CDC & source-system integration
Change data capture, event streams, ELT, API, and file-feed integration across ERP, CRM, billing, HRIS, and operational line-of-business systems.
Data & KPI Visibility
CDC and data lake integration for portfolio company KPI visibility
Connect fragmented ERP, CRM, billing, operational, and add-on systems into governed reporting and analytics foundations sponsors and management teams can run the value creation plan on.
The Operating Reality
The plan is clear. The data layer underneath it is not.
Portfolio-company value creation runs on reporting cadence and operating visibility. When the source systems disagree, KPI reports lag, and add-ons multiply the landscape, management teams stop trusting the dashboards—and so does the sponsor.
- Source systems disagree on the same number. ERP, CRM, billing, operations, and HR each maintain a partial version of the operating truth. Consolidated reporting drifts apart from week to week.
- KPI reporting lags the business. Operating decisions wait on monthly close, manual extracts, and overnight refreshes. The plan is current; the data feeding it is not.
- Add-on acquisitions multiply the system landscape. Every add-on adds another set of source systems, chart-of-accounts decisions, and definitions to reconcile before reporting can stabilize.
- Dashboards are not trusted. When freshness, lineage, and definitions are unclear, operators rebuild a parallel reporting layer in spreadsheets every cycle.
- AI and automation stall on a brittle data layer. AI in the loop, automated workflows, and decision support need reliable data underneath them. Brittle pipelines turn pilots into rework.
What We Build
A governed analytics foundation behind the KPIs the plan runs on.
CDC, ingestion, data quality, and reporting integration sized to portfolio-company scale—built for the operating cadence sponsors and management actually use.
Data lake & warehouse ingestion
Lakehouse or warehouse ingestion patterns tuned to portfolio-company scale—governed, auditable, and right-sized for the operating cadence.
Schema & data quality checks
Schema validation, reconciliation against source systems, exception alerts, and freshness signals that catch breakage before reports go out.
KPI semantic layer support
A documented, versioned definition layer for the KPIs sponsors and management run on—shared by finance, operations, and the board view.
Freshness & exception monitoring
Pipeline health, latency, and exception monitoring tied to the KPIs that matter, not generic platform telemetry.
Operational dashboard feeds & secure access
Trusted feeds into operational dashboards and board views with access, governance, and lineage that hold up in QofE and diligence.
Implementation Path
A staged path from fragmented sources to trusted reporting cadence.
1
Source Inventory
Map the ERP, CRM, billing, operations, HRIS, and add-on systems that actually hold the data the value creation plan depends on.
Outcome: A decision-ready inventory of where the operating truth lives—and where source systems disagree.
2
KPI & Data Contract Definition
Lock the KPIs sponsors and management will run on, with named owners, sources, refresh cadence, and explicit data contracts between systems.
Outcome: A KPI and data-contract layer the board, the operators, and finance all sign off on before the build starts.
3
CDC / ELT Pipeline Design
Design the change data capture, event-stream, ELT, and API integration patterns that move source data into the analytics foundation at the cadence the business actually needs.
Outcome: Reliable, near-real-time data movement from source systems into the lakehouse or warehouse layer.
4
Data Quality & Reconciliation
Stand up reconciliation against source systems, schema validation, exception alerts, and freshness checks so the analytics layer is defensible under scrutiny.
Outcome: A reporting layer management trusts—and stops bypassing with parallel spreadsheets.
5
Dashboard & Reporting Integration
Wire the analytics foundation into operational dashboards, board-cycle views, and exception reporting against the same trusted definitions.
Outcome: One reporting layer feeding management, sponsors, and board cadence—no duplicate sources of truth.
6
Operating Cadence & Support
Embed the data layer into weekly, monthly, and board-cycle operating reviews with ongoing data-engineering support sized to how the company actually runs.
Outcome: A trusted reporting cadence sponsors expect, with the engineering capacity behind it.
Where It Fits in PE Value Creation
Visibility now, automated reporting next, defensible data at exit.
CDC and data lake integration is rarely the headline of the value creation plan. It is the layer that lets the plan run on trusted KPIs through the hold period.
First 30 days
Establish visibility. Inventory source systems, lock the first KPIs, and decide where CDC and lake/warehouse ingestion deliver the fastest reliable read on operating reality.
Days 30–100
Automate the reporting cadence. Stand up CDC pipelines, reconciliation, and operational dashboards so weekly and monthly operating reviews run on the same trusted layer.
Add-on integration
Normalize systems and KPI definitions across acquired companies. Bring add-on source data into the same governed analytics foundation instead of bolt-on dashboards.
Exit readiness
Defensible data lineage, reconciled definitions, and QofE-ready reporting that hold up under buyer scrutiny and shorten the path from LOI to close.
Technical Credibility
Vendor-neutral patterns. Built for portfolio-company reality.
We pick the integration, ingestion, modeling, and dashboarding patterns that fit the source systems and the operating cadence—not the ones that look best on a slide.
- Source systems: ERP, CRM, billing, HRIS, and operational line-of-business platforms across the portfolio.
- Movement patterns: CDC, event streams, ELT, APIs, and file feeds—matched to source-system constraints and reporting latency needs.
- Storage & modeling: lakehouse or warehouse foundations with a documented KPI semantic layer and dashboarding integration.
- Trust: data lineage, reconciliation, freshness checks, and exception monitoring built in from the start, not bolted on later.
Bring the KPI gap or the integration constraint. We will identify the first reporting workstream worth executing.
We strengthen sponsor and management-team execution capacity. We do not replace operator judgment.
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