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Data governance and MDM services built on trust

We help you establish a single source of truth for critical business data, with governance frameworks that keep it accurate, secure, and compliant as your organization scales.

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Data management challenges we help you solve

1 Many systems, one definition

One master record, used everywhere

Customer, product, and vendor records get reconciled into a single golden record, so every system references the same accurate information.

2 Avoid scrambling to pass an audit

Compliance built into daily operations

Governance frameworks continuously document data lineage and access, so audit readiness doesn't depend on a last-minute cleanup effort.

3 Trustworthy data without double- and triple-checks

Data quality you don't have to verify twice

Validation rules and stewardship processes catch errors before they spread, so teams can rely on data without re-checking it themselves.

4 Know who can access what, and why

Access control that matches actual policy

Role-based access and data classification are aligned with your unique compliance requirements, not a generic template applied after the fact.

How we approach data governance & management

Governance that fits how you operate Governance that fits how you operate

Trust frameworks are shaped around your existing systems and workflows, rather than forcing a rigid structure that your teams have to work around.

Ownership is assigned, not assumed Ownership is assigned, not assumed

Every data domain has a clear steward accountable for its quality, closing the gap where issues usually go unaddressed.

Quality standards that hold up to regulation Quality standards that hold up to regulation

Governance practices are designed to meet regulatory requirements such as GDPR and HIPAA, not a generic best-practices checklist.

Designed around the process Visibility into where data comes from

Lineage tracking shows exactly how a piece of data moved and changed, making root cause investigation straightforward rather than guesswork..

The practices behind the outcomes

Master Data Management

Customer, product, and vendor records are consolidated into a single, authoritative source across systems.

Data Quality & Validation

We build rules and checks directly into pipelines to prevent data issues before they reach reports.

Auditability & Cataloging

Every data asset is documented and tracked, showing where it came from and how it changed.

Access Control & Data Classification

Sensitive data is classified, and access is restricted based on role, need, and policy.

Regulatory Compliance Frameworks

Governance structures are aligned with standards, including GDPR, HIPAA, and industry-specific regulations.

Data Stewardship Programs

Clear ownership is assigned across data domains, so accountability for quality doesn't fall through the cracks.

Related Services

Explore these additional services from our Data & Analytics capability pillar.

We design unified data platforms that break down silos, making information accessible across your organization.

arrow-forward Explore Data Engineering

We build fully integrated systems of intelligence enabling you to monitor performance, predict patterns, and automate analysis.

arrow-forward Explore Business Intelligence

We architect data pipelines capable of processing events as they happen, enabling instant response to business-critical signals.

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Built to pivot without losing velocity

We understand that in a high-growth business, pivots are inevitable. We’re built to absorb the impact and keep you moving forward.
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1. Full product teams

Full product teams

End-to-end product teams that own the entire lifecycle from discovery to delivery and continuous improvement.​
2. Forward-deployed engineering

Forward-deployed engineering

Senior pods quickly embedded to solve complex problems and drive strategic initiatives.​
3. Co-sourced delivery

Co-sourced delivery

A collaborative partnership where we share ownership and accountability to deliver high-quality results.​
4. Rapid capacity deployment

Rapid capacity deployment

Quickly scale your team with pre-vetted talent to meet urgent demands and accelerate delivery.​
5. Team augmentation

Team augmentation

Extend your team with skilled professionals who seamlessly integrate and enhance your capabilities.​

Data governance and MDM consultants who have been there, done that

No engagement is one-size-fits-all. Our data experts adapt to your stage, your stack, and your team.

Yury Zhukovsky
Yury Zhukovsky

Practice Lead, AI & BI

Over 20 years leading complex data programs for global enterprises.

Data & Analytics
AI & Gen AI
Alena Bashmakova
Alena Bashmakova

Data & Analytics Lead

Over 20 years of Business Intelligence & Data Warehouse expertise.

Data & Analytics
Julia Grishkevich
Julia Grishkevich

Business Intelligence Engineer

Global expertise in building scale-ready data systems across diverse tech stacks.

