The Role of Data Mining in Examining Customer’s Online Buying Behaviour (Other (Not Listed) Sample)
THE ROLE OF DATA MINING IN EXAMINING CUSTOMER’S ONLINE BUYING BEHAVIOUR
BIG DATA AND DATA ANALYTIC
DATA MINING, TEXT MINING
REPORT - WORD COUNT: 5000 WORDS
INTRODUCTION, HEADINGS, REFERENCES, DIAGRAMS.
do not forget to provide evidence for everything.
25% of your overall grade.
THE ROLE OF DATA MINING IN EXAMINING CUSTOMER’S ONLINE BUYING BEHAVIOUR
By (Student’s Name)
City and State
Data Mining in Examining Customer’s Online Buying Behaviour
Today, big data has emerged as an important topic of study for a broad range of governments, businesses, and academic institutions throughout the globe (Jin et al. 2015). Big data has been highlighted in several unique topics in nature and science. Big data has penetrated or penetrated every industry. It becomes a crucial part of the manufacturing process. To increase output and entice customers, companies are turning to big data. Companies and individuals that can transform data into useful goods will have a bright future (Larson and Chang 2016). The future information economy will run on big data, described as the new fuel for this engine.
Despite the lack of a unified definition of big data, it may be distinguished from typical huge databases based on a broad consensus regarding its distinction and uniqueness (Zhang et al., 2017). Big data has been dubbed a “moving definition” by some scholars because of the way it evolves over time. It would be impossible to define a threshold for determining which data types and sizes qualify as “big data” if the volume of data kept growing. Using big data, the physical world, human civilisation, and cyberspace can all be interconnected and coordinated. According to Gupta et al. (2018), large amounts of data may be broken down into two categories: information about the physical environment and information about society as a whole. Sensors, experiments, and observation may be used to gather data from the physical world. Still, social networks, the Internet, and sources such as health and transportation can also be used to gather data from human society as a whole. According to the 5Vs (Volume Velocity Variety Veracity and Value), big data may be described by the following: The sheer number of data isn’t the major issue; it’s the variety and uncertainty that come with enormous data sets, as well as the need to react in real-time to new information (Sheng et al. 2017). From the standpoint of study, big data covers both structured and unstructured data, such as text, social media, online, multimedia, and sensor data. An organisation’s popularity is directly related to its social media marketing strategy. Although Indian businesses are making substantial use of social media as a marketing tool, the number of businesses doing so is both small and expanding (Shin et al. 2020).
Figure 1: Data volume from 2010 to 2025 in zettabytes (See, 2021).
Figure 1 above illustrates how big data growth from 2010 to 2025. According to See’s (2021) report, the amount of data has been increasing over the past decade and will reach a high of 175 Zettabytes by 2025.
Big Data Applications in Organisations
A great amount of data is being generated by businesses and people, which may be used to gain fresh insights and better one’s position in the competitive arena. Big data technologies have gained widespread recognition for improving efficiency and competence inside organisations (Jung, 2021). There were 5 Exabytes (EB) of data produced by humans in 2003, which is currently generated in days. According to a CISCO analysis, the number of devices and connections is expanding faster than the number of people and internet users globally. According to the research, while the population and internet users are expanding at 1% and 7%, the former is growing at 10% CAGR (Barnett et al., 2018). Large amounts of data may be used to help the second economy, which relies on processors, sensors, executors, and connections.
Machine learning and massively parallel processing are the two main approaches to pre-processing large amounts of data. Large amounts of data can be processed quickly and efficiently using machine learning algorithms (see figure 2) (Dahiya et al., 2021).
Figure 2: Data science to machine learning algorithms flow chart (Research Gate, 2022).
They classify huge data into distinct categories, analyse movement patterns, and forecast the future based on the past might benefit from this technique. Big data-driven machine learning solutions might aid in detecting fraud, the rapid release of new goods to the market, and an increase in our ability to compete (Dahiya et al., 2021). Other methods for handling large amounts of data include “massively parallel processing,” which includes database systems as well as “data mining grids” and “distributed databases.”
Understanding the Basics of Data Mining
Data mining or knowledge discovery of data (KDD) deals with unearthing the hidden knowledge and information which one may regard important from the huge assortment of data. Therefore, it can be described as pointing out patterns and trends in big datasets to reveal their relevant intuitions. Its origins are anchored on machine learning, artificial intelligence (AI), and classical statistics. According to Chen et al. (2019), data mining is an iterative process of probing knowledge in data. Data mining entails selecting the needed dataset and accumulating data from relevant sources, cleaning the data (pre-processing) to get rid of irrelevant data, changing the pre-processed data to an organised correct form (transformation), deriving the sequences of interest, and examination and documentation of the outcomes. Figure 3 below summarises the iterative process of examining knowledge in data.
Figure 3: Basic overview of data mining.
It is difficult for marketing decision-makers to make quick selections because of the many options accessible to clients and the severe
- Technology of De-extinction to Protect and Preserve SpeciesDescription: De-extinction is an essential aspect that will help in protecting and preservation of the species at the risk or dying or resurrection the dead animals. Genetic engineering, cloning and animal husbandry department will host an annual meeting that aims at creating awareness and on the former option...5 pages/≈1375 words| 4 Sources | APA | Technology | Other (Not Listed) |
- Management Information System Versus Knowledge Management SystemDescription: Arguably, knowledge is one of the most important things to manage. In the modern world, knowledge has become one of the most sought treasure both and personal and at organizational level. However, while people spend millions of money to seek knowledge, they hardly spend the time to find out what knowledge...12 pages/≈3300 words| 13 Sources | APA | Technology | Other (Not Listed) |
- Networking Technology Other (Not Listed) Research PaperDescription: To ensure the security of crucial data, encryption is essential. Algorithms employed in data encryptions are different and of unique edifices that need the user to have keys necessary to decrypt the data. The symmetric session key allows the encryptor to set a key that matches...7 pages/≈1925 words| No Sources | APA | Technology | Other (Not Listed) |