Business Intelligence in Agricultural Analytics

This report discusses the benefits of integrating Business Intelligence (BI) technology within the agricultural sector. It covers data collection and storage, consumer-centric product design, recommendation system, and business continuity. The report concludes that the use of big data tools and cloud computing has helped in the storage of data systems within the agricultural field.

Running head: BUSINESS INTELLIGENCE IN AGRICULTURAL ANALYTICS
Business Intelligence in Agricultural Analytics
Name of the Student
Name of the University
Author’s note:

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Executive Summary
In the recent times, the main focus of the government has been focusing on increasing
the yield of the agriculture. Integrating the technology of Business Intelligence (BI)
within the agricultural sector could be a major revolution for the sector of agriculture.
There are many benefits that would be made with the implementation of the BI
technology within the agricultural sector. In the age of technology, the use of big data
and various kinds of analytical tools are helpful in enabling various companies across
various kinds of industries in order to gain better financial and operational results. The
use of big data has helped in improving the operations of business within many
industries. The revolution of big data has brought about a revolution within the industry
of agriculture and has helped in modernizing the sector at a rapid pace. With the impact
of BI within the sector, several farmers and various kind of other stakeholders have
started to view the various benefits that includes the reduction in the savings of cost,
fertilizers, optimization of yield and many others. The use of big data analytics has
made a major impact within the industry of agriculture. It has brought major effects with
the implementation of the technology and would also bring changes in the future. This
report discusses about the various changes that have been brought with the
implementation of the technology and the future prospects of the technology.

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Table of Contents
Introduction........................................................................................................................3
1. Data Collection and Storage..........................................................................................4
1.1 Data Collection System............................................................................................4
1.2 Storage System........................................................................................................5
2. Data in Action................................................................................................................6
2.1 Consumer-centric Product Design...........................................................................6
2.2 Recommendation System........................................................................................7
3. Business Continuity.......................................................................................................8
Conclusion and Recommendations...................................................................................9
References.......................................................................................................................11

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Introduction
The advent of technology within the agricultural sector has been a major boon for
the sector. With the advancements in the field of technology, farmers would like to
implement the technology within the sector in order to yield better results of agriculture
such as better production of crops, high profits for the farmers and better quality of food.
The technological and the digital advancements are taking the industry within their grip
and has started improving the yield in the sector. It has also added much value within
the supply chain of farm to fork (Suprem, Mahalik and Kim 2013). It has also helped in
the usage of the natural based resources in an efficient way. The data that could be
generated with the help of sensors or agricultural based drones that are collected from
the farms or during the transportation of the crops would be helpful in offering
information about the seeds, crops, costs, soil or the use of fertilizer and water (Sonka
and Ifamr 2014). Several other kinds of technologies such as Internet of Things and
advanced analytics could be helpful for farmers in order to analyze real time data such
as temperature, prices, moisture content, weather or GPS signals. They also help in
providing valuable insights on the optimization and the increase of the yield,
improvement of the planning of the farm, making of the smarter decisions about the
needed resources and the places of distribution.
This particular report is undertaken to explain data collection and storage system
in agricultural sector. This report also discusses about the consumer centric product
design, the recommendation system and the processes for the continuity of the
business within the sector of agriculture.

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1. Data Collection and Storage
1.1 Data Collection System
Innovations in the field of big data within the agricultural sector and the analysis
of management, centers of the analysis of the image, mapping of the plants and the
mapping of crops. A predictive based analysis could also be used in order to make
smart decisions in the field of farming by the collection of real time data based on the
quality of the air and soil conditions, maturity of crops, costs of labor and availability of
equipments, weather conditions and many other forms of data. The analysis of the data
would be a challenge with the enormous increase in the data size (Lamprinopoulou et
al. 2014).
This data would combine in order to assess the level of performance and crop
management, operations of the field and soil. Agriculture is regarded as one of the
important survival sources. The analytics of big data in the applications of agriculture
have provided a greater insight in order to provide advanced decisions on the weather
that would affect the farm conditions (Schader et al. 2014). They would also be helpful
in yielding the productivity and thus avoid unnecessary cost that would be related to the
harvesting and the use of fertilizers and pesticides. Efficient techniques of spatial data
are much required in order to gain valuable information from the spatial sets of data. In
present conditions, the techniques of spatial data mining are as classification, clustering
and association (Shelestov et al. 2013). An effective analysis of the data was performed
by using the techniques of hybrid data mining by the mixture of the techniques of
classification and clustering.

