Data siloed across tools, finance started with one schema and no data. Now non-technical users query 10K food items in 2 minutes.
A national carrier managing hundreds of catering suppliers, thousands of fleet contracts, and operations across a global network, with company data historically spread across disparate tools and duplicated in silos.
Finance leaders wanted to move beyond static dashboards showing historical data toward understanding why costs moved and what to do next. When a...
Flag carrier airline of the UAE operating passenger and cargo flights.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Etihad Airways's Finance analytics is part of this use case:
Related implementations across industries and use cases
Every data question routed through engineers. Now 800+ users — 70% non-technical — query a 200-country travel dataset in plain language.
Every new meeting question triggered days of data prep. Finance teams now ask the data lake directly and test hypotheses in minutes.
Reconciling siloed systems delayed revenue forecasts. Now, teams query AI agents in plain language to pull project data in seconds.
Reconciling siloed systems delayed revenue forecasts. Now, teams query AI agents in plain language to pull project data in seconds.
Guests spent 40 hours planning trips using rigid search menus. Now, AI matches natural language queries to live flights and loyalty data.
Scattered data made AI features impossible to build. Unifying it unlocked search that understands traveler intent, not just keywords.
Manual prospecting across multiple tools delayed first contact. Now, an agent curates warm leads, so reps start their day ready to sell.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Invoice disputes took days across disconnected systems. An AI assistant now researches and classifies each case; specialists just decide.
Data siloed across tools, finance started with one schema and no data. Now non-technical users query 10K food items in 2 minutes.
A national carrier managing hundreds of catering suppliers, thousands of fleet contracts, and operations across a global network, with company data historically spread across disparate tools and duplicated in silos.
Finance leaders wanted to move beyond static dashboards showing historical data toward understanding why costs moved and what to do next. When a...
Flag carrier airline of the UAE operating passenger and cargo flights.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Etihad Airways's Finance analytics is part of this use case:
Related implementations across industries and use cases
Every data question routed through engineers. Now 800+ users — 70% non-technical — query a 200-country travel dataset in plain language.
Every new meeting question triggered days of data prep. Finance teams now ask the data lake directly and test hypotheses in minutes.
Reconciling siloed systems delayed revenue forecasts. Now, teams query AI agents in plain language to pull project data in seconds.
Reconciling siloed systems delayed revenue forecasts. Now, teams query AI agents in plain language to pull project data in seconds.
Guests spent 40 hours planning trips using rigid search menus. Now, AI matches natural language queries to live flights and loyalty data.
Scattered data made AI features impossible to build. Unifying it unlocked search that understands traveler intent, not just keywords.
Manual prospecting across multiple tools delayed first contact. Now, an agent curates warm leads, so reps start their day ready to sell.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Invoice disputes took days across disconnected systems. An AI assistant now researches and classifies each case; specialists just decide.