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The agricultural industry has numerous areas for future development with big data. Quite a few are already underway Some of the opportunities that come from data analytics in the future revolve around assisting farmers in finding better, more efficient ways to plan, produce, and protect their crops.

“One of them is a Brazillian company called Agrosmart. Its technology relies on Internet of Things (IoT) sensors and artificial intelligence to determine the kind of insects on a crop and the quantity present. Farmers then get an associated report and can use it to plan their pest management approaches. The goal is to help farmers cost-effectively control pests with a minimized environmental impact” (Matthews, K., 2019). Data analytics that can fight pests and save farmers money.

Another interesting piece to look at is things like what’s being fed to poultry and livestock. “For example, researchers know trace minerals positively affect the metabolic functions of livestock and poultry, while carotenoids play a role in increasing egg yolk quality and nutrition” (Matthews, K., 2019).

Even future projects that will help farmers deal with the effects of climate change. “One project involves giving IoT sensors to Taiwanese rice farmers so they can collect crucial information about their crops. It’ll all go into a database used to help farmers optimize their production cycles, even when climate change makes that task exceptionally challenging. Following the traditional farming calendar is no longer sufficient because of climate change. But, data analysis could forever change the future of farming” (Matthews, K., 2019).

Based on these kinds of ongoing projects, I imagine that agriculture is one industry that would see enormous ROI with data analytics. Saving farmers and ranchers time, money, and improving quality of life for crops and livestock.

I think healthcare will continue to find difficulty truly utilizing the full potential of big data.

“ Front-line clinicians rarely think about where their data is being stored, but it’s a critical cost, security, and performance issue for the IT department.  As the volume of healthcare data grows exponentially, some providers are no longer able to manage the costs and impacts of on premise data centers” (Bresnick, J., 2017). The sheer scope and future-proofing of such a project is daunting to think about and both security and integrity of data are paramount. 

Data analytics projects in the future will most likely continue to mature and client expectations will be better set on what they should expect from a project like this. Things like that will give the industries better common sense and then organizing and collecting the data will continue to be tightened up until data analysts will be looking at clear lanes with far fewer fatal errors or painful lessons-learned during such projects.


References:

Bresnick, J., (2017). Top 10 Challenges of Big Data Analytics in Healthcare. Retrieved from https://healthitanalytics.com/news/top-10-challenges-of-big-data-analytics-in-healthcare 

Matthews, K., (2019). 6 Ways the Agricultural Industry Is Benefiting From Data Scientists. Retrieve from https://towardsdatascience.com/6-ways-the-agricultural-industry-is-benefiting-from-data-scientists-b778d83f61db