Big Data Analysis and Techniques for Business Growth - Desklib

Information system and
big data analysis

Contents
INTRODUCTION...........................................................................................................................1
Big data and its characteristics.....................................................................................................1
Challenges of big data analytics and techniques to analyse big data...........................................3
Techniques of big data analysis...................................................................................................3
How big data technology supports business................................................................................4
CONCLUSION................................................................................................................................4
REFERENCES................................................................................................................................5

INTRODUCTION
A process in which complex and large information is analysed to discover data such as
customer preferences, unknown correlations, hidden patterns, market trends and other useful
information. In this analysis, the information is extracted and analysed from a large set of data.
Company use this process because it helps in formulating better business decisions by giving
valuable insights that are required to limit the risks within organisation (Aboelmaged and
Mouakket, 2020). In present report, big data and its characteristics will described. Challenges of
big data analytics will also be explained along with the techniques of analysing big data. Within
the portfolio, there is also a description of methods of how the technology of big data supports
business.
Big data and its characteristics
Big data is a large number of information sets and is a kind of advanced analytics that
includes complex applications with elements such as statistical algorithms, stream analytics, data
virtualisation and predictive models. Company use big data analysis because it helps in
formulating the decisions related to data-driven that provides assistance in improving business
outcomes. The benefits of implementing big data analysis is that it helps in developing new
opportunities regarding new revenues and makes marketing as well as business operations more
effective. This process also facilitates in maintaining the customer personalization and also helps
in gaining competitive advantage over its rivalries. Big data analysis assists business in
supporting and utilizing its information to search new opportunities so that business can run in a
smarter way. Through this way, the company will generate a large number of profits within the
business as well as makes its potential customers happy. Data mining, data storage, data
visualization and data analysis are all included in the analysis of big data.
Big data is categorised basically in three parts, namely, structured data, semi-structured
data and unstructured data. The type of data that can be stored, processed and recovered in a
particular format is defined as structured data. This kind of data can be readily and smoothly
accessed and stored with the help of a database using simple algorithms (Kim, and Cho, 2017).
Semi-structured data is a type of data in which both structured and unstructured data are
involved. This type of data has not been classified into a specific database. However, this data
consists of essential tags that separates linguistic or logical components within the existing data.
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