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TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE TYPE YOUR ANSWER HERE 6 A white paper by International Data Corporation (IDC) reports that the global data volume has grown exponentially from 4.4 zettabytes to 44 zettabytes between 2013 and 2020. It also predicts that the volume of data will reach 175 zettabytes by 2025. Zettabyte is a unit that is used to describe the amount of data, and 1 zettabyte equals 1021 bytes (that is, 1,000,000,000,000,000,000,000 bytes!). The world has officially entered zettabyte era and data is still being generated at a staggering speed. For example, in retail Walmart processes more than 1 million customer transactions every hour; in tech, Facebook users upload more than 350 million photos every day. With such an amount of data and the speed at which data is being generated, comes the desire to analyse and extract information from the datasets. Often the information that is extracted from a big dataset as a whole is much more useful than the collection of information extracted from small individual datasets. This desire gives rise to big data, which, as a field, studies the techniques that analyse and systematically extract information from datasets that are too large or complex to be processed by traditional data processing techniques. Big data has attracted much research in the recent years and has seen a wide range of applications across various sectors. For example, big data techniques have been used to analyse current or historical data to make predictions about future or other unknown events, which is particularly useful to facilitate decisionmaking in health care, crime, security and natural disaster management. Big data has also been used to reveal relationships and dependencies or infer laws embedded in large sets of data. Such information can 3 be very valuable and can inform business decision making. For instance, big data might reveal that customers who bought item A are significantly more likely to buy item B. This information would enable businesses to make more customised and personalised recommendations to their customers. SkyMall is one of the world’s largest online marketplaces with over 100 million active users globally and over 2 billion product listings on their platform. SkyMall's business model allows individuals or small business owners to open stores online and to sell products to customers worldwide. Online retail has had a phenomenal growth in the past decade - such a business model challenged the traditional offline retail industry, and many have chosen to move their businesses online for reduced labour cost, reduced operational overhead and much greater reachability to potential consumers. In 2019, SkyMall reported a transaction volume of 0.5 trillion dollar from their worldwide operation. SkyMall is a platform provider. While it does not sell their own products directly on the platform or generate profits from the sale proceedings, it charges online store owners a monthly subscription fee and charges a small percentage from their sale transactions. SkyMall has the following responsibilities: • it attracts consumers to their platforms through a number of marketing channels, e.g. email direct marketing and online advertisement through major online marketing agencies like Google and Facebook. • it plays a regulatory role in ensuring that the online marketplace complies with various local legislations, e.g. compliance with consumer laws in local jurisdiction, no illegal/copycat/counterfeit products are being sold on their platform and no fake/fraudulent advertisement in online stores. • it handles complaints of consumers against online store owners, or vice versa. • it provides order fulfillment service to online store owners, that is, SkyMall allows online store owners to store products in their fulfillment centre and it will take care of picking, packing, and shipping the orders. SkyMall is responsible for optimising the stock levels: too much being stocked means too much unnecessary storage cost; too little being stocked means frequent delays in dispatching and shipping orders. SkyMall has felt pressure from the heated global competition, especially competition from other online retail platforms that specialise in particular regions or countries. Those platforms do not have a global presence, but they understand their local markets and understand their consumers’ preferences and bahaviours much better than a platform like SkyMall which targets global consumer markets. The Chief Information Officer (CIO) of SkyMall decided to incorporate big data techniques in their global operations. She would like to investigate how SkyMall can leverage big data to facilitate decision makings in daily operations as well as to gain a competitive edge against other competitors. One staff proposed the following two solutions: • SkyMall may use their mobile app to track users' location. With the power of big data, SkyMall would be able to infer users' purchase behaviour and/or preference based on the places they have visited. For example, big data techniques would be able to discover statistically significant 4 patterns and relationships: people who visited place A are more likely to purchase item A than those who have not visited that place. Such information provides a cost-effective way to market particular products to people who need them the most. • SkyMall could collect large amount of data from its consumers, and many other businesses would be interested in this data. SkyMall can inform customers in the terms and conditions on the platform that the data (transactional data, product browse history, product review) will be shared with