Data & Analytics

Case Studies

Fleet battery intelligence customer portal and installation app
Manufacturing & Industrial Services

Fleet battery intelligence customer portal and installation app

Our product teams turn field activity, asset data, and fleet metrics into customer-facing insight and installation control.
20
Multi-disciplinary delivery engineers
30k+
Fleet of trucks and batteries
2
Connected products for web & mobile
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Our approach

With little formal documentation to lean on, Coherent’s team relied on frequent, direct conversations with the client’s technical staff to confirm new features as they completed each step of the project:

  • Codebase archaeology and consolidation: engineers worked through the four mismatched mobile repositories, cross-referenced them against the live app store build, and reconstructed the most current working codebase before making any changes.
  • Environment separation: introduced dedicated development, QA, and production environments in place of the single, undifferentiated setup the client had been running.
  • Cloud infrastructure cleanup: rebuilt cloud build pipelines and restructured infrastructure, improving reliability, while bringing monthly cloud costs down from roughly $8,000 to about $1,500, an 81% reduction.
  • New device API: built a new backend API, on a Grails and Java/Spring stack, that takes raw measurements from the client's new refraction-testing hardware, applies the client's formula, and returns validated results ready for review by a licensed doctor.
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The solution

Today, the platform supports a complete at-home vision-testing workflow. Users complete a guided assessment with the client's hardware, results are processed through Coherent-built backend logic, and outcomes are routed to a licensed eye care professional for a prescription. The underlying infrastructure now runs across separate dev, QA, and production environments at a fraction of its previous cloud cost, giving the client a stable foundation to build on as it brings new devices to market.

 

The impact

  • 81% reduction in monthly cloud costs, from about $8,000 to about $1,500
  • New device API delivered in about 9 months, supporting the client's newest hardware line
  • New development, QA, and production environments to replace the client’s single setup, consolidating four mismatched mobile repositories into one working codebase
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The challenge

An undocumented, fragmented codebase

Before building the API or writing new code, Coherent needed to identify the code currently driving the client’s companion app. With no product requirements documentation and four mismatched repositories to sort through, they had to cross-reference what was on old developer laptops against the live versions in the app stores.

No environment separation and rising cloud costs

The client’s systems and software were running in a single environment — without a clear separation between development, QA, and production — which increased the likelihood of issues like cascading errors. Additionally, cloud infrastructure spend was disproportionate to the size of the product, running close to $8,000 per month.

New hardware, new math

The client was bringing a new device to market that paired with the user’s smartphone and measured refractive error using patented optical technology. Coherent needed to build the backend logic that would take the client's proprietary formula, apply it to raw device measurements, and return an accurate, prescription-ready result.

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What's next

Through AKTIV, Coherent’s dedicated fitness and wellness practice, the company will continue to support the client’s ongoing platform enhancements across mobile, backend, DevOps, QA, and project management. Using the same consumer healthtech context that shaped the client’s rebuild, AKTIV's engineers will also ensure the client’s hardware, app, and backend continue to evolve together as the device line matures.

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Fitness & wellness

Building a better backend to support at-home vision testing
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Our approach

As the client's partner, Coherent Solutions engineered an NLP solution that analyzes online product reviews. Aspect-based sentiment analysis makes it possible to see which product characteristics customers react to, and how, across a large set of reviews.

Cloud engineering and scalable data processing allowed the solution to handle the large volume.

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The solution

Coherent Solutions contributed:

  • AI and machine learning engineering for a natural language processing solution built on aspect-based sentiment analysis
  • Data processing designed for large volumes of customer feedback
  • Cloud engineering supporting scalable data processing


The impact

The engagement produced the following results:

  • Sentiment identified for specific product characteristics
  • Product strengths and weaknesses identified from customer feedback
  • Customer feedback processed at scale
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The challenge

Reviews often mention several characteristics of a product in the same text, each with its own opinion. An overall review score or sentiment label cannot capture that, and the client needed to know what customers thought about individual characteristics of each product.

The work covered hundreds of thousands of online product reviews, so the solution had to process customer feedback at scale.

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What's next

How we worked here is how we work on every engagement. Whatever form your data takes, we start with the questions you need answered, select the right approach, and engineer the data processing and cloud deployment so the answers are ready to be used.

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Data & Analytics

Unlocking actionable insights from hundreds of thousands of customer reviews
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Our approach

We started working on two products. The early effort went into the MVP to establish the core architecture of the customer portal, a web application for fleet managers. Our team delivered all scheduled work on time for the release, and the MVP successfully went live.

