Information Systems and Big Data Analysis: Economic Support

This report provides an overview of big data analysis within the context of information systems, exploring its characteristics, history, and applications. It defines big data as the analysis and extraction of information for predictive and user-analytical behavior, highlighting key characteristics such as volume, velocity, variety, veracity, and value. The report discusses how big data technology supports the economy by offering new business opportunities and improving customer interactions. It addresses challenges in big data analytics, including the lack of understanding of complex data and the integration of data from different sources, and it outlines various data management techniques like machine learning, statistics, and A/B testing. The report concludes that big data combines all necessary tools and processes for managing large datasets, improving decision-making, driving customer acquisition and retention, and enhancing overall business operations.

History on big Data
The big data analysis is process of examining large and
complex data which is used for disclosing the data such as
correlation customer preferences, hidden patters and market
trends. From the large set of data this tool is used for analyzing
and extracting information which helps company in making
better decision and valuable insights is offered that reduces
organization risk. The concept of information system is wide in
the economy as organization are interrelated with IT sector that
provides wide range of solutions.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
This process is a type of advanced analysis that includes complex
applications along with components such as statistical algorithms,
predictive models, and so on. The design of big data analytics is to help a
company make data-driven decisions that will improve business results.
Big data is defined as the analysis and extraction of information that can
also be used for predictive and user-analytical behavior.
Characteristics of Big data
The characteristics of big data are as follows-
• Volume
• Velocity
• Variety
• Veracity
• Value-
The challenges of big data analytics
Big data challenges involve finding the best way to manage
large amounts of data, including storing and analysing
information in multiple data stores. There are several major
challenges when dealing with big data. Some of these
challenges are explained as follows
• Lack of understanding of complex data-
• Integration of data from different sources-
• Securing data-
References
• Pramanik and et.al, 2017. Big data analytics for security and
criminal investigations. Wiley interdisciplinary reviews: data
mining and knowledge discovery. 7(4). p.e1208.
How Big Data technology could support
business & Examples
Big data technology offers new opportunities for business
growth from the internal view to the interactions of customers
or users who are at the front. With the help of robot-controlled
process automation, big data improves intrinsic efficiency and
business operations. Large amounts of data can be perfectly
analyzed and further developed in business processes for
automated decision-making.
• Better Decision Making
• Drive Customer Acquisition and Retention
Techniques that are currently available to analysis big data
Organizations use a variety of data management techniques and need
more insight into speed, scope, and depth. There are several techniques
for analyzing big data, which are mentioned below:
• Machine learning:
• Statistics:
• A/B Testing-
Conclusion
It is being concluded, big data combine all tools along with process
which is relevant while using and managing data sets of large