The Problem With Agriculture System

Every day, we produce 2.5 quintillion bytes of data. 90% of all data in the world was produced in the past two years. Data has been around forever; we have always gathered information. Paleolithic cavemen recorded their activities by carving them in stone or notching them in sticks. Egyptians used hieroglyphics to record significant events in history. The Library of Alexandria was home to half-a-million scrolls of the ancient world. Less than hundred years ago, we used punch cards to record and store information. As technology continues to evolve, the amount of data we store continues to grow. We’ve come a long way since stone tablets, scrolls, and punch cards. It’s important to understand the concept of big data and the impact is has created. This paper will define the classifications of data, explain the challenges of big data, and describe how big data analytics is being used in today’s data driven world.

As the growth rate of the population steadily increases, a surge in consumption of commodities will additionally increase . One basic commodity that will have an escalated demand would be food. Innovation within technology has allowed the process of mass production of goods. Production of goods on a large scale allows farmers to meet the needs of the majority of consumers capitalizing on market share. In order to meet consumers forever growing needs, land must be acquired in order to generate new farms for agriculture. Although the needs of consumers are being meet, the act of mass production of agricultural is contributing to the destruction of our planet. Consumers need to be aware of the repercussions of mass production on a global scale, in order to create a sustainable outcome while still continuing to let needs be met. With contributing factors of global warming , the population needs to be informed of harmful processes through agricultural farming such as deforestation, livestock, and crop emissions.

The author points out that although there are existing algorithms and tools available to handle Big Data, they are not sufficient as the volume of data is exponentially increasing every day. To show the usefulness of Big Data mining, the author highlighted the work done by United Nations. In order to further enhance the reader’s perspective, the author provided research work of various professionals to educate its readers about the most recent updates in Big Data mining field. The author further describes the controversies surrounding Big Data. The author has first provided the context and exigence by elaborating on why we need new algorithm and tools to explore the Big Data. The author used the strategy of highlighting the logos by mentioning the research work of different industry professionals, workshops conducted on Big Data and was able to appeal to connect to the reader’s ethos. The author also used pathos by urging the budding Big Data researchers to further dig deep into the topic and explore this area

With the growth of technology, there is a substantial growth of data by volume, variety and velocity satisfying the criteria of Big Data . Volume of data already exceeded 100 EB at the end of 1990s, reached 1.8 ZB at 2011, and we have already entered in the age of ZB. By 2020, it was forecasted that the volume of data will be 50 times bigger than the one at 2011 . Big data is used to describe the huge data sets (terabyte to Exabyte) and Big Data analytics are the techniques applied on them.

Big Data Analytics is the process of analyzing large amounts of raw information generated and stored. In today 's fast paced technologies, we are inundated with in a tsunami of data before us. All applications, in a broader range are depending on data in a remarkable way. BDA is driving almost every field in our society from Retail, Manufacturing and Mobile applications to life and physical sciences. The Data Analytics techniques are performed to uncover hidden patterns, unknown correlations and other useful information. Earlier, Data Analytics were based on guessing and inaccurate data models but currently this can be done directly. Big Data has truly revolutionized scientific research (Computing Research Association 2014).

As a result of the appearance of big data in our world, conventional data warehousing and data analysis methods no longer have the process power needed. What is Big Data you may ask and why is it such a big deal. NIST defines big data as anywhere “[…] data volume, acquisition velocity, or data representation limits the ability to perform effective analysis using traditional relational approaches […]” (Mell & Cooper, n.d.).

Big data is a term that describes a large volume of data. This data comes in the form of structured and unstructured data. Structured data is information taken and sorted in rows and columns while unstructured data is pictures, tweets, videos, and location-based data. It is not surprising to see many businesses today utilizing data for financial gain. Businesses are harnessing data and using it to make investment decisions, marketing strategies, fraud reductions, and much more. These businesses and organizations can expect to become more profitable, effective, and efficient, but pushes the limits

In this note, we tackle both the hype and practical matters surrounding big data, including questions

Animals living conditions, diet and reproduction is not the only problems associated with commercial farming. Hamburgers and hot dogs these are American foods but how does it get there on our plate. Do people know how the animals are slaughtered or do they even care. Slaughter this means killing of animals for human consumption. When it comes to the slaughtering of animals I think the majority of people don’t care that the animals are being killed to be eaten. The thing that causes the controversy is how are they being killed and are the animals being slaughtered in a humane way. If someone ask are these animals being slaughtered humanely the answer would be yes of course but really I believe that if most people seen or knew the way that some animals are killed humanely still seems inhumane. That being said there are times I’m sure when things are being done that would not be considered proper procedure. This will always be a very contraversal issue because you have people who believe you shouldn’t at all use animals for anything like food or beauty products whatever it may be and then you have people on the other side who really just don’t care about animal lives. So due to the Humane Slaughter Act of 1958 it was determine that the animals must be unconscious so that they don’t feel as much pain (Dunn 2011). The methods that were used was anything that would be quick and cause little pain, such as a gunshot to the head or electrical shock just anything rendering them

The “Big Data” becomes a common word now in Information Technology and Business world. These two simple English words created history and meant a ton in Global market. In past the data refers to traditional data and data volumes either in single or multiple terabyte ranges. But today it’s beyond traditional data and includes real time transactional data which is a key to the business systems.

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

Background: Big Data has a background of data aggregation and metadata. It is the basis for future of business analytics.

With 3.2 billion internet users [1] and 6.4 billion internet connected devices by 2016 [2], unprecedented amount of data is being generated and process daily and increasing every year. The advent of web 2.0 has fueled the growth and creation of new and more complex types of data which creates a natural demand to analyze new data sources in order to gain knowledge. This new data volume and complexity of the data is being called Big Data, famously characterised by Volume, Variety and Velocity; has created data management and processing challenges due to technological limitations, efficiency or cost to store and process in a timely fashion. The large volume and complex data is unable to be handled and/or processed by most current information systems in a timely manner and the traditional data mining and analytics methods developed for a centralized data systems may not be practical for big data.

Today data is being flooded in all means as it is being collected in unprecedented ways. Decisions which were taken by way of guesswork and difficult models can now be made on the base of data itself. Big data analysis can be dream on every aspect of today’s society - Mobile services, manufacturing, retail, life sciences, financial services and physical sciences. Big Data has the potential to revolutionize scientific research, education, use of Information

The rethinking of the institutional analysis of the municipalities in metropolitan cities reveals a new question with respect to the type of governance to be implemented to restore to agricultural systems a leading role in the creation of well-being and especially for its maintenance over time and space. The metropolitan cities will implement agricultural systems and not only from a geographical and institutional point of view but also in functionality. In this perspective, it becomes essential to adopt appropriate governance models, capable of ensuring a substantial contribution of agriculture to the pursuit of sustainable well-being, but above all to resolve the apparent question between local or global governance (Webb, Kernaghan, 2005). More precisely, new forms of governance and organization of the sector are required so that agriculture can find in the proximity markets the right tools to sustain the building and the keeping of well-being of society and of the territories in which the various stakeholders can pursue shared objectives and no longer exclusively local ones. In other words, it becomes essential to adopt models of sustainable territorial governance .