Big Data In The Travel Industry and More

How To Make The Most Of ‘Big Data’ In The Travel Industry: “There is a ‘big data’ revolution underway in the travel and hospitality industry but travel companies need to be clear about the challenges. … Data analytics is an interesting prospect for the travel sector as so many data streams can be combined. … Business analytics pulls insights from vast databases commonly referred to as ‘big data’. To be successful and maximise the value of this, firms need to be very focused and disciplined.”
— As firms plan to take the plunge, here are some expert recommendations: “Focus on areas where an impact can be made … Understand how to engage with consumers more efficiently … Identify patterns that can lead to insights around consumer acquisition, retention and marketing.” (Hospitality Net) http://goo.gl/Q7dwU
 
“Business analytics should itself be adaptive and regularly refined by new data that users feed back into the system as that is the whole purpose of predictive modeling…” [Brenda] Dietrich explained that data analysis allows companies to extrapolate outcomes linearly and decide what appropriate action to take next. Those actions also generate new data, which should be fed back into the analytics model so it is continuously refined, improved, and accurate, she said. …This notion of constantly ‘learning from the data’ is a new and exciting development in the analytics space, because it means a company can see, as time progresses in reality, whether it is moving toward X or Y, and decide the next step it should take, she said.” (ZDNet) http://goo.gl/23kaW
 
“Why is data science relevant?” “Benjamin Franklin is alleged to have said in response to the questioning of the value of the first hot air balloons, ‘What is the value of a newborn baby?’ Actually, data science is probably a long way from the newborn baby stage, although it still has a long way to go before it achieves full maturity.” (Network Computing) http://goo.gl/QdvJ3
 
Dell Provides Schools and Universities with Predictive Analytics: Schools and universities are turning to Dell’s Education Data Management (EDM) solution, a decision support system, to help personalize student learning, increase retention and graduation rates while improving planning, management and reporting. The solution integrates student performance and operational data with predictive analytics to help educators monitor student progress and intervene when needed to improve success. It tracks each student’s data between schools and over multiple years to help parents and educators monitor student progress and respond to developmental needs or hone in on specific interests and aptitudes. (EON) http://goo.gl/hE3y1
 
The Hadoop bone’s connected to the SQL bone: “Microsoft has been working with Hortonworks to build a distribution of Hadoop for Windows Azure, its cloud platform, and for Windows Server.  Right now the service is available as a cloud service in a by-invitation beta that just entered its third release.  … Why would Microsoft be so bullish on technology that is open source, Java-based and largely Linux-facing in pedigree? Most likely it’s because Microsoft runs Bing. By some counts, Bing and Yahoo Search (which is Bing-powered) together have about 30% search market share and Turner announced in his keynote that Bing is now leading Google in search relevance. (ZDNet) http://goo.gl/e8k3N
 
Adding Second-Tier analysis To Harness Big Data: The real challenge with Big Data is in going from individual siloes of data analytics to a bigger picture that successfully and meaningfully puts those analytics into the full-enterprise context. It’s how we map these analytical islands to each other that ultimately provides the support we need for improved quality in our decisions. … It is important that business and operational metrics be aligned to improve decisions and help ensure business survivability.
— A useful second-tier analysis effectively describes key business functions or processes and business assets, and then correlates operational reports and metrics to them. For example, linking accounts receivable to technology assets to operational practices and metrics can help expose significant enterprise risk. (SC Magazine) http://goo.gl/mPXg7