Consolidated multiple BI platforms, including PowerBI and Tableau, into a centralized Looker instance with a unified executive data perspective
Standardized data operations for over 1,100 internal users through a scalable hub and spoke architecture
Accelerated organizational consolidation by unifying acquisition data into common models ahead of backend migrations
Utilized the Looker API to automate content migration and ensure seamless instance transitions during acquisitions
Implemented automated governance scripts to maintain a lean environment by removing unpromoted personal content
Arrive utilized Looker to rapidly unify their business analytics following multiple significant acquisitions that expanded their data footprint. By leveraging Looker, the company has established a sophisticated analytics environment that accelerated previous timelines for platform migration.
Arrive utilized Looker to rapidly unify their business analytics following multiple significant acquisitions that expanded their data footprint. By leveraging Looker, the company has established a sophisticated analytics environment that accelerated previous timelines for platform migration.
Unifying analytics across global acquisitions
Following a period of rapid international expansion and numerous acquisitions, including PARK NOW Group, Flowbird Group, and Parkopedia, Arrive inherited a fragmented analytics landscape featuring various BI tools, including Tableau, PowerBI, and Superset. The primary challenge involved integrating these historically independent businesses, each with unique focuses and tech stacks, into a single, cohesive platform. The company required a strategic "connective tissue" that could align diverse business units and provide executives with a singular, authoritative version of performance data while long-term platform migrations remained in progress.
By enabling data from new acquisitions into a single common model and mindset through Looker, we become one business and one company faster.
Doreh Bovelet
Senior Manager, Business Analytics, Arrive
A modern tech stack for global scalability
To support global operations, Arrive has built a high performance technology stack with Looker acting as the core hub of certified global data models, which provide the foundation for decentralized spokes managed by specific business units, like Finance and Business Distribution, ensuring data from disparate hardware and software sources is unified into a single, reliable source of truth.
The team utilizes Snowflake as their primary data warehouse and Fivetran to ingest data across multiple regional instances into a centralized global modeling layer, while DBT is leveraged for robust data transformation.
Executives are able to have that same conversation about how we're performing in the UK, in the EU, in the US. Even before the business consolidates into a singular platform, we’re actually combining business languages and business logics.
Doreh Bovelet
Senior Manager, Business Analytics, Arrive
Precision in content validation and developer workflow
One tool can’t have everything built into it... but with the Looker API, you can build some of these missing things yourself. It's been quite useful for platform building and migrations.
Meelis Perli
Tech Lead, Arrive
Arrive employs a rigorous governance model to safeguard platform integrity as its global user base scales. To ensure high-quality data exploration, new users are onboarded as "viewers" and must formally request "explorer" status, a process that triggers tailored training and guidance from the core team. To prevent technical debt and negative growth, the team utilizes automated API scripts to prune unpromoted personal content every 30 days, maintaining a high-performance environment.
From a development perspective, Arrive enforces a sophisticated CI/CD workflow, utilizing LookML linters to standardize code quality across all business units.
The team further extends Looker’s flexibility through the extensive use of Liquid to create dynamic explorers that adapt queries based on user selection. To streamline complex administration, tech lead Meelis Perli developed a custom Streamlit application powered by the Looker API; this internal tool automates LookML formatting and tracks field usage, significantly reducing administrative overhead and simplifying developer operations.
Pioneering conversational analytics and internal support
As part of its company planning, Arrive is developing a strategy to integrate Looker’s conversational analytics and agentic features. The team is particularly focused on utilizing the conversational analytics API to build a customized internal chatbot for their Looker Community Slack channel. This bot will act as a usage coach, sourcing information from Confluence, Jira, and Looker documentation to answer user queries automatically. By guiding users to the right data models and documentation without human intervention, Arrive aims to scale support capabilities while saving the core analytics team’s time.
As avid API lovers, we’re really excited about the conversational analytics API. We can start to do some customization to gear people towards the right answer without necessarily having to have human interaction.
Doreh Bovelet
Senior Manager, Business Analytics, Arrive
Arrive is a leading global mobility platform with the mission to ease movement in cities. Present in more than 20,000 cities across 90 countries, the company delivers core competencies from smart payments and optimizing parking solutions, to data-driven traffic reduction measures and refining public transport networks.
Industry: Technology
Location: United Kingdom
Products: Google Cloud, Looker
