Big Data Technologies: Hadoop vs. Cassandra in Government Sectors

This report provides a comprehensive analysis of Big Data applications within both government and business sectors, drawing from the provided article. It delves into the attributes influencing Big Data implementation, including decision-making processes, organizational structures, and financial resources. A detailed comparison and contrast between two key Big Data technologies, Hadoop and Cassandra, is presented, highlighting their respective strengths and weaknesses. Furthermore, the report explores the major purpose and components of Decision Support Systems (DSS), crucial for leveraging Big Data insights. The report also touches upon social, ethical, and professional aspects of Big Data applications in government sectors, including expert systems, image processing, and the use of rule-based systems, and the characteristics of a "low pass filter" in image processing. The report aims to provide a clear understanding of the role of Big Data in modern organizations and its implications for decision-making and public service.

Running head: APPLICATION OF BIG DATA IN GOVERNMENT SECTORS
Application of Big Data
Name of the student:
Name of the university:
Author note:

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Table of Contents
Introduction:....................................................................................................................................2
Discussion:.......................................................................................................................................3
Attributes involved in the implementation of Big Data application in Business Sectors and in
Government Sectors:...................................................................................................................3
Comparison and contrast between the two Big Data technologies:............................................5
Decision Support System:................................................................................................................7
Components of Decision Support System:..................................................................................8
Major purpose of the decision support system:...........................................................................9
Social Ethical and Professional aspects of Big Data application in Governmental Sectors:.....10
Expert System and Image Processing:...........................................................................................12
Expert System Methodologies...................................................................................................12
Rule-based system:....................................................................................................................12
Application of Big Data using the Rule-based system:.............................................................12
Benefits of the expert system in the application:.......................................................................12
Characteristics and use of a “low pass filter” in image process:...............................................13
Conclusion:....................................................................................................................................14
References:....................................................................................................................................15

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Introduction:
Big Data is a word that is mainly utilized for the gathering of data collections that are
huge and intricate in nature. As these kinds of data are huge and vast in nature hence it becomes
difficult to process with these huge chunks of data with the use of traditional tools (Chen, Mao
and Liu 2014). Often the data that are collected exceeds their size by terabytes as varieties of
data are encompassed within it. With this combination of huge amount of data, often it becomes
a huge challenge for processes as they become more complex and consumes huge amount of
volume. The data that are collected through Big Data technology are often unstructured and raw
and hence are difficult to analyze through the method of conventional relational database
methods. As technology advances, the use of Big Data is gaining much more importance in order
to obtain data from web and cloud services while opening opportunities for creating values and
business intelligence that are rich in nature while opening platform for decision support system
within organizations (Gandomi and Haider 2015). With the use of Big Data new challenges also
evolve with more complexity, privacy and security issues related to the new technology
application and also errors due to human skills. Big Data is becoming the latest trend to
transform industries and business platforms of modern era where data is mainly responsible for
driving the performance within business and increasing the competitiveness. Like any other
sectors, Big Data is also used in governmental sectors as well as in Business sectors so as to use
the data obtained for the purpose of promoting good to public (George, Haas and Pentland 2014).
This part of the report is thus prepared so as to imitate the position of Big Data Application in the
field of business and government sectors while paying special attention to the practice of two

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important Big Data technology within the mentioned sectors while reflecting on the importance
of decision support system as a part of Big Data technology (Kitchin 2014).
Discussion:
Application of Big Data can enable both the governmental sectors as well as business
sectors to offer services that are effective in nature while enabling quick respond to the citizens
in times of need. Although business sectors are known to be the leader in the application of Big
Data knowledge but it is now spreading towards the governmental sectors as well to support
various decisions making system so as to make assessments in real time situations (Sauter 2014).
The various practice of Big Data in the governmental sectors are reflected in many journals and
articles while pointing out the ways by which the government sector can mark the use of Big
Data so as to help to serve its citizen better. Business as well as government sectors can make
usage of the Big Data technology so as to examine the derived values that are collected from the
digital data. Although the common mission for both governmental and business sectors remains
the same in attaining sustainable competitive advantages, the main goal of the government
sectors remains to achieve sustainable development so as to ensure security of its citizen while
maintaining their basic rights to promote economic growth and welfare benefits. Most of the
business sectors aims at making short term decisions that will act as an competitive advantage in
the market.
Attributes involved in the implementation of Big Data application in Business
Sectors and in Government Sectors:
The different types of attributes that are tangled in the implementation of the Big Data in
corporate sectors as well as in government sectors include:

