Enterprise Data Integration Case Study

Single Source of Truth for Enterprise Pharmaceutical Data

A global pharmaceutical manufacturer needed consistent, trusted data across disconnected CRM and ERP systems. We implemented automated ETL pipelines, cleansed and deduplicated master data, standardized business rules, and created a governed Single Source of Truth. It improved operational consistency, strengthen data governance, and support long-term digital transformation.

Pharmaceutical Manufacturing

Data Engineering

Data Orchestration

reduction in duplicate master data

reduction in manual reconciliation

One of the world's largest pharmaceutical manufacturers develops, produces, and distributes prescription medicines, vaccines, and specialty therapies across more than 100 countries. Its global operations span research, manufacturing, supply chain, commercial, and regulatory functions, requiring trusted enterprise data to support daily operations, reporting, and strategic decision-making.

Microsoft SQL Server

Microsoft Dynamics CRM

SAP ERP

Power BI

THE CHALLENGE

Fragmented CRM and ERP Data Undermined Reporting Confidence and Required Extensive Manual Reconciliation Across the Enterprise

Business-critical information was distributed across multiple enterprise applications. Duplicate records, inconsistent business rules, and disconnected data flows forced teams to reconcile data manually before reports could be trusted. The client needed reliable synchronization without disrupting ongoing operations.

Fragmented Enterprise Data Across Disconnected CRM and ERP Platforms

Business information was spread across enterprise applications with no unified flow, making it difficult to maintain consistent records and obtain a complete operational view.

Duplicate and Inconsistent Master Data Reduced Trust in Reporting

Repeated and conflicting master records created uncertainty in downstream reports and increased the effort required to validate business-critical information.

Different Business Rules Produced Conflicting Data Across Departments‍

Departments applied inconsistent logic and definitions, causing the same business data to be interpreted differently across systems and reports.

Manual Reconciliation Slowed Reporting and Increased Operational Effort‍

Teams had to compare and correct data manually before using it, consuming time that could otherwise support analysis and business decisions.

Legacy Data Had to Be Migrated Without Interrupting Business Continuity‍

Historical information needed to be transformed and moved into the integrated environment while preserving accuracy and supporting ongoing enterprise operations.

Need trusted enterprise data across disconnected systems?

THE SOLUTION

A Governed Enterprise Integration Framework That Unified Systems, Cleansed Master Data, and Automated Reliable Synchronization

We designed and implemented an enterprise data integration solution connecting CRM and ERP platforms. Automated ETL pipelines synchronized information, while cleansing, deduplication, validation, and standardized business rules created a governed Single Source of Truth for reporting and analytics.

Integrated Microsoft Dynamics CRM and SAP ERP Into a Unified Data Flow‍

We connected the core enterprise platforms to enable consistent data exchange and reduce fragmentation across operational and reporting processes.

Cleansed and Deduplicated Master Data to Improve Record Quality‍

We identified duplicate and inconsistent records, applied cleansing logic, and established a more reliable master data layer across the integrated environment.

Migrated Historical Data and Established a Governed Single Source of Truth‍

We transformed legacy information, preserved historical value, and consolidated trusted data to support enterprise reporting, analytics, and future AI initiatives.

Built Automated SSIS ETL Pipelines for Enterprise Data Synchronization‍

We developed repeatable extraction, transformation, and loading workflows to move and synchronize data between systems with less manual intervention

Standardized Business Rules and Added Automated Validation Controls‍

We aligned data definitions and transformation rules across systems, then introduced automated checks to detect quality issues before they reached reports.

THE RESULT

A Trusted Enterprise Data Foundation Improved Reporting Reliability, Reduced Manual Work, and Prepared the Business for Advanced Analytics

The organization moved from fragmented enterprise data to a governed architecture with consistent master records and automated synchronization. Reporting became more reliable, teams spent less time reconciling information, and connected systems maintained high data accuracy. The resulting Single Source of Truth now supports operational consistency, executive reporting, advanced analytics, and future AI-driven decision-making.

