Information Systems: Big Data Analysis, Challenges, and Performance

This report provides an overview of big data analysis, highlighting its characteristics, challenges, and solutions. It discusses the five key characteristics of big data: volume, variety, veracity, value, and velocity, emphasizing their role in effective business decision-making. The report identifies challenges such as a lack of understanding of massive data, data growth issues, and the integration of data from diverse sources. It suggests solutions like employee training programs, the use of modern technologies such as compression and deduplication, and tools like Hadoop and NoSQL databases. The report further explores how big data technology can improve business performance through better-informed decisions, supply chain improvements, cost savings, and enhanced organizational productivity. It concludes by emphasizing the importance of effective big data management for companies to improve their overall business operations and maintain a competitive advantage.

Information Systems and Big data Analysis
INTRODUCTION
Big data that is big in size and volume plays a vital role nowadays as it makes companies able in talking
better decision and performing all functions in an effective manner (Oussous and et.al., 2018). This present study
is going to discuss all main 5 characteristics of big data such as: velocity, volume and others. It will further
discuss some challenges that are associated with big data analysis and management. It will also show some
effective techniques that companies might use for solving all problems that they face while managing and
analysing big data. Along with this, it will show ways in which companies can make use of big data in order to
improve business performance and productivity as well.
Importance of big data technology in improving business performance
There are number of advantages that companies can take by making use of big data technology such
as: better informed decision, improvement of supply chain, cost saving and improved organisational
performance. In addition, it can also be said that big data technology help companies to the great extent as it
generates valuable insights and companies make use of analysed big data in order to refine marketing
campaigns and techniques. Companies use it in machine learning projects in order to train machines and for
predicting modelling (Dubey and et.al., 2019). Some techniques that can be used for managing big data
include: MongoDB, Apache Cassandra, Qlik view, Tableau and others. Companies like Google, Twitter and
Facebook also make use of these technologies and manage big data,. It helps them out in making better
decision and improving performance.
Big data technology is an open source NoSQL that is beneficial for storing and managing data.
Companies find easier in identifying new opportunities and by taking advantages of new opportunities, they
take competitive advantages. It in turns lead smarter business moves and efficient operations. Some other
advantages of big data technologies include:
Improving productivity: when employees perform their functions with anslysed big data, then they
are more likely to improve their performance by decreasing errors and mistakes. It boosts their confidence
and they help company in increasing customers retention rate that is vital for improved image of company.
Companies like face book and Google are successful examples of this that has made use of big data
management technologies and now they are known as the market leader.
Challenges of big data analysis and
Big data and its characteristics
As with the name itself, it can be said that big data refers data that contains greater variety or have complex data set. Such data is
voluminous that cannot be managed with traditional data processing software. In other words, it can be said that it refers a field that treats
ways of analysing and extracting information in order to make decision. There are number of ways in which big data can help companies in
improving their business performance. Some characteristics of big data include:
Volume: It is one of the main characteristic of big data as it is related to an enormous size (Sun, Strang and Li, 2018). It can be
generated from number of sources such as: machines, social media platforms, networks, human interaction and business processes. Facebook
is one of the great examples that generates around a billion messages and around 350 million posts.
Variety: Big data can be generated in number of varieties as it may be structured, unstructured and semi-structured. Such data
were used to collect from sheets and databases but now it may be collected in the form of audios, Emails, PDFs, photos and others. Structured
data is being stored in relational database management system and semi structured is being stored in table format.
Veracity: It shows the extent of reliability of data. Veracity is one of the best process by which data are being managed in an
effective manner. It helps in improving business’ performance and development.
Value: It is one of the other main characteristic that makes businesses able in improving their operations and making decision. It is
not about data that businesses store as it is valuable data that they store and make use.
Velocity: This characteristic creates the speed by which data is being created in real time. In other words, it can be said that it is
related to rate of change, data set speed and activity bursts (Hasanin and et.al., 2019).
On the basis of above characteristics, it can be said that by focusing on all these, businesses can accomplish their goals by
managing big data.
CONCLUSION
It has been summarised from the above study that big data plays a vital role as it can make companies able in making decision as well
as improving overall performance of business. It has discussed some problems that corporations or employees face while managing and
storing bid data due to lack of knowledge and others. It has further discussed some strategies as well as software that can be used by
companies for solving all these problems. This study has shown some ways in which companies can improve its overall business operations
by making use of big data and managing data in an effective manner.
REFERENCES
Oussous, A. and et.al., 2018. Big Data technologies: A survey. Journal of King Saud University-
Computer and Information Sciences. 30(4). pp.431-448.
Hasanin, T. and et.al., 2019. Examining characteristics of predictive models with imbalanced big
data. Journal of Big Data, 6(1), pp.1-21.
.
Managing big data is not an easy task as there are number of problems, associated with big
data. Employees face problems in managing big data because of some reasons such as:
Lack of proper understanding of massive data: Employees have few knowledge regarding
big data, was of managing, storing and processing. Only data professionals know what is happening and
how to manage big data and due to lack of knowledge and understanding, it becomes difficult for
employees to deal with big data and it may affect overall performance of business.
For solving this problem, companies need to encourage their employees for participating in big
data workshops and seminars. Along with these, they can participate in military training programs that
companies should arrange for all workers who deal with big data. It can increase knowledge and
understanding of employees regarding big data management (Knüsel and et.al., 2019).
Data growth issues: It is other main problem as the quantity of knowledge being stored in data
centres as well as database of companies is increasingly rapidly. Data sets grow at rapid rate and with
time, it becomes difficult to manage. Those data that is unstructured and comes from text files, audio
and videos, become very difficult to manage and understand.
This problem can also be solved out by making use of modern technologies such as
compression and deduplication. Compression is one of the best ways of decreasing size of files or big
data and by doing so, employees can understand big data in an effective manner. There are number of
techniques and tools that are also being use now days in order to solve all these problems such as:
Hadoop and noSQL.
Integration of data from a spread of sources: In corporations and big companies, big data comes from
number of sources such as: customer logs, social media pages, E-mails and reports that are created by
employees. Employees find difficulties in combining data, gathered from all these sources. Data