In this contributed article, Ritesh Mehta, Senior Technical Account Manager for TatvaSoft Australia, discusses the impact big data is having on the global travel industry and offers 5 action points for industry players to adopt in order to capitalize on big data. By 2022, the global travel industry is expected to grow to ten percent of Global GDP or a yearly revenue of around $10 trillion. Travel is a massive industry that could become much more efficient when big data is completely implemented in each and every aspect of travel.
Big Data is Transforming the Travel Industry
June 30, 2017 by
In this contributed article, tech writer Rick Delgado, examines how the travel industry includes a wide range of businesses, such as rental car companies, hotels, airlines, tour operators, cruise lines and more. Each of these companies must find a way to improve the overall customer experience and to meet the unique needs of each customer, and big data assists with this process.
Unisys Survey Finds Airports’ Investment in Analytics Technology Set to Soar as Digital Transformation Needs Take Flight
December 29, 2016 by
New research from Unisys Corporation (NYSE: UIS) reveals that airports expect to fully embrace more advanced analytics solutions in the coming years, with potential applications for use across several key areas within the airport ecosystem. Unisys conducted the survey of 29 airport executives and industry professionals at the Airports Council International – North America Annual Conference and General Assembly held in Montreal, September 25-28, 2016.
Detecting and Mitigating Fraud at Scale
August 7, 2016 by
The presentation below by Eric Levine, Engineering Manager at Airbnb shows how Airbnb’s Trust and Safety team has built machine learning infrastructure from the ground up to catch and defuse fraudsters on the platform.
How Hotels Are Now Benefiting From Big Data
August 5, 2016 by
In this contributed article by Rick Delgado, the hospitality industry is examined in terms of how it can benefit from big data technologies.
Lexalytics® Launches New Airlines Industry Pack to Help Improve Customer Satisfaction
December 15, 2015 by
Lexalytics®, a leader in cloud and on-prem text analytics solutions, announced the Airlines Industry Pack, a version of its text analytics software honed to meet the specific needs of customer experience management and social media marketing professionals working in the airlines industry.
Rail Europe 4A Chooses TIBCO Jaspersoft to Centralize Reporting and Analytics Needs
October 21, 2014 by
TIBCO Software Inc. (NASDAQ: TIBX) today announced that it has been chosen by Rail Europe 4A (RE4A), a worldwide leader in the distribution of European rail products, to provide centralized and reliable data analytics and automated reporting capabilities.
Enterprise Grade Lustre in the Clouds
October 21, 2014 by
With the release of Intel® Cloud Edition for Lustre software in collaboration with key cloud infrastructure providers like Amazon Web Services (AWS), commercial customers have an ideal opportunity to employ a production-ready version of Lustre—optimized for business HPDA—in a pay-as-you-go cloud environment.
Ask a Data Scientist: Recommender Systems
October 1, 2014 by
Welcome to the first article in a weekly series called “Ask a Data Scientist.” Once a week until you’ll see reader submitted questions answered by a practicing data scientist. Think of this new insideAI News feature as a valuable resource for you to get up to speed in this flourishing area of technology. If you have a big data question you’d like answered, please just enter a comment below, or send me an e-mail.
insideAI News Guide to Big Data Solutions in the Cloud
September 23, 2014 by
For a long time, the industry’s biggest technical challenge was squeezing as many compute cycles as possible out of silicon chips so they could get on with solving the really important, and often gigantic problems in science and engineering faster than was ever thought possible. Now, by clustering computers to work together on problems, scientists are free to consider even larger and more complex real-world problems to compute, and data to analyze.
