Fivetran Case Studies JetBlue's Real-Time Analytics Transformation with Fivetran and Snowflake

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	JetBlue's Real-Time Analytics Transformation with Fivetran and Snowflake Fivetran

JetBlue's Real-Time Analytics Transformation with Fivetran and Snowflake

Fivetran

Technology Category	Functional Applications - Computerized Maintenance Management Systems (CMMS) Infrastructure as a Service (IaaS) - Cloud Databases
Applicable Industries	Buildings Cement
Applicable Functions	Maintenance Warehouse & Inventory Management
Use Cases	Asset Health Management (AHM) Predictive Maintenance
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	JetBlue, a major airline operating over 900 flights daily to more than 110 cities, was grappling with the challenge of managing and analyzing the vast amount of data generated by its operations. Every person, plane, and journey generated data points that could provide insights into customer sentiments, revenue forecasting, fuel consumption, aircraft maintenance, and operational readiness. However, the sheer volume of data, sourced from 130 different systems, was overwhelming and difficult to organize. The airline needed a solution that could centralize this data, making it readily accessible for analysis and decision-making. The challenge was to bring all this data into a single platform quickly and accurately for analysis. Read More
About Customer	JetBlue is a major airline that carries customers to more than 110 cities throughout the United States, Latin America, the Caribbean, Canada, and the United Kingdom. The airline operates an average of 900+ flights per day. Every person, plane, and journey generates data points that reveal customer sentiments, inform revenue forecasting, help predict fuel consumption, prescribe aircraft maintenance, and give critical insight into operational readiness. The airline was facing challenges in managing and analyzing this vast amount of data, which was sourced from 130 different systems. Read More
Solution	JetBlue decided to build a modern, cloud-based data stack using Fivetran and Snowflake. Fivetran's pipelining tools enabled JetBlue to move data from multiple sources to its Snowflake data cloud. This allowed the data engineering team to rapidly access information for analytic use cases and significantly reduced the time it took to manually build data pipelines. JetBlue's Snowflake data warehouse now contains over 115TB of data, and fresh data is readily available for analysis. The airline also built a suite of self-service analytics products, used by analysts and leaders across many workgroups to deliver meaningful insights. For instance, JetBlue integrated Qualtrics customer survey data into Snowflake using Fivetran's Qualtrics connector, enabling the airline to better understand its customers and enhance their experiences. Read More Log in to view content
Contents

Technology Category

Functional Applications - Computerized Maintenance Management Systems (CMMS)

Infrastructure as a Service (IaaS) - Cloud Databases

Applicable Industries

Buildings

Cement

Applicable Functions

Maintenance

Warehouse & Inventory Management

Use Cases

Asset Health Management (AHM)

Predictive Maintenance

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

JetBlue, a major airline operating over 900 flights daily to more than 110 cities, was grappling with the challenge of managing and analyzing the vast amount of data generated by its operations. Every person, plane, and journey generated data points that could provide insights into customer sentiments, revenue forecasting, fuel consumption, aircraft maintenance, and operational readiness. However, the sheer volume of data, sourced from 130 different systems, was overwhelming and difficult to organize. The airline needed a solution that could centralize this data, making it readily accessible for analysis and decision-making. The challenge was to bring all this data into a single platform quickly and accurately for analysis.

About Customer

JetBlue is a major airline that carries customers to more than 110 cities throughout the United States, Latin America, the Caribbean, Canada, and the United Kingdom. The airline operates an average of 900+ flights per day. Every person, plane, and journey generates data points that reveal customer sentiments, inform revenue forecasting, help predict fuel consumption, prescribe aircraft maintenance, and give critical insight into operational readiness. The airline was facing challenges in managing and analyzing this vast amount of data, which was sourced from 130 different systems.

Solution

JetBlue decided to build a modern, cloud-based data stack using Fivetran and Snowflake. Fivetran's pipelining tools enabled JetBlue to move data from multiple sources to its Snowflake data cloud. This allowed the data engineering team to rapidly access information for analytic use cases and significantly reduced the time it took to manually build data pipelines. JetBlue's Snowflake data warehouse now contains over 115TB of data, and fresh data is readily available for analysis. The airline also built a suite of self-service analytics products, used by analysts and leaders across many workgroups to deliver meaningful insights. For instance, JetBlue integrated Qualtrics customer survey data into Snowflake using Fivetran's Qualtrics connector, enabling the airline to better understand its customers and enhance their experiences.

Impact #1	The implementation of the modern data stack has significantly improved JetBlue's operational efficiency and decision-making process. The airline has been able to create better customer experiences and better understand its own operations. The integration of Qualtrics customer survey data has enabled JetBlue to gain a better understanding of its customers and enhance their experiences. The airline's data engineering team has been freed from the time-consuming task of building custom data pipelines, allowing them to focus on more valuable projects. Furthermore, the consolidation of aircraft maintenance data has brought JetBlue closer to achieving truly predictive maintenance, which could lead to improved maintenance efficiency, cost savings, and prevention of mechanical issues that could shorten the overall lifespan of a machine.

Impact #1

The implementation of the modern data stack has significantly improved JetBlue's operational efficiency and decision-making process. The airline has been able to create better customer experiences and better understand its own operations. The integration of Qualtrics customer survey data has enabled JetBlue to gain a better understanding of its customers and enhance their experiences. The airline's data engineering team has been freed from the time-consuming task of building custom data pipelines, allowing them to focus on more valuable projects. Furthermore, the consolidation of aircraft maintenance data has brought JetBlue closer to achieving truly predictive maintenance, which could lead to improved maintenance efficiency, cost savings, and prevention of mechanical issues that could shorten the overall lifespan of a machine.

Benefit #1	JetBlue's Snowflake data warehouse now contains over 115TB of data from 130 different systems.
Benefit #2	The data engineering team can set up new data pipelines in under two minutes.
Benefit #3	Fresh data is readily available for analysis, enabling real-time decision making.

Benefit #1

JetBlue's Snowflake data warehouse now contains over 115TB of data from 130 different systems.

Benefit #2

The data engineering team can set up new data pipelines in under two minutes.

Benefit #3

Fresh data is readily available for analysis, enabling real-time decision making.

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Overview

JetBlue's Real-Time Analytics Transformation with Fivetran and Snowflake

Operational Impact

Quantitative Benefit