Information Systems and Big Data Analysis: History and Challenges

This essay provides an overview of big data analysis, tracing its history from the early 1990s to its formal definition in the mid-2000s, highlighting John R. Mashey and Roger Mougalas as key figures. It defines big data by its characteristics: volume, variety, and velocity, which drive its demand in modern businesses. The essay outlines the challenges organizations face when implementing big data analytics, including a lack of professional knowledge, difficulty understanding massive datasets, data growth issues, confusion in tool selection, and data security concerns. It also explores various big data technologies and techniques such as Hive, Cloud, Spark, SQL, data fusion, data mining, machine learning, and A/B testing, which support businesses in data management, customer engagement, and data privacy. The document emphasizes the importance of these tools in gaining a competitive advantage in the current technological landscape, with this student contributed essay available on Desklib.

History on big Data
Big data is defined as the field which treats analysing,
extracting as well as deal with different set of data which are
complex and large in volume. In current competitive
technological world, big data is the tool which helps business
to manage their data in efficient manner. Big data has been
used since early 1990 and its most people credit John R.
Mashey. Although in 2005 Roger Mougalas from O'Reilly
media coined the term of big date for first time (Feng, 2019).
As big data is defined as the large set of data which is quite
impossible to manage as well as process using traditional
business intelligence tool.
Information Systems and Big Data Analysis
What is big Data
Big data is the collection of different types of data which are huge in volume as
well as growing with exponentially with specific period of time. It is considered
as the data in large size as well as complexity that can not be store and process by
the traditional management tool in efficient manner. In current competitive and
advanced technological world, big data is the effective tool and technique which
helps business to store and manage information and data of business to run it in
efficient manner and gain competitive advantages than other competitors. In
business different types of Big Data technologies are implemented by the
organisation such as Hive, Cloud and Spark, SQL and various other (Chang,
2018). It includes assessment of different factors which are related to data storage
and management which is important for the growth, development and
synchronization of business data.
Characteristics of Big data
Big Data consist various characteristics such as Volume,
Variety and Velocity. These characteristic enhance the
demand of Big Data tool in business because it helps
business to store, access and manage data in efficient as
well as effective manner which is important for business
to attain business goals and objectives in well-defined
manner. Some characteristic of Big Data are mentioned
below:
Variety
Velocity
Volume of data
Visualisation
The challenges of big data analytics
In current business environment, organisation uses the big data
tool that help business to store and manage their data in systematic
way that help business to take decisions. Implementation of big
data technique facilitates business to attain objective if growth and
success in competitive business environment. It is necessary for
organisation to project business confidential data from external
impacts in order to maintain its accuracy and efficiency. Business
faces various problems or challenges regarding big data analytics
which are mentioned below:
• Lack of professional knowledge:
• Lack of understanding regarding massive data:
• Data growth issues:
• Confusion in selecting big data tool
• Securing data
References
Chang, V., 2018. A proposed
social network analysis
platform for big data
analytics. Technological
Forecasting and Social
Change, 130, pp.57-68.
Feng, P., 2019, January. Big
data analysis of E-commerce
based on the internet of
things. In 2019 International
Conference on Intelligent
Transportation, Big Data &
Smart City (ICITBS) (pp.
345-347). IEEE.
How Big Data
technology could
support business &
Examples
• Management of Data
• Customer engagement
• Privacy of data
Techniques that are currently available to analysis big
data
There are various tools and techniques are used by the organisation to
analyse business large amount of data and manage them in efficient
manner to make decisions properly. These techniques are mentioned
below:
• Data Fusion and data integration
• Data mining
• Machine learning
• A/B Testing