Next-Gen Data Quality Consulting Services
Define standards for data system management.
Get a report on current discrepancies.
Improve the quality of analytics and record the results.
for business intelligence succesfull implementation
What is included in Data Quality Consulting services?
Do you know why large companies start data projects with data quality audits? Take a look at what consulting services entail.
Data Quality Assessment
The first stage is analyzing the current state of data in the company. Consultants check:
- the completeness of records in databases,
- the compliance of formats and data types,
- the correctness of business rules,
- the consistency between systems.
The result is a report on data quality and its impact on analytics.
Data Profiling
This is a technical analysis of data structure and behavior. The following are checked:
- value distribution,
- missing fields,
- anomalies,
- atypical values,
- logical dependency violations.
The result is a statistical analysis of data that shows where exactly the problems arise.
Data Quality Rules
After the audit, a system of rules is created.
For example:
- emails must comply with the format,
- customer IDs must be unique,
- the order date cannot be later than the delivery date,
- mandatory fields cannot be left blank.
These rules become the standard for the entire data system.
Data Cleansing
If the data already contains errors, it is cleaned up. Typical tasks:
- removing duplicates,
- correcting formats,
- normalizing values,
- merging customer records.
This is the stage that directly improves the quality of analytics.
Data Quality Monitoring
Next, a control system is created. It may include:
- automatic checks in ETL,
- alerts when errors occur,
- data quality dashboards,
- regular reports.
In other words, the company receives a system for continuous data control.
Data Governance
This is the strategic level. Here, the following are determined:
- data owners,
- rules for working with data,
- processes for changing data structures,
- information management policies.
Without this, even cleaned data will degrade again after a few months.
After Data Quality Consulting...
You will have a clear data structure, fewer reporting errors, stable analytics, faster decision-making, and readiness for AI and advanced analytics.
Common data quality issues in companies
During data audits, consultants often find recurring types of errors that accumulate in systems and gradually distort analytics and business metrics.
- Duplicate records. A single customer, product, or transaction may appear in the system multiple times due to imports from different sources or manual entry. This leads to errors in CRM, incorrect sales statistics, and duplicate contacts in marketing campaigns.
- Incomplete or missing data. Some records contain empty fields: the customer's country, product category, or transaction date is missing. Such records are typically omitted from analytics or generate inaccurate reports.
- Discrepancies between systems. Data about the same transactions may differ in CRM, ERP, and BI systems. The reason is the lack of a single source of truth and incorrect integration between systems.
- Incorrect data formats. Dates, currencies, phones, or IDs are stored in different formats. This creates problems during data integration, ETL processes, and reporting.
- Logical errors in records. Data may be technically valid but contradict business logic: delivery date before order date, negative product quantity, customer without a place of residence.
- Inconsistent reference books. The same category or parameter is recorded under different names: USA / United States / US. This leads to category fragmentation and statistical distortion.
- Unsynchronized data sources. The company works with several systems — CRM, ERP, marketing platforms, and analytical databases. Integration between them often fails, and indicators begin to differ even for the same metrics.
As a result, managers see different numbers in reports and face confusion when making decisions. Data quality consulting helps synchronize indicators between systems and create a common picture of the business that can be relied on every day.
Check the quality of data in your systems
Contact Cobit Solutions to audit your data sources and identify duplicates, logical errors, discrepancies between systems, and other factors that may distort analytics.
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Why leading companies choose COBIT SOLUTIONS for data quality consulting
Our clients often order Data Quality Consulting services when reports show inconsistent figures, analytics lose accuracy, or data from different systems do not match.Â
Transforming data into business value
When data is consistent, free of duplicates and logical errors, reports begin to show the real picture of the business. Reports no longer contradict one another, and key indicators are stable. These are the solutions we offer our clients to create a reliable foundation for financial planning, sales forecasting, and strategic decisions.
Individual information quality models
Each company has its system architecture, data sources, and business processes, so there are no universal quality-control rules. An individually developed model allows you to maintain consistency of indicators across different information sources. As a result, analytical systems operate on accurate, stable data.
Compliance with regulatory requirements and security
In many industries, information management is linked to regulatory requirements and access policies. Data quality and structure control help maintain the transparency of information required for audits and inspections. This reduces the risk of reporting errors and ensures secure handling of critical data.
Analytics stability and system integrity
When information is consistent across different platforms, analytical tools work predictably and without discrepancies in metrics. This allows you to quickly find deviations, control business metrics, and maintain report stability. After working with our team, your analytics will truly become a reliable tool for business management and development.
Experience and results that our
clients rely on
Companies turn to Cobit Solutions for accurate analytics, consistent data across systems, and reliable reporting. Our approach to working with data is based on practical experience implementing analytical solutions across industries and helps build a manageable data system for businesses.
Quick start and initial results in just 2 weeks
25+ BI and Finance experts without hiring pain
Proven BI delivery for 8Â years in 22 industries
More than 70 happy clients across 5 countries
Save 35% compared to W-2 payroll or contractors
Full end-to-end delivery, from reporting to support
Need a data system you can rely on for reports and decisions? Build a stable analytical foundation for business development with Cobit Solutions.
KEY BUSINESS BENEFITS OF DATA QUALITY CONSULTING
Accurate reports and stable analytics
When data is cleaned of duplicates, omissions, and logical errors, the figures in reports no longer contradict each other. This allows managers to make decisions based on the real picture of the business, rather than assumptions.
In practice, Cobit Solutions can achieve 98–99% accuracy in reporting. This means that the risk of erroneous management decisions is reduced by almost half.
Data consistency across systems
CRM, ERP, financial systems, and analytics platforms are starting to use the same metrics. This eliminates discrepancies between departments and simplifies data management across the company.
