Information Systems and Big Data: Techniques and Business Benefits

This report provides an overview of information systems and big data analysis, highlighting the characteristics of big data, challenges in its analytics, various techniques used, and the technologies employed to manage and leverage it. It discusses structured, unstructured, and semi-structured data, emphasizing the importance of volume, velocity, value, and variety in big data. The report also addresses challenges such as privacy, security, data access, data growth, and the selection of appropriate data tools. Techniques like data mining, machine learning, statistics, and data integration are explored, along with analytical and operational technologies. The conclusion underscores the role of big data in improving business operations, enhancing efficiency, optimizing costs, and ensuring data security, encouraging companies to adopt these techniques for sustained market presence. Desklib offers similar solved assignments and past papers for students.

Information Systems
and Big Data Analysis

Table of Contents
INTRODUCTION ..........................................................................................................................3
What is Big Data: .......................................................................................................................3
Characteristics of Big Data.........................................................................................................4
Challenges of Big data Analytics:...............................................................................................4
Various types of Big data Techniques:......................................................................................5
Big Data Technologies:...............................................................................................................6
Benefits of big data technology in business: ..............................................................................6
CONCLUSION ...............................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
Information system is an effective type of sociotechnical, organisational as well as
formal system which is basically designed to collect, store, process and distribute information.
On the other side big data refers to huge, complex and hard data which is difficult to understand
as well difficult for processing by using the traditional method. Main aim of this report is to
analyse how information system and big data technology and techniques helps organisation to
effectively manage their customer's data (Hariri, 2019). This report includes the brief discussion
related to various factors and characteristics of big data, challenges faced in big data, different
techniques which are available to solve big data issues. At the end of the report, various big data
technologies which supports the business to reduce the problems of big data.
What is Big Data:
Big data is an effective addition of structured, unstructured, and semi structured data
gathered by the company for the information. As the data gathered which have high volume,
complex, diverse, and it highly became complex when new source of data comes. These sets of
data are highly complex which are not easily managed or handle by the traditional data
processing. The volume of data is so vast which an individual conventional software cannot
manage or handle it on their own. The main fact about the big data is that it helpful in tracking
Vast segment of data which can be used to solve problem of business which are not been
potentially track or considered before. There are basically three types of big data which are
discussed below:
 Structured Data: It refers that structured data is an effective data model, having well-
structured defined data. Data which is basically stored in well manner like database. In
this structure data is established in a form of well-organised rows and columns which is
easy to access, so if someone want to use data they can easily understand and utilize the
data.
 Unstructured Data: Such type of data is not well classified or and in unstructured
manner, may be due to size of data which is large, complexity in data which are not well
define imposes various threats at the time of processing
 Semi-structure data: This type of data are not efficiently well-defined (Hamilton and
Sodeman 2020). Semi-structured Data usually not considered the format of tabular model

data because it is not fully structured, which makes difficult for the others to analyse the
whole data in an effective and efficient manner.
Characteristics of Big Data
 Volume: Data size plays an important role as it helpful in analysing the value of whole
data (Zhang Huang and Bompard 2018). Volume indicated size of data stored or
generated in big data system. Depending on the volume of data, specific data can have
considered as big data because it all depends on the volume of data.
 Velocity: Speed of data that how easily and effectively data is processed or generated in
term to fulfil the demands or to analyse the actual capability of the data. Velocity of big
data is basically considered at which speed data is flows from the various sources such as
networks, social media, processing of business, from applications etc.
 Value: Big data value plays also an essential factor in business. It is not only about the
amount of data which store or process but at the same time value of data is also reliable
and valuable which must be evaluate, processed to get useful insight about the data.
 Variety: Big data produce in multiple varieties from different range and diversity. This
refers to fundamental change in analytical needs from traditional data towards the
unstructured or semi-structure data for the process of making decision. Different types of
data collected from the various sources, and became essential for the business effectively
manage all the variety of data in an organised manner.
Challenges of Big Data Analytics:
 Privacy and Security: Data security and privacy is a big challenge which involves
conceptual, technical as well as sensitivity of data. There are many companies which are
not effectively manage their daily analyses of big data. It happens because of various
types of client’s data and information attached with big data which can impact sensitive
data of client. Also there are some companies which collect the customer's information to
increase their business value by considering their lives, form which the customers are
unaware.
 Data Accessing and Sharing: Sharing and accessing of data is also an another big
challenge for businesses. As it raises inaccessibility or approachability data set from the
various sources which are external. Data sharing involves the requirements of intra and