85%

Reduction in duplicate master data records

45%

Reduction in manual data reconciliation

98%

Synchronization accuracy between integrated enterprise applications

Enterprise Data Integration Case Study | Pharma CRM & ERP

How we provide data integration solutions

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

At this stage, we need to ensure that we understand the full scope of the project. We receive from you or perform a set of interviews and prepare the following documents: integration pipeline (which data we should get and where to upload), process logic (how system should work); use cases and acceptance criteria; solution architecture. Ultimately we make a project plan which we strictly follow.

Step 3 of 5

Solution development

At this stage, we build ETL pipelines and necessary APIs to automate the process. We attract our DevOps team to build the most efficient and scalable solution. Ending up with unit tests and quality assurance tests to ensure that the solution is working properly. Focus on Results is one of our core values as well.

Step 4 of 5

Solution delivery

After quality assurance tests are completed, we deliver solutions to the client. Though we have over 15 years of expertise in data engineering, we are expecting client’s participation in the project. While developing the integration system, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

Success stories

All Success Stories

Custom Sensor Monitoring System for Pharmaceutical Transportation

A pharmaceutical manufacturer faced disruptions and delays in vaccine transportation due to limited visibility into shipment conditions. To improve operational control and ensure product quality, the company implemented an automated monitoring system that continuously tracks environmental conditions, detects critical deviations, and immediately alerts operators. The solution streamlined cold chain operations, accelerated incident response, and created a complete digital audit trail for every shipment.

65%

Reduction in Manual Transportation Checks

80%

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Custom Sensor Monitoring System for Pharmaceutical Transportation

Real-Time Vaccine Cold Chain Monitoring Platform

Pharmaceutical R&D Platform for Hormone Therapy Development

A pharmaceutical company developing hormone-based therapies needed to replace fragmented laboratory systems and manual research coordination with a unified digital platform. We built a centralized R&D management system that unified laboratory operations, research workflows, scientific documentation, and project reporting—creating a single source of truth that improved collaboration, strengthened regulatory traceability, and accelerated research execution.

70%

less manual research administration

55%

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Pharmaceutical R&D Platform for Hormone Therapy Development

Pharmaceutical R&D Platform for Hormone Research

Ottawa Healthcare Network Gains Operational Visibility with CareOps AI OS

A growing multi-location healthcare network in Ottawa struggled with fragmented operational data spread across EHR, telehealth, scheduling, and billing systems. DATAFOREST implemented CareOps AI OS — an operational intelligence platform that unified data across 5 core systems, standardized workflows, and gave leadership real-time visibility into patient flow, provider utilization, and bottlenecks. The result was faster decision-making, better scheduling efficiency, reduced manual coordination, and a stronger foundation for scalable clinic operations.

25%

reduction in manual operational coordination

35%

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Ottawa Healthcare Network Gains Operational Visibility with CareOps AI OS

Healthcare AI Platform for Multi-Clinic Operations

Custom Sensor Monitoring System for Pharmaceutical Transportation

65%

Reduction in Manual Transportation Checks

80%

View case study

Real-Time Vaccine Cold Chain Monitoring Platform

Pharmaceutical R&D Platform for Hormone Therapy Development

70%

less manual research administration

55%

View case study

Pharmaceutical R&D Platform for Hormone Research

Ottawa Healthcare Network Gains Operational Visibility with CareOps AI OS

25%

reduction in manual operational coordination

35%

View case study

Healthcare AI Platform for Multi-Clinic Operations

80%+ Reduction in Manual Job Data Handling Using an AI Platform

The client productized its healthcare recruitment services by replacing manual job data processing with an AI-powered platform. We built an LLM-driven microservice architecture that automates the ingestion, extraction, validation, and deduplication of thousands of unstructured job postings every day. The solution powers both web and mobile applications, significantly improving processing speed and data accuracy. As a result, the platform reduced operational costs by 20–40% while enabling scalable growth.

0.9s

job posting processing time

80–95%

reduction in manual job data handling

View case study