Information Systems and Big Data Analysis: History and Support

This essay provides an overview of big data, tracing its history and defining its key characteristics such as volume, variety, and velocity. It discusses how big data technologies support businesses by enhancing productivity and improving financial evaluations. The essay also addresses the challenges of big data analytics, including the need for skilled professionals and a proper understanding of data handling. Furthermore, it highlights techniques currently available for analyzing big data, such as A/B testing and natural language processing. The document concludes by referencing relevant research in enterprise information systems and the application of IoT, big data, and artificial intelligence in various industries.

History of Big Data:
The term big data denotes a large, massive and complex to
manage volumes and size of data. It has different forms
such as structured, semi-structured and unstructured data
that deluge the organisations on regular basis. These data
are important for businesses as it helps in making business
choices better.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data can be understood as the massive and diverse combination
of data that grow at fast speed rates. It involves the volume of data,
speed or velocity at which data is developed and assembled and the
scope or variety of the data. These data often comes from data
mining and received in various formats. Jet engines, social media
challenges and many more are few examples of big data.
Characteristics of Big data
Volume- It associates with the size of data. The data can
be considered as big data or not is relied on its size.
Variety- It relates with the type of data such as
structure, semi-structured and unstructured.
Traditionally, database or spreadsheets were used by
most of the applications.
The challenges of big data analytics
• Organisations requires experts or professionals to use
such modern technologies and massive data tools. This
may cover data analysts, data experts, data engineers
who can use the tools properly.
• Companies may face the challenge of improper
understanding of big data. Therefore, employees might
not acknowledge the facts about data using, storing or
processing.
How Big Data technology could support
business & Examples
• Through big data, companies increases their
productivity level. Tools such as Google Earth,
Google Maps or social media.
• Big data helps to enhance pricing of the business. It
helps to evaluate finances and indulges clear picture
of the position of the business.
Techniques that are currently available to analysis big
data
• A/B testing: It contains comparing a control group with
variety of test groups with an aim to determine what changes
or alterations will improve the particular factor.
• Natural language processing: It is recognized as the
subspecialty of artificial intelligence, computer science and
few more. It utilises algorithms to acknowledge the human
languages.
REFERNCES
• Singh, N., 2019. Big data technology:
developments in current research and emerging
landscape. Enterprise Information Systems, 13(6),
pp.801-831.
• Misra, N.N. and et.al., 2020. IoT, big data and
artificial intelligence in agriculture and food
industry. IEEE Internet of Things Journal.