Enterprise Data Quality Consulting Services


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When you don’t trust your own numbers, every decision slows down – and the ones you do make are a gamble. Bad data quietly drains millions through wrong calls, failed audits, and AI projects that never deliver. Multishoring is the data quality consulting partner enterprises bring in when the reports stop being believable – when Sales, Finance, and Operations each show up with a different version of the truth. We turn fragmented, error-prone data into a trusted, audit-ready corporate asset your leadership can decide on.

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Executive data trust snapshot

Data Quality Consulting Services

When you don’t trust your own numbers, every decision slows down – and the ones you do make are a gamble. Bad data quietly drains millions through wrong calls, failed audits, and AI projects that never deliver. Multishoring is the data quality consulting partner enterprises bring in when the reports stop being believable – when Sales, Finance, and Operations each show up with a different version of the truth. We turn fragmented, error-prone data into a trusted, audit-ready corporate asset.

Boutique data quality & governance specialists | 40+ enterprise clients | Avg. 60% reduction in manual data corrections

What we deliver

  • Enterprise data quality assessment and profiling
  • Data cleansing and remediation programs
  • Master data standardization and golden records
  • Automated validation pipelines
  • Governance frameworks and quality dashboards

When leadership engages us

  • Conflicting reports across departments
  • Customer or product data duplication
  • Compliance and audit exposure risks
  • Manual spreadsheet corrections at scale
  • Failed analytics or AI initiatives

How we make it work

  • Microsoft Purview and Azure Data Factory
  • Power BI quality dashboards
  • Databricks and Spark profiling
  • dbt and Great Expectations
  • MDM solutions (Profisee, Informatica)

Business Outcomes of Enterprise Data Quality

Reporting your leadership can finally trust, and far less regulatory exposure. A governed data foundation that supports strategic growth and confident, evidence-based decisions.

Operational Impact of Automated Data Quality Controls

Automated quality controls and standardized master data replace endless manual correction cycles. Errors are caught before they reach the business, not after they’ve skewed a report.

Multishoring’s data quality consulting establishes the governance, cleansing, and validation frameworks that keep enterprise data accurate, compliant, and decision-ready – turning a costly liability into a trusted corporate asset.
BUSINESS IMPACT

Is Bad Data Quietly Holding Your Business Back?

You Can’t Trust Your Own Reports

When every department walks into the meeting with different numbers, strategy stalls. If you’re deciding on gut feel because the dashboard looks off, that’s not caution – it’s a data quality crisis paralyzing leadership.

Bad Data Is Hurting Your Customers

Duplicate records and missing details turn into the errors that get noticed – the wrong client billed, the wrong name on a campaign. Poor data quality doesn’t stay internal; it reaches your customers and chips away at your brand.

You’re Paying Analysts to Scrub Spreadsheets

Your most expensive people spend hours cleaning data by hand instead of analyzing it. This “hidden factory” of manual correction quietly drains your budget, your operational capacity, and your team’s morale.

Every Report Is a Compliance Risk

Inaccurate data isn’t just inconvenient – it’s exposure. Whether it’s GDPR, HIPAA, or financial reporting, data quality issues lead to failed audits, fines, and legal risk that lands on the C-suite.

Your AI Strategy Can’t Get Off the Ground

You’re ready to invest in AI, but your models are only as good as the data feeding them. Without clean, trusted data underneath, your analytics and AI projects will stall and fail to return the investment.

OUR PRINCIPLES

Our Approach – Turning Data Liability Into Asset

Data quality isn’t a technical ticket to close – it’s a core business discipline. Our data quality consulting is built on three principles that deliver results your entire leadership team can measure and trust.

01

Value-First Prioritization

We don’t try to “boil the ocean” and fix every trivial error. We target the critical data elements that move your revenue, compliance, and board-level reporting – and put our effort where it delivers the highest return, not the longest error list.

02

Prevention First

Cleaning data is an expense; preventing bad data is an investment. We move you from a reactive “fix-it” cycle to a proactive governance model, with automated quality gates that stop errors at the source before they ever reach a decision.

03

Business-Led Ownership

Data quality can’t live with IT alone – most bad data starts as a business process, not a technical bug. We give your business leaders ownership of their data, with the definitions, roles, and accountability that keep it trusted long after our engagement ends.

FULL-CYCLE CAPABILITIES

From Diagnosis to Sustainable Data Health

We don’t just find the problems. We fix them, and make sure they stay fixed.