inter-institutional deeds of legal which can cause challenges of substantial, from the
public repositories it became difficult for accessing data.
 Issue of Data growth: Growth of data plays an essential role in the storage of large data
(Ghani, Hamid, and Ahmed 2019). An effective knowledge of these large set of data
helps the business to manage their business activities in an effective way. Quantity stored
in the data centres and company's databases are increasing rapidly. As with the time these
type of data base increase quickly and became challenging for business to manage. This
happens because many times data come as unstructured from different files, videos,
documents which makes difficult for the organisation to search out.
 Insufficient Understanding of Big Data: Lack of effective and efficient understanding
of big data can lead to create big challenge for the companies. This is because due to lack
of proper knowledge, companies find insufficient in completion of customer's data. For
example, in company if workers not know about how to create, proceed, or store data.
This create difficulties for them to create the plan for data. which requires privacy as well
security. At the time when the essential data is required workers are not able to find the
data on time.
 Creates disorder in selection of data tools: Selection of significant data tool became
challenging for the companies to handle big data. Companies find difficulties to select the
effective data tool for the storage and analysis of big data (Zhu and Tang 2018). For this
reason, company either to hire best professionals who know well about the big data tools.
Also Company can hire consultant for the analysis of big data because they provide better
and effective options about tools of big data.
Various types of Big Data Techniques:
 Data Mining: It is an essential tool for the analysis of big data. It refers to the process of
sorting big data sets, to analyse various patterns which help to solve business problems
through data analysis. Data Mining reduces the various set of big data scale by the
method of combining machine learning or statistics.
 Machine Learning: Machine learning is an another effective technique of big data
analysis as it highly engaged in artificial intelligence tools which helps the business in
analysis or interpret big data. Machine learning deals with computer algorithms to
produce assumptions which are based upon data.

 Statistics: For business statistics is also an effective technique for big data Analyses.
With the experiments and surveys big data technique help business in collecting,
organising and in interpretation of data in an effective and efficient manner (Mikalef and
Krogstie 2019).
 Data Integration: By joining the various sets of data integration techniques it helps
business to integrate or analyse the data from the various solution and sources if business
established data through one data source then this will give high effectiveness and
efficiency to the data in business.
Big Data Technologies:
 Analytical Technology: Analytical technology is an advance level big data technology.
The major analysis of big data or metrics performance in the business for the major
reason of making decisions are coming under this technology. This technology used to
analyse big data related to the decision of business. Some of the example where this
technology highly used like in forecasting whether, database of space mission, stock
marketing data.
 Operational Technology: This technology helps in maintain the daily basis activities.
This offers the raw data to consider or analyse the operations of the business, Daily bases
activities which are comes from social media platform or can be from any other specific
area Some areas where this technology highly used are trading online, data from social
networking sites (Hallikainen and Laukkanen 2020).
Benefits of big data technology in business:
 Enhance Efficiency: Big data technology improves the efficiency in business as it
collects or store large amount of client's data. After the collection of data this data
determine and analyse to find out useful scale of patterns hide behind the preferences,
behaviour, taste of the customer. Big data technology helps the companies to analyse the
market trends which allows the company to know about their competitors in the industry
for Example: If the company use data analytics technology they can effectively analyse
the current trends of market. Also it helps the company to regulate the day to day task
process.

 Optimize Cost: Big data technology helps in optimizing cost, because cost plays an
essential role in business. Big data technique provides cost advantage in business When it
comes to processing, analysing and storing large amount of data. With the help of these
techniques provides efficiency and cost saving ways for the operations of business. For
Example: In logistics industry the product cost goes half time higher than the exact cost
of shipping. Big data technology gives an effective way to minimize the return cost of
product by predicting the return on product.

CONCLUSION
From the above report it has been concluded that big-data plays an essential role in the
field of technology as it helps in solving the issues related to the data which is difficult to handle
in today's times. Big and small both types of companies are willing to adopt big data techniques
and technology to improve their overall business operations. Along with it helps to survive in
market for longer period of time. Business can easily improve their cost, expenses as well as
privacy and security in business. By using big data technology company get various benefits that
impact on organisation efficiency and it helps to manage their data in different manner.

REFERENCES
Books and Journals
Hariri, R.H and Bowers, K.M., 2019. Uncertainty in big data analytics: survey, opportunities,
and challenges. Journal of Big Data, 6(1), pp.1-16.
Hamilton, R.H. and Sodeman, W.A., 2020. The questions we ask: Opportunities and challenges
for using big data analytics to strategically manage human capital resources. Business
Horizons, 63(1), pp.85-95.
Zhang, Y., Huang, T. and Bompard, E.F., 2018. Big data analytics in smart grids: a
review. Energy informatics, 1(1), pp.1-24.
Ghani, N.A., Hamid, and Ahmed, E., 2019. Social media big data analytics: A
survey. Computers in Human Behavior, 101, pp.417-428.
Zhu, L., Yu, F.R., and Tang, T., 2018. Big data analytics in intelligent transportation systems: A
survey. IEEE Transactions on Intelligent Transportation Systems, 20(1), pp.383-398.
Mikalef, G. and Krogstie, J., 2019. Big data analytics and firm performance: Findings from a
mixed-method approach. Journal of Business Research, 98, pp.261-276.
Hallikainen, and Laukkanen, T., 2020. Fostering B2B sales with customer big data
analytics. Industrial Marketing Management, 86, pp.90-98.