Elaborate the Characteristics of the Big Data using E-Commerce Data
Nowadays, E-Commerce data is growing speedily and is treated as a valuable asset (Monica, 2014). Shopee, one of the E-Commerce firm which founded in Singapore has more than 7 million active sellers and more than 200 million downloads of its app at 30th June 2019 (Ong, 2019). The growing of active sellers and Shopee app users which help in generating big data. Hence, the characteristics of big data in Shopee business will continue to be discussed in the following paragraphs.
Shopee has variety of data which refer to the different kinds of data that are formed and stored in the database (B.M, 2018).The variety of data normally divided into two different categories such as structured data and unstructured data. For structured data, Shopee business generated a lot of data in the form of text such as sellers and users’ personal data, customer reviews, product details and so on. While as for unstructured data, it is generated in the form of video and images of selling products (B.M, 2018).
The volume refers to the size or amount of data (B.M, 2018) and Shopee has huge volume of data. This is due to the Shopee has a lot of texts, videos and images data from 7 million active sellers and more than 700 million app users which have highlighted in the previous paragraph. Basically, a text file size is about few kilobytes, whereas, a JPEG image file is in range of few hundred kilobytes to few megabytes. Lastly, a three to four minutes of high definition video file is roughly one hundred megabytes. Assuming 700 million app users have updated their personal profiles, the data size of personal profiles itself can roughly achieve almost 1 Terabytes (700 million users multiply with estimated text file size), it has not yet included other data such as retail data, product consumption and etc.
The velocity means the speed at which the data gets generated and streamlined (B.M, 2018). For instances, the gross orders of Shopee has surged from 127.8 million in second quarter of 2018 to 246.3 million in the second quarter of 2019 (Saieed, 2019). It grows 92.7% compared to a year ago, this also help in growing the data such as retail transaction data, shipping data, customer profiles, product consumption and customer reviews with high velocity.
Next, the characteristics of big data in Shopee business is veracity. The veracity is about accuracy and reliability of data (B.M, 2018). The data in Shopee such as retail transaction data, shipping data, customer profiles, product data and seller profiles are accurate data. For instance, after customers have placed order and made payment to any of products in the Shopee, the customer profiles such as bank account details shall be accurate to ensure the transaction can be proceeded successfully. Therefore, shipping data of customers play important roles to make sure that the bought items can delivery according to the accurate address of customers. But if the product owners out of their house, the contact number of product owners are important to ensure shipper able to contact product owners to determine the second delivery date and time. Without veracity data, the whole retail process cannot be done successfully.
According to Cheh (2019), the recommendations for buyers have implemented in Shopee with help by Artificial Intelligence technology and data from customers’ past browsing and purchasing patterns. These big data in Shopee have created business value which help in recommending relevant products to respective customers through Shopee’s Feed and Daily Discover features (B.M, 2018). Besides, these big data from Shopee also help Shopee’s brand partners to spot customer behavior, which in turn help in seller’s inventory management especially during major Shopee campaign such as annual double eleven or double twelve event. The value which derives from Shopee data can help to understand the customer and gain business insight (Cheh, 2019).
The characteristics of big data have included variability by Gartner in 2012 (Gandomi & Haider, 2015). The variability is different from variety of big data characteristics in the first place. Variability means the understanding and interpreting of data is constantly changing (Impact, 2019). For instance, when Shopee customers review on their bought items with the following examples:
· Great product quality.
· Greatly disappointed with the product quality
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· The shipping duration is amazingly fast. Great! It took 4 weeks from Kuala Lumpur to Selangor.
Based on the examples, the understanding and interpreting of these customers review might be changing constantly from positive to negative and back to positive review.
Visualization is presenting large amounts of complicated data such as dozens of variables and parameters in a nice manner which is readable and accessible by Shopee customers and sellers (Impact, 2019). The product data are well presentable in Shopee as it can help customer to grasp huge amount of data easily. For example, when accessing product in Shopee App, the product prices are highlighted in red colour thus customers can easily find this important parameter. Therefore, followed with product details, product ratings and buyer reviews which help customers to take wise decisions and can help in increasing Shopee sales.
Reference:
Free Learning Points. (2019). Big Data Characteristics in Big Data Management Course. http://www.freelearningpoints.com/ex/big-data-management-eng-part-1
Gandomi A., Haider, M. (2015). Beyond the Hype: Big Data Concepts, Methods, and Analytics. International Journal of Information Management Volume 35, Issue 2, April 2015, Pages 137–144
B.M., A. (2018). Big Data Technologies For E-Business– Future Opportunities, Challenges Ahead and Growing Trends. International Journal of Advanced Research in Computer Science, 9(2), 328–332. doi: 10.26483/ijarcs.v9i2.5704
Goel, H., and Rao, T., Venkat, Narayana. (2019 ). Data Visualization in E-Commerce an Indispensable Implementation in Real World Business Scenario. International Journal of Scientific and Technology Research.
Free Learning Points. (2019). Principle in Data Science. http://www.freelearningpoints.com/ex/principle-in-data-science-eng-part-1
Free Learning Points. (2019). Data Mining. http://www.freelearningpoints.com/ex/data-mining-eng-part-1
