Service · 03
Data Integration & Reporting
One trusted view across the systems you already use.
We connect your systems, clean the data, agree common business measures and build reliable reports, dashboards and AI-ready data.
Problems we solve
What usually brings teams here
- ERP, CRM, finance, warehouse and e-commerce data do not line up.
- Teams use different numbers for the same measure.
- Reports depend on manual spreadsheet work.
- Business users wait too long for answers.
- Data problems block automation and AI projects.
- Cloud data and reporting costs keep growing.
What's included
What we do in data integration & reporting
01
Business System Connections
Connect ERP, CRM, finance, warehouse, e-commerce and other approved systems.
02
Data Cleaning & Enrichment
Fix formats, remove duplicates, standardize records and add useful fields.
03
Shared KPI Definitions
Agree one calculation, source and owner for each important business measure.
04
Dashboards & Reporting
Build dashboards and reports people actually use, for the decisions that matter.
05
AI-Ready Data Preparation
Prepare structured data and approved documents so they can support AI and automation.
06
Data Quality & Ownership Rules
Add checks, alerts and clear owners so problems are caught early.
07
Platform Cost Review
Review storage, processing and reporting cost, then remove waste.
What you receive
Clear deliverables
- System and data map
- Connected data flows
- Clean business data model
- KPI dictionary
- Dashboards and reports
- Quality checks and ownership rules
- Technical and user documentation
- Ongoing support plan
How it works
- 1Map the business needList systems, reports, users and the decisions that matter.
- 2Connect the sourcesBuild reliable flows from each approved system.
- 3Clean and defineApply rules and agree common KPI definitions.
- 4Build the viewsCreate dashboards, reports or reusable data for AI and automation.
- 5Run and improveMonitor quality, performance, usage and cost.
Want data integration & reporting scoped for your team?
Send us the problem and the systems involved. We reply within one business day with a starting point, a target and a first step.
Beyond dashboards
Make definitions and source history part of the data product
Reliable reporting starts before a chart. DataplexLabs maps approved source systems, resolves duplicate records and conflicting values, agrees refresh schedules and documents each KPI's definition, owner and source. That traceability helps reports stay consistent and gives downstream automation or AI a clearer business context.
- Name the system of record and resolution rule when two sources disagree
- Use stable identifiers to reduce duplicate or orphaned records
- Document KPI formula, inclusions, exclusions, owner and refresh schedule
- Track source-to-report lineage so a disputed number can be traced
- Prepare reusable, consistent business data for approved analytics and AI uses
How we measure success
Agree the measures before delivery starts
These are measurement categories, not performance claims. The relevant definitions and acceptance criteria are agreed for each engagement.
- KPI consistency
- Whether teams use the same documented calculation and source.
- Freshness
- Whether source and report updates follow the agreed schedule.
- Duplicate and conflict handling
- Whether repeated or contradictory records follow a documented rule.
- Traceability
- Whether a reported value can be followed back to its approved source.
Outcomes
Why teams engage us
- One set of numbers everyone agrees on
- Less manual spreadsheet work each month
- AI and automation projects are no longer blocked by data
How we position this
You usually do not need to replace your systems. The goal is to connect and improve what you already use, starting with one report or business area.
Related solutions
Packaged around a business outcome
03
AI-Ready Business Data
Create one trusted data base for reporting, automation and AI.
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10
Purchasing & Supplier Dashboard
See spend, suppliers, contracts and savings opportunities in one place.
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08
Profit Leakage Finder
Find pricing, rebate, billing and contract errors that reduce profit.
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FAQ
Data Integration & Reporting questions, answered
Common questions we hear about data integration & reporting. If yours is missing, ask us.
No, usually you keep the systems you already use. The service connects your ERP, CRM, finance, warehouse and e-commerce systems, cleans the data, and agrees one set of KPI definitions across teams. Dashboards and reports are built on top of your existing reporting tool unless you specifically ask us to review alternatives. A first working dashboard or report is common within 3 to 5 weeks.
Cost depends on the number of systems connected, data volume, and how many KPIs and dashboards are needed. We usually start with one report or business area as a fixed-price pilot before pricing a wider rollout. This lets you confirm accuracy and adoption before expanding to more systems or teams. Ongoing support and monitoring are quoted separately as ongoing engagements.
We run a short workshop with business owners to agree one calculation, one source and one owner for each important measure. This becomes a written KPI dictionary that dashboards and reports are built against. When new conflicts appear later, the same owner and definition process resolves them. This keeps reporting consistent as new systems or teams are added.
Accuracy is maintained through data quality checks, freshness monitoring and clear ownership rules for each pipeline. We test coverage and correctness against source systems before launch, then track pipeline reliability and report preparation time on an ongoing basis. Alerts flag failed connections or unusual data changes so issues are caught before they reach a dashboard. This is reported alongside usage metrics after go-live.
You need to grant read access to the systems in scope, such as your ERP, CRM or finance database, following your normal approval process. We work within your existing security and access controls rather than requesting broad permissions. A system and data map is agreed with you first so only the required data flows are built. No changes to your core systems are needed.
The same clean, structured data and KPI definitions used for dashboards can feed models, assistants and automated workflows later. Because sources, fields and quality rules are already documented, AI teams do not need to redo data preparation. This removes one of the most common blockers to starting an AI project. Many clients treat integration and reporting as the foundation step before automation work.
Proof
Where this work paid off
Manufacturing
Cut purchasing cost surprises and document work across plants
This manufacturer had spend and supplier data trapped in plant-level systems, spreadsheets and supplier portals. Purchase teams spent days reconciling costs, tariffs changed without warning, and quality documents were processed by hand. DataplexLabs connected the sources, built a unified purchasing view and put document extraction in place with a human review queue.
Read the case study →Wholesale & Distribution
Recover margin lost in rebates, billing errors and price inconsistencies
Rebates, special pricing agreements and billing mistakes were quietly eroding margin. Prices varied between customers and channels, and order-to-cash work was still manual. DataplexLabs rebuilt the price-to-invoice trail, matched contracts to transactions and added monitoring for the top leakage causes.
Read the case study →Retail & E-commerce
React to market moves faster with clean product, price and seller data
Competitor prices, promotions and stock levels were checked by hand, so the team reacted too late. Product content drifted across marketplaces and unauthorized sellers broke pricing rules. DataplexLabs set up continuous monitoring of competitor and marketplace data and built a single source of product truth.
Read the case study →Next step
Discuss your use case
Bring one pain point, a data source, a workflow, a margin question. We'll come back with a focused assessment and a clear ROI hypothesis.