Plenty of consultants will hand you a report listing your data errors and wish you luck. We pair strategic advisory with hands-on execution. Whether you need a corporate governance policy defined or millions of records physically cleansed in your ERP, we own the entire data quality remediation lifecycle.

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Strategy & Governance Framework

We set the “rules of the road” for your organization – defining data standards, assigning ownership roles, and putting in place the policies that make accountability stick across the business.

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Deep-Dive Audit & Profiling

We look past the symptoms. Our data quality assessment profiles your data to find the root causes of the errors – and puts a dollar figure on what bad data is costing your operations.

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Remediation & Cleansing

This is the heavy lifting – fixing the historical data itself. From de-duplicating customer records to standardizing product codes, we get your baseline data accurate and ready to use.

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Automated Quality Firewalls

We build validation rules and automated workflows that block bad data at the door, stopping the “garbage in” cycle for good instead of cleaning up after it again next quarter.

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Culture & Enablement

Tools alone won’t solve this. We train your teams and internal “Data Stewards” to hold the quality standards, so accurate data becomes something the whole organization owns, not just IT.

We take full ownership of the problem, from diagnosing the root cause to engineering the permanent solution – delivering a governed data foundation you can finally trust.

OUR STEPS

A Proven Path to Trusted Data

Discovery & Impact Analysis
We start with your business goals, not your database. We assess the current state of your data, pinpoint the pain points that hurt most, and put a number on what poor data quality is costing your operations and decisions.
Outcome:
A clear, objective read on your data health, and a prioritized business case showing exactly where fixing data returns the most ROI.
Strategy & Rule Design
We work with your business stakeholders to define what “good data” actually means for you. Together we set the specific quality rules, metrics, and governance policies your industry requires.
Outcome:
Documented standards and a governance framework that aligns IT execution with business expectations – no more ambiguity over whose definition is right.
Remediation & Cleansing
This is the execution phase. We combine automated tooling with expert teams to cleanse historical data – removing duplicates, filling gaps, and standardizing formats across your systems.
Outcome:
An immediate, measurable jump in data accuracy. Teams stop firefighting spreadsheets and start trusting the reports they produce.
Automation & Prevention
To make it last, we build validation rules directly into your pipelines and entry forms. This “firewall” stops bad data from ever entering your systems again.
Outcome:
A shift from reactive cleaning to proactive prevention. Operational efficiency climbs as the flow of bad data is permanently cut off.
Monitoring & Sustainment
We stand up real-time quality dashboards and assign Data Stewardship roles, then give your team the training and tools to track data health as an ongoing KPI.
Outcome:
Lasting confidence. Data quality becomes a sustainable discipline, keeping your foundation for AI and analytics solid.
Discovery & Impact Analysis
We start with your business goals, not your database. We assess the current state of your data, pinpoint the pain points that hurt most, and put a number on what poor data quality is costing your operations and decisions.
Outcome:
A clear, objective read on your data health, and a prioritized business case showing exactly where fixing data returns the most ROI.
Strategy & Rule Design
We work with your business stakeholders to define what “good data” actually means for you. Together we set the specific quality rules, metrics, and governance policies your industry requires.
Outcome:
Documented standards and a governance framework that aligns IT execution with business expectations – no more ambiguity over whose definition is right.
Remediation & Cleansing
This is the execution phase. We combine automated tooling with expert teams to cleanse historical data – removing duplicates, filling gaps, and standardizing formats across your systems.
Outcome:
An immediate, measurable jump in data accuracy. Teams stop firefighting spreadsheets and start trusting the reports they produce.
Automation & Prevention
To make it last, we build validation rules directly into your pipelines and entry forms. This “firewall” stops bad data from ever entering your systems again.
Outcome:
A shift from reactive cleaning to proactive prevention. Operational efficiency climbs as the flow of bad data is permanently cut off.
Monitoring & Sustainment
We stand up real-time quality dashboards and assign Data Stewardship roles, then give your team the training and tools to track data health as an ongoing KPI.
Outcome:
Lasting confidence. Data quality becomes a sustainable discipline, keeping your foundation for AI and analytics solid.
Our Technology Expertise & Capabilities

Enterprise-Grade Tools for Trusted Data

We leverage the most robust platforms in the industry to secure your data foundation. While our primary focus is the Microsoft Azure ecosystem, we are fully equipped to handle multi-cloud environments (AWS, Google Cloud) and modern data stacks.

Unified Governance (Purview) 

We use Microsoft Purview (and alternatives like Collibra or AWS DataZone) to create a holistic map of your data estate. This establishes the strategic framework, identifying where sensitive data lives, visualizing lineage, and enforcing quality policies across the organization.

