Information Systems and Big Data Analysis: Techniques and Challenges

This report provides a comprehensive overview of big data analysis within information systems, highlighting its characteristics, challenges, and techniques. It defines big data as high-volume, high-velocity, and high-variety data and discusses its value and veracity. The report identifies key challenges in big data analytics, including expensive maintenance, talent gaps, data security, uncertainty, and long system response times. Various techniques for analyzing big data, such as data mining, A/B testing, and machine learning, are explored. The report also examines how big data supports businesses by driving customer acquisition and retention, improving decision-making, and enabling automation. It concludes that while big data offers significant opportunities, organizations must address the associated challenges to leverage its full potential. Desklib provides access to similar solved assignments and resources for students.

Information system
and big data analysis

INTRODUCTION
The term big data is defined as that data that is generated in world wide at a unprecedented
rate. Big data is an aggregation of all the instruments and procedure which is related to the
utilization and managing set of the larger data. Concept of the big data was introduce out of
requirements of the understanding trends, pattern and preference in a vast database during the
interaction between people with each other. Concept of the information system is wide in
economy as companies are connect with the IT sector in order to get wide range of the solutions.
There is much use of the Internet on information system, internet is interrelated with the device
network to have a connectivity and data exchanges. With the help of information technology,
organization build a communication by creating administrating database. In this report there will a
discussion on the different characteristic of big data, issues arise and techniques of the big data.
Explain the characteristic of big data
Process of the big data is an advanced analysis which is very complex application as it
include some complicated element such as predictive model, algorithm theory and many more.
For companies, design of the big data analytics is very helpful as it help business to make data
driven decision in order to improve the business outcome. Organizations used the big data to
improve their operational activities so that they can provide a better service to their customers.
There are some characteristic of the big data which are mentioned below:
 Variety- It refers to various sources and their different natures to extract the data. In
previous time people uses the data base and spreadsheet to collect their essential data. But,
nowadays people use the latest technology such as PDF, photos, email and many more
thorough which company's essential data are stored safely.
 Value- It described as benefits of driven by data. Data are very reliable and valuable if to
analyse and processing. Big data is considered as more valuable after a successful analysis.
It make enable an organisation to enhance itself. An effective utilization of data help the
company to build a strong relationship with customers.

 Veracity- This term is associated with the trustworthy and reliability of data by having
numerous ways to the data translation that define accuracy of the data. In big data,
trustworthy is also considered along with the data quality.
 Volume- Process of big data include large number of the data which are related to the a
large amount of the data obtained form the multiple sources including social media,
networks, machine and many more.
 Velocity- It is knows as speed that is related to the generation of an information and data
processing. Flow of the data has very high speed fro different sources including social
media sites, application and many more.
Challenges of the big data analytics
The big data analytics challenges include finding of the best way so that the large amount
of data can be managed. It include the storing analysing an information in a multiple data store.
When dealing with the big data, there are various challenges which are mentioned below:
 Expensive maintenance- The is an ongoing investment is required to maintain the big
data system. Every business want to make a little investment. Therefore, if companies are
comfortable with the maintenance and infrastructure cost then it is considered a useful idea
to take a fresh look at organisational system and make sure that there is not overpaying
 Big talent gap- There are numerous expertise that are acquirable within this filed as big
data is a flourishing field. Big data is considered as very complex field, so people who is
able to understand intricate nature and complexity of such filed are far few and between. In
big data analytics, another main challenge is talent gap that exist within that industry.
 Security of data- Organisation faces the challenges of security of complex data as
companies shave large number of essential data and they are concerned with the analysing
or storing these information. If these data get stolen, then company may has to bear a
heavy loss.
 Uncertainty- Big data is expanding with a continuity, the business organisation innovating
latest technology very rapidly. So, it is a challenge for the business to analyse that what
technology they should adopt in order to perform better without any risk and issue.

 Long system response time- When examine data, then it take a long time even thou8gh
the input data is already available or report need now. Due to this delay companies face
cost pretty penny.
Techniques available for analysing the big data
In the process of data analytics, data's are examined to draw a conclusion related an
information through particular software and method. There are various techniques of the data
analytics. Some of these techniques are mentioned below:
 Data mining- Organisation undertake this process to examine the information to get
insight in their customer's behaviour. This tool is widely used by the business organisation
within big data analytics. Data mining combine ways for statistic and machine learning to
extract the pattern from large data set. Data scientist gather data and examine it. They
looks for discrepancies and the pattern to resolve the issues or problems.
 A/B learning- This technique provide ways to compare two different variants of a version
in order to identify a better performer within controlled environment. A successful A/B
technique provide advantages and large volume of the business to a company.
 Machine learning- This technique is very helpful as it facilitate a good understanding of
big data analysis by displaying large variety of the pattern and trends. This technique
provide benefits to accelerate the process of decision making by using algorithm. It
classify the upcoming information, convert data into a visualize form and identify the
pattern and trend.
How the big data support businesses?
The big data offer several new opportunities to the business organisations in their growth
and development. For instance, by using robotic machine, big data improve the intrinsic efficiency
of a business. A large data set's can be managed and analysed perfectly for the further process of
business related to the decision making. The big data also reveal some hidden opportunities about
which companies are not aware. Big data make enable to think with a new perspective and
discover essential information that can be used appropriately. It support the business in many
ways which are mentioned below:

 Drive the customer acquisition and retention- Customers are a valuable assets for a
business so the companies uses big data to observe the customer's related trends and
pattern. By gathering more data, company become able to identify more pattern and trends.
Latest technology help the business to collect more customer data and formed strategies to
develop the big data so that company can maintain a good customer base. Through
customer insight, company can fulfil the customer's requirements. For instance Coca- Cola
has managed has managed to strength their data strategy by creating digital Led loyalty
program.
 Better decision making- Organisation uses this tool to make an intelligent and effective
decision on the basis for information rather than assumption. To improve the
organisational decision making, a company need to access the data so that the user can
examine and enquiry the data to response the business's question. For instance, Walmart
gave a control to people so that they can access the data.
 Automation- Big data are useful to improve the organisational internal operation and
efficiency with the help of robotic process. Large amount of real time data are analysed for
the automation process of the decision making.

CONCLUSION
From the above report it is conclude that big data combine all instruments along with a
process that is relevant while managing set of large data. These data are stored stored by the
organisation as it help them in many ways such as understating of customer's behaviour and
effective decision making. Along with the advantages, company also face several challenges in the
analysis of big data. There is risk of data stolen as it may lead to misuse of essential information
that cause a big trouble for the company. Some effective techniques including data mining, A/B
technique and many more. The big data analytic support the business effectively as it reduce their
cost and expanses and promote the automation at workplace efficiently.

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