Big Data is a complex term that can be overwhelming when first learning about it. I found clarity for this term during a lecture on airport security by Jacqueline Kusnic. By explaining how big data features in multiple areas of airport security it showed how diverse and important it is. From this lecture I found that the use of data collection in airports could be compared to the livestock industry and the complex nature of the data acquired through and for it.
Airport security and the livestock industry are very similar when you consider how integral data collection is too their success. A major example of which being; while airports use data collecting to categorize and recognize potential threats the livestock industry uses it to monitor the supply and demand of beef for both domestic and international needs.
Within the livestock industry Big Data plays an essential role in the breeding, marketing and distribution of millions of animals per annum. The cattle industry in particular heavily relies on the use of data collection, with it being used in many processes; from the breeding sector to livestock sales and to the market ready product we eat.
GrowSafe is a recent technological advancement in the data collection front for beef growers. The software enables the monitoring of cattle, at both group and individual levels to allow for more effective selective breeding and meat production. “These sensors constantly collect data on the weight of the animals, plus their movements, drinking behaviors, feeding behaviors, temperatures, and all kinds of other data.” (So, 2013). This means that not only do farmers access the information needed to use their money more effectively but that over time they are able to create more accurate breeding, selling and feeding schedules.
The use of big data has also influenced the dairy industry significantly, it has the potential to assist breeders in identifying genetically superior livestock whilst they are still developing. Instead of having to prove themselves, farmers are now able to predict a bulls worth by using its DNA to create a Net Merit through a complex formula that evaluates all the necessary attributes needed in dairy production. “Dairy breeding is perfect for quantitative analysis…milk production, fat in the milk, protein in the milk, longevity, udder quality, that breeders want to optimize” (Madrigal, 2012), with farmers investing up to thousands of dollars per beast, with their productive, non breeding, lives being three to four years it is vital that farmers invest their money and time where it is needed the most.
Through the technological advancements made in recent years, and due to the collection of data used to make these advancements operate at optimum level we are now seeing an increase of productive cattle and a more streamlined production process. In the last 70 years milk production has increased by over 400% with the average dairy cow producing 5,000 pounds of milk in its lifetime in 1942 compared to 2013 where the average dairy cow produced over 21,000 pounds of milk per lifetime (Madrigal, 2012). This dramatic increase is the result of the collection and analyzing of masses of data and advancements in the fields of genetics, as well as substantial levels of hard work.
For examples of Net Merit see;
Ironbark Stud breed bulls specifically for meat production compared to Oldfield who breed for female heard growth.
Oldfield Poll Herefords (2014) Oldfield Dynamite!, Herefords Australia Ltd
Madrigal, Alexis (2012) The Perfect Milk Machine: How Big Data Transformed the Dairy Industry, The Atlantic
Jacqueline Kusnic , Lecture, 2014
So, Candice (2013) Using Big data to improve farming, one cow at a time, itBuisness