third parties. No one would actually read terms and conditions before they click “I agree”. A white paper by International Data Corporation (IDC) reports that the global data volume has grown exponentially from 4.4 zettabytes to 44 zettabytes between 2013 and 2020. It also predicts that the volume of data will reach 175 zettabytes by 2025. Zettabyte is a unit that is used to describe the amount of data, and 1 zettabyte equals 1021 bytes (that is, 1,000,000,000,000,000,000,000 bytes!). The world has officially entered zettabyte era and data is still being generated at a staggering speed. For example, in retail Walmart processes more than 1 million customer transactions every hour; in tech, Facebook users upload more than 350 million photos every day. With such an amount of data and the speed at which data is being generated, comes the desire to analyse and extract information from the datasets. Often the information that is extracted from a big dataset as a whole is much more useful than the collection of information extracted from small individual datasets. This desire gives rise to big data, which, as a field, studies the techniques that analyse and systematically extract information from datasets that are too large or complex to be processed by traditional data processing techniques. Big data has attracted much research in the recent years and has seen a wide range of applications across various sectors. For example, big data techniques have been used to analyse current or historical data to make predictions about future or other unknown events, which is particularly useful to facilitate decisionmaking in health care, crime, security and natural disaster management. Big data has also been used to reveal relationships and dependencies or infer laws embedded in large sets of data. Such information can 3 be very valuable and can inform business decision making. For instance, big data might reveal that customers who bought item A are significantly more likely to buy item B. This information would enable businesses to make more customised and personalised recommendations to their customers. SkyMall is one of the world’s largest online marketplaces with over 100 million active users globally and over 2 billion product listings on their platform. SkyMall's business model allows individuals or small business owners to open stores online and to sell products to customers worldwide. Online retail has had a phenomenal growth in the past decade - such a business model challenged the traditional offline retail industry, and many have chosen to move their businesses online for reduced labour cost, reduced operational overhead and much greater reachability to potential consumers. In 2019, SkyMall reported a transaction volume of 0.5 trillion dollar from their worldwide operation. SkyMall is a platform provider. While it does not sell their own products directly on the platform or generate profits from the sale proceedings, it charges online store owners a monthly subscription fee and charges a small percentage from their sale transactions. SkyMall has the following responsibilities: • it attracts consumers to their platforms through a number of marketing channels, e.g. email direct marketing and online advertisement through major online marketing agencies like Google and Facebook. • it plays a regulatory role in ensuring that the online marketplace complies with various local legislations, e.g. compliance with consumer laws in local jurisdiction, no illegal/copycat/counterfeit products are being sold on their platform and no fake/fraudulent advertisement in online stores. • it handles complaints of consumers against online store owners, or vice versa. • it provides order fulfillment service to online store owners, that is, SkyMall allows online store owners to store products in their fulfillment centre and it will take care of picking, packing, and shipping the orders. SkyMall is responsible for optimising the stock levels: too much being stocked means too much unnecessary storage cost; too little being stocked means frequent delays in dispatching and shipping orders. SkyMall has felt pressure from the heated global competition, especially competition from other online retail platforms that specialise in particular regions or countries. Those platforms do not have a global presence, but they understand their local markets and understand their consumers’ preferences and bahaviours much better than a platform like SkyMall which targets global consumer markets. The Chief Information Officer (CIO) of SkyMall decided to incorporate big data techniques in their global operations. She would like to investigate how SkyMall can leverage big data to facilitate decision makings in daily operations as well as to gain a competitive edge against other competitors. One staff proposed the following two solutions: • SkyMall may use their mobile app to track users' location. With the power of big data, SkyMall would be able to infer users' purchase behaviour and/or preference based on the places they have visited. For example, big data techniques would be able to discover statistically significant 4 patterns and relationships: people who visited place A are more likely to purchase item A than those who have not visited that place. Such information provides a cost-effective way to market particular products to people who need them the most. • SkyMall could collect large amount of data from its consumers, and many other businesses would be interested in this data. SkyMall can inform customers in the terms and conditions on the platform that the data (transactional data, product browse history, product review) will be shared with third parties. No one would actually read