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Ep. 13: All the Data That's Fit to Analyze
As the CTO of LodgIQ, Somnath Banerjee is bringing dynamic data science and machine learning to an industry that understands the importance of data to their business, but often uses manual practices to collect and analyze this information - the hospitality industry.
Many of the factors that go into determining a hotel room rate - whether there's a major event nearby, flight costs, weather conditions, what competitors are charging - are constantly in flux. It's impossible to keep up through manual rate shopping and following static competitor intelligence reports.
In this episode of The New Builders, Somnath explains how LodgIQ applies data science and machine learning to enable more intelligent revenue management (6:55), the types of data that have the most influence on room rates (8:17), the role of Apache® Spark™ and Python in the LodgIQ platform (11:05), why LodgIQ built its data layer using a relational database and a MongoDB NoSQL database (13:08), how reviews on Yelp can predict whether a guest will stay again (15:44), and how elastic computing enables hotels of any size to deploy machine learning (21:52).
The New Builders podcast listeners can obtain special discounts for the upcoming CloudNativeDay (Toronto, Aug. 25) and CloudNativeCon (Seattle, Nov. 8-9) events:
- For a discounted CloudNativeDay pass, register here with code CND16IBMDW.
- For a discounted CloudNativeCon pass, register here with code CNC16IBMDW.
You can find new episodes of The New Builders on developerWorks TV and SoundCloud. Find out more about IBM Cloud Data Services at IBM.biz/forbuilders. Contact hosts Doug Flora and Jim Young on Twitter (@DSFlora, @JW_Young) or email ([email protected], [email protected]).
The show’s music is provided by School for Robots. Check them out at schoolforrobots.bandcamp.com!
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By IBM developerWorks TVAs the CTO of LodgIQ, Somnath Banerjee is bringing dynamic data science and machine learning to an industry that understands the importance of data to their business, but often uses manual practices to collect and analyze this information - the hospitality industry.
Many of the factors that go into determining a hotel room rate - whether there's a major event nearby, flight costs, weather conditions, what competitors are charging - are constantly in flux. It's impossible to keep up through manual rate shopping and following static competitor intelligence reports.
In this episode of The New Builders, Somnath explains how LodgIQ applies data science and machine learning to enable more intelligent revenue management (6:55), the types of data that have the most influence on room rates (8:17), the role of Apache® Spark™ and Python in the LodgIQ platform (11:05), why LodgIQ built its data layer using a relational database and a MongoDB NoSQL database (13:08), how reviews on Yelp can predict whether a guest will stay again (15:44), and how elastic computing enables hotels of any size to deploy machine learning (21:52).
The New Builders podcast listeners can obtain special discounts for the upcoming CloudNativeDay (Toronto, Aug. 25) and CloudNativeCon (Seattle, Nov. 8-9) events:
- For a discounted CloudNativeDay pass, register here with code CND16IBMDW.
- For a discounted CloudNativeCon pass, register here with code CNC16IBMDW.
You can find new episodes of The New Builders on developerWorks TV and SoundCloud. Find out more about IBM Cloud Data Services at IBM.biz/forbuilders. Contact hosts Doug Flora and Jim Young on Twitter (@DSFlora, @JW_Young) or email ([email protected], [email protected]).
The show’s music is provided by School for Robots. Check them out at schoolforrobots.bandcamp.com!