According to Gartner estimates, companies with consistent data reduce integration costs by up to 30%. In real-world projects, report generation time can be reduced from several hours to several minutes.
Reducing operational risks
Incorrect data often leads to financial errors, inaccurate forecasts, or reporting issues. Data quality control helps reduce these risks and improve the reliability of business processes.
According to IBM, poor data quality can cost companies up to $3.1 trillion annually worldwide. Implementing control systems can reduce critical errors in financial processes by 20–40%.
Faster implementation of analytical solutions
When the data structure is organized, it is much easier to implement BI tools, automated analytics, and forecasting systems. This reduces the time to launch new solutions by an average of 25–40%.
In Cobit Solutions projects, BI solution integration has been reduced from several months to several weeks. This gives businesses a competitive advantage by providing faster access to insights.
Preparation for data scaling and analytics
According to McKinsey estimates, companies with a high-quality database implement AI solutions 2–3 times faster. In Cobit Solutions' practice, this means that customers are ready to scale without additional time and resource costs.
This reduces financial risks and increases transparency in working with information. Our database modernization services include internal requirements and external regulatory standards. This allows you to work in a controlled environment with clear rules and predictable processes.
Increasing trust in data within the company
When indicators in reports are stable and consistent, teams actively use analytics in their daily work. This creates a culture of trust in data, where decisions are based on facts rather than intuition or conflicting sources.
According to a study by Experian, more than 70% of companies consider data quality a key factor in strategic decision-making. In Cobit Solutions projects, team engagement with analytics increased by 20-30% after implementing data quality control systems.
Work with data quality consultants trusted by companies with complex analytics – from $60/hour
Develop a clear plan to improve data quality that will help eliminate reporting errors, reconcile metrics across systems, and increase confidence in business analytics.
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Next-generation technologies and tools we use in data quality consulting
Modern analytics systems require reliable data architecture, accurate processing models, and tools that ensure consistency of metrics across all business systems. We combine platforms and technologies to identify data errors, standardize information structures, and create a stable foundation for analytics.
Our technology stack for data quality assurance:
- Analytical platforms. We use Power BI, Tableau, and other BI tools to verify indicator consistency, identify anomalies, and ensure reporting accuracy.
- Data processing and transformation systems. Azure Data Factory, SSIS, Databricks, and other ETL/ELT tools enable you to standardize data from multiple sources and automate data cleaning.
- Cloud data platforms. Azure, Snowflake, and other modern platforms provide scalable infrastructure for storing and processing large volumes of data.
- Integration tools. API integrations, Airflow, and Power Automate allow us to synchronize CRM, ERP, and other enterprise systems.
- Models for checking and calculating metrics. We use OLAP models, tabular models, and DAX logic to analyze relationships among indicators.
- Data monitoring and updating systems. We established processes for regular data updates and verification using Airflow, Azure Data Factory, and other orchestrators.
If you need consulting on data quality, contact our team. We will help you build a robust data management system, improve reporting accuracy, and lay the foundation for effective analytics.
Customers Trust Our Data Quality Consulting
Cases from various industries confirm our experience and professional approach to working with data.
Healthcare
“Dobrobut” clinics network
Result:
- Clinic's directors got daily updated P&L report;
- The management uses daily dashboard with budget/actual analysis on operational indicators;
- Dashboards combine data from ERP and the Doktor Eleks medical system .
Logistics
Meest China
Result:
- Dashboards combine data from ERP and CRM;
- Routes margin is automaticaly calculated in dashboards and monitored every day by management;
- Daily generated Profit & Loss report;
Manufacturing
Steelite International USA
Result:
- Automated reporting, reducing turnaround from 10 days to overnight.
- Scaled visibility from regional to global (US, UK, Canada, Europe, Australia).
- Centralized data enabled data-driven decisions on a weekly cadence instead of monthly.
Industry-focused case studies designed for your needs
Partner with COBIT SOLUTIONS for comprehensive data quality consulting
Get a clear data quality management strategy, consistent metrics across systems, and a stable foundation for accurate analytics and management decisions.
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FAQ about data quality consulting
How do you assess our current data quality?
We audit sources, models, and reporting to determine the accuracy, completeness, and consistency of information across systems. The analysis covers data structure, transformation rules, duplicates, and errors. Additionally, we verify that the indicators in BI reports align with the financial and operational systems.
However, modernization is carried out in stages. That is, the work is structured so that the company continues to operate in its usual mode. At the same time, some data is already used in analytics, and some is still being rebuilt, but this does not stop operational activities.
How do you ensure compliance with GDPR, HIPAA, or CCPA?
We implement data management rules, access control, and personal information protection mechanisms in accordance with regulatory standards. The process includes auditing data flows, storage policies, and information processing. The system architecture supports secure handling of sensitive data.
What tools do you use for data cleansing and profiling?
We use modern ETL/ELT platforms, cloud processing environments, and profiling tools to analyze data quality. We identify duplicates, structural errors, incorrect values, and discrepancies between systems. The results of the check form the basis for further data standardization.
Can you integrate data quality control into CRM, ERP, and cloud platforms?
Yes. We integrate verification and standardization mechanisms into CRM, ERP, analytical platforms, and cloud environments. Information consistency across systems is maintained automatically, and analytics run reliably.
What ROI can you expect from improving data quality?
Companies that implement data quality control reduce the cost of manual information verification and receive more accurate reporting. In practice, a Cobit Solutions client in the retail sector reduced the time to prepare financial reports from 6 hours to 40 minutes, which saved more than 200 man-hours per month.
7 YEARS IN BUSINESS INTELLIGENCE
457
dashboards created in 2025150+
years of IT experience among employees22
data experts & BI consultants12B
USD annual revenue of clients that utilize our analytics solutions