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1.2 Storage System
In the age of advancing technology, the systems of storage should be designed
in such a way that it should be able to handle the agricultural data (Abbasi, Islam and
Shaikh 2014). It should be also able to promote the processing of heavy server that
would be needed in an efficient cost effective way. The rising need of the forestry
inventory and agricultural data has provided the challenge to deliver high quality
systems of storage of the data (Channe, Kothari and Kadam 2015). The need for the
use of the tools for the analysis of big data is mainly emphasized with the requirement
of big data. The real time data could be stored in various kind of servers. The farmers
also have the need to gain the valuable information related to their crops and various
other aspects related to the agricultural sector. The technology of cloud computing is
one of the recent technological trend that could impact the agricultural sector (Bosona
and Gebresenbet 2013). The data stored in the cloud infrastructure could be easily
accessed by the farmers. The security of food is another major factor, which can help in
promoting the widespread adaptation of Information Communication Technology (ICT)
within the sector of agriculture (Abdullah and Samah 2013). The tools for ICT that could
be used in agriculture include Google Earth engine. They provide the tools and methods
of computing based on parallel processing. With the help of this tool, agricultural
scientists would be able to collect information that would be time sensitive based on
weather and water (Haldane and Antle 2015).

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2. Data in Action
2.1 Consumer-centric Product Design
The consumer centric is a kind of activity of the business with the consumer in
such a way that it would be able to provide a positive business experience with the
consumer before and post-sale to drive business repetitiveness, loyalty among the
consumers and incurring more profits (Singh, Keshav and Brecht 2013). The process of
consumer centricity is not only limited to the providing service to the consumer. It is also
meant to offer greater experience from the stages of awareness through the process of
purchasing and after the purchasing has been made. The consumer-centric is a kind of
strategy, which is based on the principle of putting the consumer at the topmost priority
and the core level of the business (Bogers, Hadar and Bilberg 2016).
Putting the customer at the core of the business model would help in the
incurring certain benefits, which could be majorly used to enhance the experience of the
customers.
 The use of the data of the consumers would be helpful for the business in order
to understand the behavior, engagement of the consumers within the business
and the varied interests of the consumers (Spiess et al. 2014).
 With the help of the data, business could help in identifying various opportunities
in order to develop services and products for the benefit of the consumers.
 The lifeline value of the consumers could be used in order to segment the
consumers based on the value of top spending consumers.
In the recent agricultural trends, the dynamics based on agriculture are changing
at a rapid pace (Badia-Melis, Mishra and Ruiz-Garcia 2015). The trend of the

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agricultural sector would be moving from the methods of traditional farming towards
smart farming. The primary goal within the agricultural sector is to improve the
productivity within the agricultural sector while meeting the demand of the consumers in
order to reduce the varied use of famous pesticides and various kinds of chemicals on
the crops. There were many startups and IT organizations that have helped the farmers
in order to manage the pests, diseases among the plants, conditions of the weather and
yield of supply of crops (Cavallo, Ferrari and Coccia 2015). The tools for analytics and
supporting of decisions use the sources of data in order to present recommendations to
the consumers. The use of analytics of data would also help in growing more crops. It
also helps in fostering loyal relationships with the core customers within the process.
2.2 Recommendation System
One of the prime causes for the continuous breakdown in the trends of
agriculture is the crop cultivation, which is not so suitable with the factor of environment
such as weather and the conditions of the soil. The problem could be solved with the
help of the Recommendation System (Kumar et al. 2013). It is a kind of system of the
filtering of information that would be able to forecast the items that might be some
additional interest for the users. The recommendation system could also be helpful in
providing various kind of suggestions for a particular kind of crop, which could be
cultivated on the basis of the weather and the soil conditions (Moore et al. 2015).
The content-based systems would be able to examine the properties of the
various items for the purpose of recommendation. The collaborative systems of filtering
would be able to automatically extract the structured form of information from the