4APPLICATION OF BIG DATA IN GOVERNMENT SECTORS
Decision making process: The evolution of Big Data involves decision creation process through
IT permitted decision support systems (Accorsi, Manzini and Maranesi 2014). The perception of
Big Data has evolved implying a wide quantity of data through the procedure by which Big Data
is extracted.
The decision making process of the implementation of Big data in the government sectors
consumes a huge amount of time as it includes a large amount of varied actors such as interest
assemblies or ordinary people (Kim, Trimi and Chung 2014). The implementation of the Big
Data analytics helps in acquiring decision making process while accepting the relationship
between the data patterns and supporting the predicted data in the next step of decision making
process.
The decision making process for the implementation of Big Data in business sectors
includes improving of real time data through customer engagement and through the process of
retention. The decision making process that is involved in the organizational sector enhances the
operational efficiency of the organization while optimizing the strategies related to sells (Mergel,
Rethemeyer and Isett 2016). Implementing a suitable decision making process in business
sectors also helps in growing the overall capacity of the business without extra investment.
Application of Big Data Analytics in business association helps to reduce the errors in networks
while optimizing the resources and also assistances in increasing the overall delivery rate (Chen
and Zhang 2014). Most of the business firms uses short term decision making processing order to
maximize the rate of self-interest and minimizing the cost while most of the Government sectors
makes use of long term decision making process so as to maximize the self-interest while
promoting the public interest (Erevelles, Fukawa and Swayne 2016).

5APPLICATION OF BIG DATA IN GOVERNMENT SECTORS
Organizational structure:
The detail organizational structure of business as well as governmental firms helps in
evaluating the scope of the implementation of Big Data while making suitable market decisions
and describing the external as well as internal factors that are used to determine the hierarchy
within the organization (Wu et al. 2017). The organizational structure of the business
organizations follows a hierarchical structure while the organizational structure of government
sectors forms the governance structure (Klievink et al. 2017).
Financial resources: The financial resources that are used by business organization is based on
revenue whereas the financial resources of government organization is based on taxes (Gupta
and George 2016).
Comparison and contrast between the two Big Data technologies:
Hadoop:
Apache Hadoop is a kind of java created software agenda that can efficiently store huge
quantity of statistics in a band. This type of outline runs in equivalent or in cluster and has ability
to develop data across all its nodes (Anuradha 2015). Hadoop consists of a Distributed File
System which is a kind of packing structure that helps in splitting the data while distributing
them across various nodes in the form of a cluster (Manikandan and Ravi 2014). This helps in
replicating the data in a bunch while providing its high obtainability. The hadoop technology
consists of an HBase that helps in storing the data in the HDFS (Oussous et al. 2018). The HBase
is mainly used in case of real time need and is random in nature so as to provide access to the
usage of big data. The HBase helps in providing support to the high volume of data via high
throughput (Lee et al. 2014). The technology of Big Data makes use of a sqoop which is a tool

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that is designed to transfer data between the NoSQL and Hadoop. It also enables managing and
importing of data from the relational database such as My SQL or Oracle and export the data
from the HDFS to the relational database systems. Implementation of the Hadoop technology in
big business organizational sectors is an useful approach as it includes using of cheap servers and
hence are more cost effective in case of storing data and further processing them. Hadoop
technology helps business organizations to provide better decision support system while
providing the history of data with the various record of the company. Hadoop technology is itself
a challenge for many business sectors as implementation of this technology requires expertise
and experience on widely available outsourced help. Finding the competent data scientist for the
implementation of Hadoop technology and also finding the right visualization technique to
analyze the data becomes the core difficulty that most of the organizations face and hence are not
implemented often.
Cassandra:
Except Hadoop technology, the most commonly used big-data knowledge that is casted
off in business administrations as well as in government organizations include the Cassandra
technology Chebotko, Kashlev and Lu 2015). The Cassandra data base technology is defined as
one of the highly scalable, increased performance distributed database that is designed so as to
handle the large sets of data across commonly used servers providing no point failure and high
availability of data. It is a type of NoSQL database that enables loading and retrieving of data
other than expending any tabular associations within the relational database. This type of
database are often scheme free and supports easy replication, consistent in nature and enables
easy handling of huge chunks of data (Hashem et al. 2015). The use of Cassandra database
within organization is the safest way to use database that affects the operational function when

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scaled in a single or cross multiple data centers. The use of Cassandra within organizational
sectors helps in providing multi datacenter support to the customers.
The main difference between the two kinds of Big Data technologies are as follows:
1. Hadoop is designed to be used in data warehouse for huge voluminous data whereas
Cassandra is used as a gossip protocol to keep the status of the nodes within the cluster updated.
2. Hadoop technology supports structured as well as semi structured or unstructured data but
Cassandra technology supports unstructured data with flexible schema (Marchal et al. 2014).
3. Big data hadoop technology uses big data processing framework while Cassandra is a
distributed No SQL database that is designed for managing huge amount of data sets.
4. Hadoop technology is mainly used for batch processing of data while Cassandra is mostly
used for real time processing of data.
However the government sector faces a number of challenges while choosing the right
kind of big data technology as they often faces issues regarding Big Data integration from
various sources with variety of costs and challenges (GalbRaith 2014).
Decision Support System:
Decision support structure is defined as a type of information structure that helps in
supporting the decision making activities of an organization or business (Gandomi and Haider
2015). It is a type of computer programmed application that helps in analysis of business data
that are present while enabling users to make decisions regarding business activities more easily

