Colrows
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Travel retail · Global SSP Group

One platform. 3,000 venues. 40 countries.

Fragmented database tooling and a custom in-house front-line system replaced by a single platform combining SQL, notebooks, conversational analytics, and Slack. See the first-party research behind these numbers.

Before

A different tool for every developer.

3,000+ venues across 40 countries. Each developer used their own client - DBeaver, Squirrel, Toad. Front-line staff had no self-serve data access. A custom in-house system couldn't scale, and bastion infrastructure piled on operational overhead.

With Colrows

SQL, notebooks, chat - one platform.

A single unified workspace combining the SQL editor, Python notebooks, a conversational interface, and Slack integration. Developers, analysts, and front-line teams work in the same place - the proprietary front-line system was retired entirely.

01 · About SSP Group

SSP Group plc is a leading global operator of food & beverage venues in travel hubs - running over 3,000 units across nearly 40 countries and employing around 49,000 people. Specialising in airports, train stations, and other transit locations, SSP runs a diverse range of outlets, from sit-down restaurants and cafés to bars, quick-service restaurants, lounges, and food-led convenience stores.

Operating at this scale means SSP manages enormous volumes of data every day - tracking business performance, designing marketing strategies, and launching campaigns across dozens of markets simultaneously.

“Colrows is a complete solution for a firm like SSP Group; it turned out to be a one-stop solution for us.”
SSP at a glance
3,000+Venue units across airports, train stations, and transit hubs
~40Countries with active F&B operations
49KEmployees, from front-line staff to data scientists
DailyData crunching to track performance, campaigns, and KPIs across all markets
02 · The challenge

Fragmentation at scale.

SSP Group manages large volumes of data related to local events, business performance, and community insights - all critical for daily decision-making. As the business grew, so did the complexity of managing that data, exposing deep inefficiencies in the tools and workflows teams relied on.

The tech team had no standardised approach to database management. Developers independently used different clients - DBeaver, Squirrel, Toad - creating a fragmented environment where knowledge was siloed and work couldn't be reliably shared. Front-line staff couldn't access real-time data at all, forcing them to queue requests to already-stretched engineering teams.

SSP tried to solve the front-line access problem by building an internal system. But as the business scaled, that system became a burden - requiring constant refinement it could never sustainably keep up with. Compounding everything: SSP was simultaneously building a data science team and needed Python notebooks integrated into the same environment, not bolted on separately.

01

Tooling fragmentation

Developers used DBeaver, Squirrel, and Toad independently - no shared approach, no standardised query management.

02

Collaboration breakdown

Separate script copies per developer meant version mismatches, lost context, and no reliable way to track progress across teams.

03

Front-line data lag

Customer-facing staff had no self-serve access to data, forcing reliance on engineers to fulfil basic inquiries - slowing issue resolution.

04

Unsustainable in-house system

A proprietary front-line data tool required constant maintenance and couldn't scale with growing business demands.

05

Disconnected data science

The nascent data science team needed Python notebooks integrated into the same workflow - not as a separate, unconnected environment.

06

Bastion host complexity

Secure database access required maintaining bastion infrastructure - adding operational overhead and slowing developer setup.

03 · Why point solutions weren't enough

A platform, not a patch.

SSP's problem wasn't any single tool gap - it was the accumulation of many, each addressed independently, each adding to the fragmentation. Standardising the SQL client wouldn't resolve front-line access, or unify the data science workflow, or eliminate the bastion host. SSP needed a platform.

Point-solution approach

One tool per problem, multiplied across teams
×

Compounding integration debt

Each new tool creates a new integration surface - auth, routing, access controls - that compounds over time.

×

Context loss between tools

Notebooks don't know what the SQL editor ran. Front-line tools have no visibility into analyst work.

×

Inconsistent access management

Every tool has its own user model. At SSP's scale, synchronising permissions across tools becomes a full-time operational task.

×

No shared institutional knowledge

Queries and scripts built in isolated tools walk out the door with the individual, not the organisation.

Colrows unified platform

One environment, raw data to front-line action
✓

Single source of truth

SQL, Python notebooks, and conversational access live in one platform, pointing at the same data with consistent permissions.

✓

Collaboration as default

Shared SQL notebooks mean work is visible, reviewable, and reusable across the team from day one - not after a migration project.

✓

Bastion-free connectivity

Colrows eliminates the need for bastion host infrastructure, reducing operational overhead and simplifying developer onboarding.

✓

Python notebooks natively integrated

Data science workflows sit inside the same environment as SQL and conversational analytics - no separate toolchain, no context switching.

04 · The solution

One platform, every team.

Colrows addressed SSP's challenges not by replacing one tool at a time, but by providing a single unified environment across the entire data workflow - from database engineering to executive insight to customer-facing issue resolution.

01

SQL editor & shared notebooks

Replaces DBeaver, Squirrel, and Toad with one collaborative environment. Queries are shared, versioned, and searchable.

02

Conversational interface

Front-line staff query data in plain language without SQL or waiting on engineering - real-time answers at the point of interaction.

