, percent N, P, & K, and volume sold. The raw data consists of over 8 Million records and is stored on a dedicated database server. 
PAQ also developed customized scripts and algorithms to perform estimates using the AAPFCO data that allow us to estimate volume of Farm fertilizer nutrients at the county level for all years, in all states. 
 

AgriStats

Agristats, a development of the International Plant Nutrition Institute, is an entirely web-based information system designed to collect agronomic and fertilizer use data for regions throughout the world.  
The site produces medium to long-term projections of realistic agronomic market potential and boundaries for major crops and serves as an enterprise data entry point and clearinghouse for a large amount of agronomic data in the form of regional crop profiles.
IPNI worked with PAQ Web Developers and Programmers to build the Agristats site. Numerous complex algorithms were written to support the data summarization and projection functions of the Agristats site.   
 

Field Trial Analyses

PAQ works with several clients to perform analysis of data collected during Agronomic field trials. 
Clients and farmers collect observations of practices used in the field, such as fertilization rate, tillage, and cover crops as well as quantitative observations made during the growing season and at harvest. PAQ Analytics staff combine the data collected in these observations and perform analysis to identify correlations, produce summaries of practices used and prepare reports.