8APPLICATION OF BIG DATA IN GOVERNMENT SECTORS
(Qin 2014). A decision support system may be present within the organization in the form of a
information graphic and may include expert system or technologies like artificial intelligence.
Modules of Decision Support System:
A typical decision support scheme contains of three chief constituents which includes
database, software system as well as DSS user interface.
1. DSS Database: The database component of decision support system comprises data that are
collected from different sources such as data collected from internal sources of an organization,
data that are generated from different application software and finally the external data that are
often mined from the internet (Wamba et al. 2017). The database of a decision support system
can be small in size or it can be a standalone system enabling support to huge amount of data
warehouse information that are needed within an organization. In order to evade the intrusion of
decision making process, the scheme also supports the functioning of the operational structures
which contains a copy of the entire production of the database (Power 2014).
2. DSS Software System: The Decision Support System of the software consists of models
supporting the mathematical as well as analytical data that are sued to examine the multifarious
data sets while creating the required data. The model of the DSS software system helps in
predicting the required output based on different inputs while comparing the condition of
different combinations that are finally used to create the anticipated output of the data sets. The
models that comprises of the decision support system are meant for performing various functions
based on their specific performances. The selection of the appropriate model of the decision
support system rest on the necessities of the user and the purpose of the DSS. Some of the
frequently used replicas of the DSS include- Statistical models, Sensitivity analysis model,

9APPLICATION OF BIG DATA IN GOVERNMENT SECTORS
optimization analysis model, forecasting model, backward analysis sensitivity model and many
more.
3. DSS user interface: The third most component of the DSS includes the user interface which
is a type of interactive graphical boundary that allows communication between the DSS and its
users more smoothly (Kwon, Lee and Shin 2014). It displays out the result generated out of the
analysis of the data in various forms such as in the form of charts, texts or in the form of
graphics. Here the users can select their suitable options in order to view the production data
according to their necessity.
Major purpose of the decision support system:
A well-defined decision support system aims at collecting, organizing as well as
analyzing data related to business activities so as to facilitate quality in decision making process
of business for operations, management and planning activity. A suitable decision support
system helps in combining a variety of statistics from numerous sources such as collecting raw
data sets, personal knowledge or any type of documents received from employees, executives or
management groups of the business models. Implementing a decision support system helps in
solving problems while making effective decision s through the data that are collected and
analyzed.
Some of the typical information that is collected by decision support system includes the
following:
1. Revenue that are projected and the sales figures, that are based on projected sales on new
products.

10APPLICATION OF BIG DATA IN GOVERNMENT SECTORS
2. Comparative figures of sales that are collected during selected period of time.
3. Inventory data that are collected and organized into relational database systems for analysis
based on time periods.
Decisions support systems are used in various fields such as in case of verification of
credit loans or evaluating any bids during engineering projects. It is also used in business
management systems for the purpose of effective evaluation of raw data.
Social Ethical and Professional aspects of Big Data application in Governmental
Sectors:
Social Aspect:
The use of Big Data in Governmental sectors has the probability to deliver huge social
impact while helping in generating public benefits. With the introduction of different types of
models in the decision support system, the use of Big Data has created influence on the investing
of shared values, social innovations as well as social enterprises. The social impact of claim of
Big Data can be seen in the case of European Union where the commission initiated the Digital
Agenda within Europe while enabling delivery of sustainable economic as well as social
welfares to its inhabitants from a single digital marketplace via fast internet application. The
commission implemented strategies so as to ring Big Data into their effort helping in to ensure
data protection and gaining individuals trust while developing other technologies like IoT for
enabling communication between devices with huge interventions. Many of the South Korean
ministries are also known for implementing Big Data within their government sectors helping in
to initiate the Social welfare integration within the management network while allowing analysis

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of 385 dissimilar types of public statistics and handling those providing assistances by the central
government to the deserving recipients.
Ethical Aspect:
In directive to grant the ethical application of Big Data inside government sectors some of
the ethical aspects that needs to be kept in mind includes-
 Maintaining Privacy of self-management: This allows users the option to control their
data while allowing controlling the access to the data by opting in or out. However these
is not applied in reality as data are always collected, used and analyzed in random manner
and are often at the verge of risk of getting shared or abused.
 Maintaining transparency: Transparency is the sole need for the use of any technology
and should be applied to all stages of Big Data application. The group of stakeholders
who are involved with the data should be informed adequately about the actual purpose
of collecting the data and how it should get transferred or processed or analyzed in the
next step. It is significant to provide guarantee to the users that the data collected from
them will not be sold to any third party without proper consent.
Professional Aspect:
The benefit of using Big Data within government sectors has some professional aspects
as it includes generating and collecting of vast amount of data through the daily activities. It
allows advanced analytic features with the help of automated algorithms while improving its
effectiveness providing internal transparency of data collected. This helps in improving the
services that are provided to the citizens while learning from the performance of the services
from analyzed data.