Data helps optimize major airport
Company Size
1,000+
Region
- America
Country
- Canada
Product
- Qlik
- Snowflake
Tech Stack
- Data Analytics
- Oracle
- SQL Server
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Transportation
Applicable Functions
- Logistics & Transportation
Use Cases
- Predictive Maintenance
- Real-Time Location System (RTLS)
Services
- Data Science Services
- System Integration
About The Customer
The customer in this case study is Vancouver International Airport (YVR), located in Vancouver, Canada. YVR is one of the major airports in Canada and serves as a significant hub for trans-Pacific flights. The airport is constantly seeking ways to improve its operations and passenger experience. One of the key challenges for YVR is to optimize the minimum connection time for passengers, which requires a clear understanding of how passengers, bags, and planes move through the airport. To achieve this, YVR needed a solution that could provide near real-time data analytics.
The Challenge
Vancouver International Airport (YVR) is striving to become the preferred TransPacific hub for passengers traveling between Asia and the Americas. To achieve this, YVR needed near real-time data analytics to gain a clear understanding of how passengers, bags, and planes move through the airport. This data would enable YVR to optimize its minimum connection time and enhance the passenger experience.
The Solution
Qlik partner GINQO provided data integration and analytics solutions that are used throughout YVR. These applications provide immediate insights on the many intertwined subprocesses – security, customs, baggage screening and so on – to help YVR improve efficiencies. A new data hub ecosystem, which combines Qlik and Snowflake, has also been implemented. This new system has enabled YVR to cut the time to run a report from 33 hours to under one minute, positioning the data infrastructure for future growth and agility.
Operational Impact
Quantitative Benefit
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