Profiling & Discovery 

Before fixing data, we must understand it. We use tools like Azure Databricks and AWS Glue DataBrew to statistically scan your datasets. This deep profiling uncovers hidden anomalies, pattern inconsistencies, and “quality hotspots” that manual checks miss.

Automated Cleansing (ADF) 

We don’t just patch errors; we build automated remediation pipelines. Using Azure Data Factory, Azure Functions, or Spark, we implement scalable business logic that standardizes formats, enriches records, and deduplicates data as it flows through your system.

Master Data Management (MDM) 

To solve the “multiple versions of the truth” problem, we implement MDM solutions like Profisee (optimized for Azure) or Informatica. We help you create a single, authoritative “golden record” for critical entities like Customers and Products.

Quality Dashboards (Power BI) 

We make data health visible to the business. We build dedicated Power BI dashboards that track key quality metrics (completeness, accuracy) over time. This provides leadership with a clear, ongoing view of data reliability and ROI.

Pipeline Validation (dbt) 

For modern data stacks, we implement “Quality as Code.” Using tools like dbt and Great Expectations, we write automated tests that validate data integrity at every step of the pipeline, stopping bad data before it ever reaches your reports.

We Make Data Quality Visible and Measurable

You can’t manage what you don’t measure. We implement executive dashboards that give you a real-time view of your data health. We translate technical error counts into business-relevant KPIs.

Executive Data Health Overview

Scope: Enterprise Master Data

System Healthy
Trust Score Improvement (6 Months)
Quality by Data Domain
Automated Action System Source Impact Status

See Where Your Data Is Costing You - in 30 Minutes

Let’s talk about the gap between the data you have and the data your business actually needs. In a short, no-obligation strategy call, we’ll assess your current data maturity and hand you a prioritized action plan to restore trust in your numbers. No pitch, no commitment – just a clear read on where your biggest data risks are and what to fix first.

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    FAQ

    Frequently Asked Questions about Data Quality Consulting

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    Why can't our internal IT team simply fix the data?

    Because it’s usually not a technical bug – it’s a business process problem. IT keeps the “pipes” running; they’re not built to police how Sales enters a record or how Finance defines a metric. Most bad data starts in the process, not the system. We bring the cross-departmental authority and the frameworks to fix the root cause, which is often political or procedural rather than technical.

    What is the typical ROI of a data quality engagement?

    It shows up in three places: operational efficiency (recovering the 20-30% of time teams lose to manual fixes), revenue protection (fewer billing errors and lost leads), and risk mitigation (avoiding compliance fines). We typically target a 30-40% reduction in data-related operational costs within the first year.

    How long does it take to see results?

    Full governance maturity is a journey, but you won’t wait a year to see value. In the initial Discovery and Remediation phase – usually 4 to 6 weeks – we bulk-cleanse the errors hurting your reporting most. Most clients see a real jump in data trust within the first quarter.

    Do we need to switch platforms to work with you?

    No. Our approach is to get more out of what you already own. We work across the Microsoft stack, AWS, Snowflake, and modern data stacks, and we implement quality rules inside your current architecture. We only recommend a new tool if your existing stack genuinely can’t meet your governance requirements.

    Our customer data is inconsistent across Sales and Finance systems. How do we fix this "Single View" problem?

    This is a classic master data management (MDM) challenge. When data lives in silos, you get duplicates and conflicting records. We fix it with a “golden record” strategy – one authoritative source for critical entities like Customers and Products that pushes validated data back to every operational system, so everyone finally sees the same numbers.

    We're planning a major migration (cloud or ERP). Should we clean the data before or after?

    Always before. Migrating bad data is one of the top reasons ERP and cloud projects blow their budget and miss ROI. We run a data quality health check and remediation before the migration starts, so you only pay to move accurate, valuable data – and carry far less risk into the new environment.

    Our BI dashboards are unreliable because of missing or incomplete data. Can you help?

    Yes – this is the classic “garbage in, garbage out” problem. Null values and bad formatting mean your dashboards quietly lie to you. We trace the errors back to the source and add automated validation and enrichment, so your BI tools are fed complete, certified data you can actually decide on.

    How does poor data quality affect our regulatory compliance (GDPR, HIPAA, ESG)?

    It creates real legal risk. If duplicates stop you from accurately identifying a customer record, you can’t reliably honor “right to be forgotten” requests under GDPR. If your reporting data is flawed, your financial or ESG disclosures can be wrong. We put governance frameworks in place that keep your data accurate, traceable, and compliant with international regulations.