At Gulf Air, an internally developed big data solution is helping the airline understand how passengers\u00a0feel about its products and services, as well as enhancing more customer loyalty by delivering offers and promotions. The solution \u2014 called Arabic Sentiment Analysis \u2014 is built on open source technologies and runs in the airline\u2019s private cloud. This cloud is using Red Hat products to achieve reliability, availability, and scalability in a virtualised environment that encompasses more than 200 servers and more than 100 different enterprise applications.<\/p>\n
Sentiment analysis for social media<\/strong><\/p>\n Gulf Air has developed a sentiment analysis solution based on big data technologies that is capable of addressing social media posts in both Arabic and English languages. Called Arabic Sentiment Analysis, the solution was developed entirely in-house by Gulf Air.<\/p>\n \u201cAs an airline, it is crucial to know what our customers are thinking. We want to know who is satisfied\u00a0with Gulf Air\u2019s service, who is not, if not then why, and what Gulf Air can do to improve its offering. Analysing social media can help us gain more insight into potential customer demands for everything from on-board services to new destinations, information which can be incorporated into decision-making to enhance the airline\u2019s offering,\u201d said Dr. Jassim Haji, Director of Information Technology, Gulf Air.<\/em><\/p>\n Arabic Sentiment Analysis is based on Cloudera\u2019s distribution of the open source Hadoop big data\u00a0framework, running across a cluster of servers based in Gulf Air\u2019s private cloud IT environment.\u00a0This, in turn, uses a number of Red Hat products, including Red Hat Enterprise Linux, Red Hat JBoss\u00a0Enterprise Application Platform, and Red Hat Storage. The private cloud encompasses 200 servers\u00a0running more than 100 core applications and holds more than 50 terabytes of data. The scalability\u00a0achieved using virtualisation meant there was plenty of capacity to host the big data solution.<\/p>\n The private cloud is based on a dedicated, state-of-the-art \u201cgreen\u201d data centre and has been in place\u00a0since 2012. During its planning, Gulf Air\u2019s IT team made the strategic decision to migrate all the\u00a0airline\u2019s UNIX platforms to Red Hat Enterprise Linux. Red Hat\u2019s technologies fully integrate with all\u00a0other major infrastructure components that Gulf Air uses, from companies such as EMC, Cisco, and\u00a0F5 Networks.<\/p>\n Today, Arabic Sentiment Analysis sits on this private cloud infrastructure and processes hundreds\u00a0of thousands of social media posts, providing sentiment results in minutes that indicate what passengers\u00a0are talking about and how they feel about particular routes, products, or services. The solution\u00a0also uses social media posts as the basis of wider analysis of the state of the market and actions\u00a0taken by Gulf Air competitors.<\/p>\n Increased competitive advantage<\/strong><\/p>\n Arabic Sentiment Analysis lets Gulf Air provide passengers with offers and promotions on a timely basis, often in response to competitor actions. Real-time reports, for example, alert Gulf Air marketing executives when a competing airline launches a particular promotion or offer involving a destination that Gulf Air flies to.<\/p>\n \u201cThe airline industry is very price-sensitive, and the majority of travellers look for the cheapest\u00a0fares available. During peak travel times like summer, quick action is crucial, because any delay\u00a0in responding to the competition could mean the loss of passengers and revenue. Such real-time\u00a0reports have helped Gulf Air to respond very quickly to its competitors,\u201d said Dr. Haji<\/em>. Using Arabic\u00a0Sentiment Analysis has meant improved time to market for new offers and promotions, as well as\u00a0improved sales cycles.<\/p>\n Big data made reliable<\/strong><\/p>\n Gulf Air has been able to tackle a reliability issue inherent to many big data implementations. Their big data solution is based in its Red Hat private cloud, it was easy for IT staff to create \u201cghost images\u201d of the master server, which can be deployed in minutes if the original master server fails.<\/p>\n Faster response times<\/strong><\/p>\n Social media monitoring and analysis, when performed manually, can be slow and resource-intensive,\u00a0but with Arabic Sentiment Analysis, it is \u201cautomatic, quick and efficient,\u201d says Dr. Haji. New posts and changes in social media trends are periodically captured and stored locally, and then transformed\u00a0into reports that make it easy for Gulf Air employees to act on their findings. This gives them a good, up-to-date view of any changes in sentiment, shifts in demand, or emerging market trends, enabling them to respond quickly.<\/p>\n The journey ahead<\/strong><\/p>\n Many big data projects come with a hefty bill for the companies concerned. At Gulf Air, however, Arabic\u00a0Sentiment Analysis has been delivered very cost-effectively, thanks in part to the company\u2019s enthusiasm\u00a0for open source solutions.<\/p>\n \u201cThe big data solution deployed is an open source one, which meant no special license fees to pay,\u00a0while the infrastructure where it runs is based on an existing open source-based private cloud\u00a0environment and virtual servers, which meant no hardware investment was required. Open source technologies have many other advantages,\u00a0including wide community\u00a0support and quick and frequent fixes and new releases,\u201d said Dr. Haji.<\/em><\/p>\n \t<\/p>\n","protected":false},"excerpt":{"rendered":" At Gulf Air, an internally developed big data solution is helping the airline understand how passengers\u00a0feel about its products and services, as well as enhancing more customer loyalty by delivering offers and promotions. The solution \u2014 called Arabic Sentiment Analysis \u2014 is built on open source technologies and runs in the airline\u2019s private cloud. This […]<\/p>\n","protected":false},"author":20,"featured_media":9361,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[34,331,809],"tags":[1492,2241,1494,2242,307,646,144,2243,50],"class_list":["post-9358","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-case-studies","category-cloud","category-more-news","tag-arabic-sentiment-analysis","tag-big-data-solutions","tag-gulf-air","tag-hadoop-big-data-framework","tag-open-source","tag-private-cloud","tag-red-hat","tag-sentiment-analysis","tag-virtualisation"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/posts\/9358","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/comments?post=9358"}],"version-history":[{"count":0,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/posts\/9358\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/media\/9361"}],"wp:attachment":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/media?parent=9358"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/categories?post=9358"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/tags?post=9358"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}