03

Python notebooks

Natively integrated with the same data sources as SQL, letting the data science team run analyses without leaving the platform.

04

Slack integration

Query results shared directly into Slack channels - analytics embedded in existing workflows, not a separate destination.

Data layer
Operational DBs Performance data Event & campaign data KYC / customer data
Colrows platform
SQL editor & notebooks Conversational interface Python notebooks Access management
Integrations
Slack Direct DB connectors (no bastion) Team collaboration layer
End users
Tech & data engineers Data scientists Front-line staff Customer success teams
05 · Before & after

The transformation in practice.

Tech team · database engineering workflow

Before / after deployment

Before Colrows

SQL clients3+ tools in active use - DBeaver, Squirrel, Toad - per developer preference
Query sharingIndividual file copies. No centralised repository. Version conflicts common.
CollaborationDevelopers worked in isolation. Progress tracking was manual and error-prone.
DB accessRequired bastion host setup per developer. Complex, slow to onboard new hires.
Data sciencePython notebooks lived outside the data workflow - separate tools, no integration.

After Colrows

SQL clientsOne platform. All engineers on the same editor with shared notebooks and history.
Query sharingCentralised, searchable. Queries shared directly to Slack. No duplication.
CollaborationNotebook-based collaboration. Work is visible, reviewable, and reusable across the team.
DB accessBastion eliminated. Direct connectors. New developer onboarding dramatically faster.
Data sciencePython notebooks natively integrated. Same platform, same data, no context switch.

Net effect: 40% reduction in data management overhead - engineers spending time on analysis, not infrastructure.

Front-line staff · customer-facing workflow

Before / after deployment

Before Colrows

Data accessZero self-serve capability. All data requests routed through tech or data teams.
Issue resolutionCustomer inquiries required waiting for engineering availability. Hours to days of lag.
In-house systemCustom-built tool. Constant maintenance burden. Couldn't scale with business growth.
CostOngoing engineering hours for internal system upkeep - rising with each new venue and market.

After Colrows

Data accessReal-time, self-serve. Conversational interface answers questions in plain language - no SQL required.
Issue resolutionCustomer inquiries resolved at the point of interaction. 3× faster resolution rate.
In-house systemRetired. Colrows replaced it entirely - eliminating maintenance overhead and technical debt.
CostInternal system costs replaced by a single Colrows subscription. Significant net savings.

Net effect: front-line teams operating with real-time data independence - no engineering bottleneck, no queued requests.

“There are no tools currently available on the market that compare, and the pricing is incredibly reasonable.”

Jayesh Pawar · Head of Analytics, SSP Group

What changed in production.

40% Reduction in data management overhead
3× Faster issue resolution for front-line staff
80% Improvement in cross-team collaboration
1 Custom internal system retired entirely
06 · Outcomes

Platform as competitive infrastructure.

The deployment didn't just improve efficiency metrics - it reframed what SSP's data infrastructure is capable of. Every team, from engineers to customer success managers, now operates with the same data fluency that previously required deep technical expertise.

40%

Reduction in data management overhead

Standardised tooling and centralised notebooks eliminated the operational cost of managing fragmented, per-developer environments across the engineering team.

3×

Faster issue resolution for front-line staff

Conversational data access allows customer-facing teams to resolve inquiries in real time - without queuing requests to engineers or waiting for data pulls.

80%

Improvement in team collaboration

Shared SQL notebooks and Slack integration transformed how teams work together - moving from isolated work streams to a single, visible, collaborative environment.

Zero

Internal system maintenance burden

SSP's custom-built front-line data tool was retired entirely. Colrows replaced it - eliminating ongoing engineering maintenance costs and technical debt at scale.

“There isn't any comparable platform in the market; Colrows is the all-in-one solution.”

Jayesh Pawar · Head of Analytics, SSP Group
07 · Why Colrows

Not another point solution.

What SSP needed wasn't a better SQL client, or a smarter front-line tool, or a new notebook environment. They needed a platform that understood how these capabilities belong together - and built them as a coherent whole rather than a collection of integrations.

Colrows provides a unified data platform in which SQL editing, Python notebooks, conversational access, and collaboration tooling share the same authentication layer, the same data sources, and the same institutional memory. Analysts, engineers, data scientists, and front-line staff all operate in the same environment - with appropriate access, not separate tools.

The result is a system where knowledge compounds. Queries built by engineers surface in notebooks used by data scientists. Insights from analysts flow directly to front-line teams via the conversational interface. Work done today becomes institutional infrastructure - not a file on someone's laptop.

Colrows vs. fragmented tooling
Separate authentication per toolSingle access model for all teams
Work siloed to individualsShared notebooks, searchable history
Bastion infrastructure requiredDirect connectors, zero bastion
Front-line reliant on engineersConversational self-serve interface
Python separate from SQLNotebooks natively integrated
Custom in-house maintenanceMaintained platform, scales with you

“There isn't any comparable platform in the market; Colrows is the all-in-one solution.”

JP
Jayesh Pawar
Head of Analytics, SSP Group

Retire the proprietary front-line tools.

One workspace for SQL, notebooks, conversational analytics, and Slack - for every team.

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