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unstructured form of information or other form of machine readable documents
(Nikolidakis et al. 2015).
3. Business Continuity
Every form of business has to prepare for the worst kind of situation, which might
arise from the outages of power or any other kind of disasters. The online businesses,
which are meant to store the agricultural data of the various farms have to take the
responsibility to store the data of the farmers in an efficient way. A proper Disaster
Recovery Plan (DRP) should be designed in order to save millions of money (Wallace
and Webber 2017).
A proper disaster recovery plan is a kind of plan that is mainly used for the
restoration and providing accessibility of the data in the cases of disaster, which could
destroy every part of the resources of the business. The job of the DRP is to ensure the
happenings in the surroundings such that critical data could be easily recovered within
the possible shortest time (Dowd et al. 2014). There are many kind of disasters, which
could happen such as natural, man-made or technological disaster such as outages of
power. A backup generator could be the primary support in cases of power outages
(Castillo 2014). UPS could also be another form of technique to solve the problem in
cases of disasters faced by online businesses. These are the kind of battery systems
that are particularly designed in order to plug-in such kind of things such as
workstations, routers and different kind of servers in the cases of loss of power.
Irrespective of the size of the online business, a situation of a disaster would
bring the entire operation of the system to a state of halt. The business should be able

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to recover itself as soon as possible in order to provide the continuity of the services to
the clients and the consumers of the business. Downtime is one of the largest expenses
of IT, which could be faced by any kind of business. With the help of the a proper DRP,
a company or a business could save themselves from several kinds of risks that would
also include out of the budget expenses, loss of the reputation of the company, loss of
important data and hence would provide a negative impact on the customers and the
clients (Yang, Yuan and Huang 2015).
Conclusion and Recommendations
Based on the above report, it can be concluded that the advent of digital
technology could play a vital role in the field of agriculture. The report discusses about
the various forms of systems for the collection of the data and the various forms of
systems for the storage. These data storage systems are much vital for the collection of
the vital information that are in relation with the agricultural sector. The collective use of
big data tools and the other tools of cloud computing have helped in the storage of the
data systems within the agricultural field. Although the use of big data within the smart
farming techniques is at the primary stage of their development, yet they have made a
major amount of impact at the places where the technology is being used. Many of the
global based issues such as the security and the safety of food are being addressed
with the applications of big data. The report also discusses about the consumer centric
product design, which described the fact that different organizations and businesses
should put forward their consumers on the topmost priority. They should be listening to
the complaints and the grievances of the consumers in order to decide about the best
possible measures, which should be designed in order to solve the various issues.

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Based on the consumer based actions, a proper system of recommendation have to be
designed that would be able to tackle the several issues related to the agricultural
sector. These would be helpful in increasing the yield and better production of crops in
the future.
The use of big data has played a major role within the scope of the organization.
Many of the global issues that are related to the security and the safety of food,
sustainability could be addressed with the applications of Big Data. The issues that are
faced in the agricultural sector could be solved within the scope of the big data
applications (Lokers et al. 2016). The use of the technology of Internet of Things (IoT)
could also bring about a major change within the industry. The agricultural sector is
mostly referred to as the form of an industry that would be able to gain much amount of
profits with the coupling of the IoT framework. The IoT technology would be helpful in
providing the ability to collect the objective based information in an automatic way.
These information could be in relation with the status of the conditions of the soil, crops,
water and animals. The development of the IoT framework, which would help in
connecting every kind of devices and objects within the farming environment and the
chain of supply would also help in producing many of the new kind of data that are
accessible in real time environment (Dlodlo and Kalezhi 2015). The transactions and
operations are also regarded as one of the sources of process mediated data. Different
kinds of sensors and robots would also help in producing non-traditional data. With
regards to the traditional methods of the manual collection of data, it has been seen that
digital based technology could provide better insights for the higher production and yield
within the agricultural sector.

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