In parallel, our team carried out the analysis for the installation app, a mobile application for technicians who install batteries and related equipment on trucks and trailers. The goal of this phase was to agree on the scope for the app’s own MVP. It resulted in an approved clickable prototype of the main flow, a solution design, an approved baseline scope document, a test plan and test strategy, an estimation, and a timeline. The app’s MVP reached the App Store and Google Play.

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The solution

The customer portal grew over eleven releases, with each stage providing value to fleet managers.

MVP. A landing page with fleet-level widgets for idling hours, fuel savings and CO2 reduction, and an idling dashboard. The data comes from the manufacturer’s data platform, and sign-in is secured through single sign-on.

Fleet health. Battery status per vehicle, filtered by vehicle type and status. Detail pages cover driver response, fuel savings and CO2 reduction, and data can be exported for offline work.

Administration. Tools to manage users, clients and locations, customer configuration, a vehicle history card, and control over which data each user can see.

Alerts and reporting. Immediate actions, notifications and reporting.

The architecture was set in the MVP and will support future battery management capabilities. The same foundation will support future battery management capabilities.

The installation app gives technicians a guided workflow on a phone, and each line below shows what installers can do with it.

Guided installation.A step-by-step flow with scanning, photo confirmation and offline synchronization, available on the App Store and Google Play.

Battery tracking.Records for truck and trailer batteries and installed equipment, plus a battery swap flow that keeps the battery’s history intact.

Web version. Installation management from a browser, with region-specific battery configurations for North America and EMEA, and German localization.

 

The impact

Our client realized digital value across both products, with these results:

  • Increased visibility into fleet battery health and faster identification of battery issues
  • Enhanced fleet monitoring and reporting
  • Better administrator control over portal configuration
  • Improved customer self-service and reduced manual operational effort
  • Eliminated manual and paper-based installation processes, improving consistency and data quality
  • Increased installation accuracy through automated validation, QR and barcode scanning, and structured data capture
  • Improved traceability of batteries, installed equipment, and vehicle assets throughout their lifecycle
  • Expanded operational visibility through centralized reporting, installation tracking, and enterprise data management

The portal now scales to enterprise fleets. From the first release, the work carried a clear business impact, and this approach to closing the gap between technology investment and business outcomes is what we call Digital Value Creation.

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The challenge

The manufacturer wanted to give its fleet customers direct access to the data its batteries produce. That meant a secure and scalable portal, built on a foundation that could take new features independently, so that fleet managers could see insights about their own fleets.

The second problem was in the field. Technicians installed batteries and related equipment on trucks and trailers by hand, using paper forms, so installation records were inconsistent and hard to trace.

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What’s next

Both products continue to evolve. The customer portal roadmap includes additional analytics, parasitic draw, jumpstart tracking, and custom export. Its architecture is ready for future battery management capabilities.

The current priorities for the installation app include improving data quality through additional information about assets, tighter integration with the manufacturer’s backend systems, and new workflows for flexible battery configurations and equipment swaps. These workflows will support field services and supply chain capabilities.

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Data & Analytics

A fleet customer portal for a global battery manufacturer
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Relevant
Questions

Data governance defines who owns data, how it's classified, and what quality standards apply. Data security enforces technical controls, such as encryption and access restrictions, that protect data in accordance with governance decisions. One sets policy; the other implements it.

Mapping overlapping requirements, like data minimization and access logging, into a shared set of controls avoids building separate compliance processes for each regulation. Framework-specific requirements get layered on top of that shared foundation rather than starting from scratch each time.

 

Validating at the point of entry prevents bad data from spreading in the first place, but requires enforcement across every system where data originates. Downstream validation catches issues that made it through, despite that, so most mature approaches use both rather than relying on one.

Specific metrics, such as completeness rate, duplicate percentage, and validation failure rate by data domain, make problems traceable to a fixable cause. A single aggregate score tends to hide which underlying issue actually needs attention.

Survivorship rules define which source wins in each field based on factors such as recency, system reliability, or business priority. Without explicit survivorship logic, merges tend to produce inconsistent results depending on which system last synced.

A registry approach keeps data in its original source systems and only links related records together, which is faster to implement but leaves reconciliation logic distributed. A centralized golden record consolidates data into a single authoritative store, which requires more upfront work but gives every system a single, consistent source to query.