Report on Big Data Analysis: Techniques, Challenges, and Applications

This report provides a comprehensive overview of big data analysis, encompassing its definition, the techniques employed, and the challenges faced. It begins by defining big data as the collection, management, and storage of large datasets for achieving organizational goals. The report then explores various techniques such as classification tree analysis, association rule learning, machine learning, and Monte Carlo simulation, illustrating how these tools support business objectives. It also delves into the challenges associated with big data, including a lack of technical knowledge, the selection of appropriate tools, data growth, data security, and data quality issues. Furthermore, the report highlights the characteristics of big data, including veracity, variety, value, velocity, volume, and variability. In conclusion, the report underscores the importance of big data for informed decision-making and organizational growth. It emphasizes the need for effective data management and the strategic use of big data to optimize business operations.

History on big Data
Big data is a concept of collecting, managing as well as storing large data and
information of an organization effectively to meet the desired goals on time.
Nowadays almost all big firms used and Implement multiple methods and software
to manage and record their big data (Zhao and Guo, 2018).
Information Systems and Big Data Analysis
Techniques that are currently available
to analysis big data
Classification tree analyses- It refers to the technique where managers determine that which
data or document is belong to which category.
Association rule learning- This technique help the manager to evaluate the correlations
among independent data as well as dependent data.
Machine learning- This technique is related with updated and advance software which is
used by big companies to manage their vast data.
Monte Carlo simulation- This technique and tool used by management to make models or
strategy for decision making for desired result and achievement of goals effectively.
How Big Data technology could
support business & Examples
Technologies of big data can support any organization to meet their goals and objectives
for future growth. In recent times all most all businesses use advance and updated
software like cloud computing, cloud storage for storing their big data in systematic
manner.
. For example, In Unilever, management use updated software and technologies for
maintaining and recording their big data effectively.
The challenges of big data analytics
Lack of technical knowledge –Collecting and recording the data needs technical
skills which is challenging for a manager to develop in less time.
Confusion about the selection of right tool for big data- There are many
techniques and tools which is used by manager to manage big data.
Data growth challenges- This is related to managing big data year to year as it
increases every year which create difficulties for management to keep it for long
time.
Securing data- It is the biggest challenge for company to manage their big data as
well as keep it safe or secure from cybercrime. Keeping big data into various
software and internet sources will leads to increase the possibilities of data hacking
and theft by hackers of another company
Fixing and finding data quality issues – Management of huge data can be
challenging for an organization if the quality of data is poor that means the data that
is recorded and saved by managers are collected incomplete and form wrong source. References
Chen, P.T., Lin, C.L. and Wu, W.N., 2020. Big data management in healthcare: Adoption
challenges and implications. International Journal of Information Management. 53.
p.102078.
Lin, H.Y. and Yang, S.Y., 2019. A cloud-based energy data mining information agent
system based on big data analysis technology. Microelectronics Reliability. 97. pp.66-78.
Conclusion.
As per above presented information, it has been concluded that recording and managing
big data is important for an organization in order to make effective decisions for future
growth and development as well as operate business operations in systematic manner.
Characteristics of Big data
The various characteristics of big data that are shown below-
Veracity- It refers to the accurateness and truthfulness of the big data. The organization are
needed to collect and record actual data as well as avoid to gather false and hypothetical data
(Lv and Singh, 2021).
Variety- It refers to the different types data for all the functions that are needed to collect by
an organization
Value- It has been termed as importance and significance of data. Organizations are needed
collect and record those data only which is beneficial for them to increase their profitability
and productivity.
Velocity- It means the speed and time at which organization collect, manage and store data
for the use of their business operations
Volume- It means the size and amount of big data that is determine and collect by an
organization
Variability- It refers to the changing nature of big data and information.