PILLARDATA MANAGEMENT

One number. Every system. Same source.

Data architecture, pipelines, governance, and CDP — without vendor lock-in or undocumented magic.

Book a consultSee sub-services
Method
Decisions-first
We map the decisions the data must support before we design a single table.
Contracts
Data contracts
Automated tests between producers and consumers catch breakage in the pipeline, not the exec's inbox.
Governance
PIPEDA · HIPAA · SOC 2
Regulated-industry architectures shipped through external audit without material findings.
Practice proof

Numbers the practice will defend in writing.

Schema designed for downstream decisions
Decisions-first
Automated tests on every producer/consumer pair
Data contracts
Typical mid-market CDP implementation
12–24 weeks
Documented hand-over · no vendor lock-in
Transferable

Quick answer
NUUN Digital's Data Management practice designs data architecture, builds ETL/ELT pipelines, installs governance, and implements Customer Data Platforms (CDPs) for mid-market and enterprise clients. The goal is one reconciled customer view that the marketing model, the analytics dashboard, the AI system, and the finance close all draw from. No reconciliation wars in the QBR.
Sub-services

4 discrete engagements inside the Data Management pillar.

001
Data Management

Data Architecture & Modeling

Modern data architecture — warehouse, lakehouse, or both.

002
Data Management

ETL / ELT Pipelines

Production-grade ELT with observability and tests.

003
Data Management

Data Governance & Quality

Catalogs, stewards, and data contracts that hold.

004
Data Management

Customer Data Platforms

CDP selection, implementation, and activation.

How we work.

A six-step process from discovery to measured outcome.

  1. 01

    Discover

    Interviews, audits, and a written problem statement.

  2. 02

    Design

    Approach options with trade-offs and pricing.

  3. 03

    Plan

    Phase-by-phase plan with a single accountable owner.

  4. 04

    Build

    Execution in weekly sprints, stakeholder demos every 2 weeks.

  5. 05

    Measure

    Against the KPI we set in week one. No vanity metrics.

  6. 06

    Compound

    Quarterly review, roadmap refresh, next bet.

The unglamorous layer that makes everything else work

Every broken dashboard, every failed attribution model, and every AI pilot that "didn't work" traces back to a data layer nobody owned. We own it.

We design the schema, build the pipes, install the governance, and leave a maintenance rhythm your team can actually run. No vendor lock-in, no undocumented magic.

Comparison — CDP archetypes

| You need | Best fit | Strengths | Typical cost (annual) | Typical implementation | |---|---|---|---|---| | Fast marketer-activation with light engineering | Segment / mParticle / Tealium | Pre-built connectors, campaign activation | $60k–$400k+ | 8–16 weeks | | Warehouse-native, engineering-led | Snowflake + Hightouch / Census | Full data control, no duplication | $40k–$250k+ | 10–20 weeks | | Open-source first | RudderStack / Jitsu | Self-host option, data sovereignty | $20k–$150k | 10–18 weeks | | All-in with enterprise suite | Adobe Real-Time CDP / Salesforce Data Cloud | Suite consolidation | $200k–$1M+ | 16–28 weeks |

Industries we know

Data patterns matched to regulatory and operational reality across CPG, Financial Services, Health & Wellness, Healthcare & Pharma, Lottery & Gaming, Retail & E-commerce, Travel & Hospitality, Public Affairs, Energy, Real Estate, Education, and Tech & SaaS.

Browse industry pages →

Related reading

Sources & further reading

NUUN Digital Data Engineering Practice — Head of Data. Data architecture and modelling, ETL/ELT on dbt and Fivetran, governance aligned to PIPEDA and HIPAA, CDP implementation across Segment, mParticle, and warehouse-native stacks.

Proof.

Recent wins across NUUN Digital engagements.

Retail & E-commerce

A loyalty app worth keeping on the home screen.

NativeiOS + Android rebuild · Swift + Kotlin
Financial Services & Fintech

A bank AI assistant with zero material findings.

ZeroMaterial audit findings at rollout

FAQ.

What is a Customer Data Platform (CDP) and do we actually need one?
A CDP unifies customer data from marketing, product, sales, and service systems into a single, identity-resolved profile, then activates that profile to downstream tools. You need one when marketing, product, and analytics are each keeping their own version of "the customer" — and the versions no longer agree. If teams are reconciling customer lists manually, that's the tell.
CDP vs data warehouse — which comes first?
The warehouse, almost always. A CDP is an activation and identity layer on top of a data foundation. If the warehouse isn't trustworthy, the CDP will amplify the problem. We frequently recommend a warehouse-native CDP architecture (Snowflake + Hightouch or Census) for mid-market clients rather than a parallel CDP stack.
Which ETL/ELT tools do you prefer?
Tool-agnostic. Fivetran and Stitch for managed replication, dbt for transformation, Airbyte for open-source flexibility, and custom Python or TypeScript where tools don't fit. Our default recommendation is dbt plus Fivetran for most mid-market clients because the total cost of ownership is predictable. For enterprise or unusual sources, we build custom.
How long does a CDP implementation take?
12–24 weeks for mid-market, 24–40 weeks for enterprise. The longest poles are identity resolution design, compliance review, and activation use-case definition — not technical integration. Implementations that promise 8 weeks are usually skipping one of those.
Do you work with our security and compliance requirements?
Yes. We run engagements under PIPEDA, GDPR, HIPAA, PCI-DSS, and SOC 2 requirements, and we've shipped architectures for regulated industries including healthcare, financial services, and government. Compliance is scoped from week one, not as an afterthought.
What happens after implementation?
Hand-over or managed. We either transfer full ownership to the client team with documentation, training, and 60 days of backup — or we continue as the managed data team under a Data-as-a-Service agreement. Either is priced transparently.
Can you fix a failed CDP implementation we started elsewhere?
Often. Rescue engagements are common and usually begin with a two-week diagnostic — what's salvageable, what needs re-architecting, what's behaviorally broken between teams. We give an honest rebuild-or-repair recommendation before scoping the work.

Ready to talk Data Management?

Bring the target and the deadline — we'll scope an approach in 5 business days.

Book a call