Next-Gen Data Science Consulting Services for Business Growth
Test hypotheses faster by relying on predictive models and algorithms rather than intuition.
Spend less resources on experiments, testing, and process iterations.
Scale solutions without rebuilding systems, while maintaining control over business growth.
for business intelligence succesfull implementation
COBIT SOLUTIONS is the Data Science Consulting Company Enterprises Rely On
We work with tasks for which standard analytics are not suitable. We develop complex models, create AI solutions for R&D, and optimize engineering and manufacturing processes.
From numbers to results, data to decisions
Data science consultancy is necessary for businesses when it is important to use data as a basis for strategic decisions and competitive advantage. Our team analyzes operational and financial information in conjunction and models development scenarios. This allows us to see problems and points of influence that are not apparent in standard reporting. In particular, in one project for a financial company, combining operational metrics and financial flows revealed internal fraud amounting to UAH 500,000 per month. The difficulty, which had existed for over a year, was detected within the first month after the implementation of analytics.
Industry-Specific AI & ML Models for Future-Ready Businesses
In industry projects, it is significant to understand how results are formed within processes, rather than just looking at the final figures. We work with data in such a way that it is clear where costs begin to grow faster than sales and why. In a manufacturing project, this became clear at the analytics design stage: P&L analysis showed that general production costs were growing faster than sales. Adjusting the control approach resulted in an effect of about 2% of turnover.
Ethical, Transparent, and Accountable Data Science Practices
When data is used for management decisions, it is important to understand where the figures come from and whether they can be trusted. We structure our analytics so that each indicator has a clear source, calculation logic, and verifiability.
In a project for a large retail chain, this made it possible to replace manual report preparation, which took up to two hours every day, with automatic reporting that is updated instantly. Management received a single version of the data, and analytics ceased to depend on human factors and errors in files.
Linking Strategy, Technology, and Scalability for Success
We approach analytics as a long-term management tool, not a one-time project “for reporting.” Our consultants design solutions so that they can be expanded along with the business — adding new stores, directions, data sources, and users without reworking the entire logic. Once, we launched analytics for several of the owner's retail outlets, and later connected 100+ stores in several regions. The architecture was not changed, and scaling did not require stopping operations or rebuilding the analytics system.
Our Core Data Science Consulting Services
We get involved when a business needs results, not just another analytical system or report. In our practice, data processing consulting directly influences management decisions, financial indicators, and business controllability.
End-to-End Data Planning with Implementation Roadmaps
- Get a clear understanding of what data your business really needs.
- See the sequence of steps without unnecessary costs and risks.
- Determine what to do now and what can be postponed.
- Avoid chaotic implementations and rework.
- Control deadlines, budget, and expected results.
Machine Learning Model Integration & Ongoing Support
- Use models that work in real business processes.
- Get consistent results without manual adjustments.
- Reduce dependence on individual specialists.
- Keep models up to date as your business changes.
- Focus on solutions, not technical details.
Predictive analytics for strategic growth
- Track future risks before they become problems.
- Assess the consequences of decisions before they are implemented.
- Plan resources based on scenarios, not assumptions.
- Make strategic decisions based on calculations.
- Move from reaction to proactive management.
AI automation for cost savings and efficiency
- Reduce manual work and operating costs.
- Reduce errors in calculations and reports.
- Speed up data processing without expanding your staff.
- Get repeatable and controllable results.
- Invest in solutions that quickly pay for themselves.
Data reliability, control, and compliance certification
- Clearly understand the origin of each indicator.
- Control the logic of calculations and changes in it.
- Reduce the risk of management errors.
- Increase management confidence in analytics.
- Prepare the system for audits and scaling.
Sustained support and system refinement
- Work with analytics that evolve alongside your business.
- Adapt solutions to new tasks without interruption.
- Receive expert support without losing context.
- Avoid system degradation over time.
- Maintain manageability and investment value.
Core Business Advantages of Data Science Consulting
In the data science consulting business, value is determined by how quickly a company can derive insights, optimization, and competitive advantages from data.
Unlock Hidden Value from Your Data Assets
Data often exists in a company but does not function as an asset. Consulting reveals where information is not being used, is duplicated, or distorts the real picture. Businesses stop losing money due to false indicators, manual corrections, and “averaged” figures. A clear understanding emerges of which data affects the result and which only creates noise. This is how a structured approach to data transforms information into a manageable resource.
Execute Data-Driven Strategies with AI & ML Intelligence
Strategies often remain at the level of declarations if there are no tools to verify them. Analytical and predictive models allow you to assess the consequences of decisions even before they are implemented. Businesses can see which scenarios work and which lead to losses. This removes dependence on the intuition of individuals and reduces the risk of strategic errors. This is precisely why companies order data science services consulting, rather than to create “yet another BI system.”
Boost Performance Through Smart Automation & Analytics
Manual calculations, Excel, and endless reconciliations consume time and create errors. Automating analytics removes the human factor from critical calculations. Teams stop wasting resources on data preparation and start working with results. Decisions are made faster, without delays or repeated recalculations. This change in approach increases productivity even without increasing staff.
Build Trust with Secure, High-Quality, Compliant Data
When management does not trust the numbers, management stops. Clear origin of indicators, control of calculation logic, and compliance with requirements eliminate doubts about the accuracy of data. The business receives a single version of the truth that can be worked with at all levels. This reduces management risks, simplifies audits, and allows analytics to be scaled without losing trust.
Hire an Experienced Data Science Consultant Starting at 50 USD/h
Pay for control and predictability, rather than waiting until mistakes become truly costly.
Next-Gen Technologies and Tools We Use in Data Science
Without reliable technology, forecasting doesn’t work. Our stack allows you to build complex models, quickly update forecasts, and stay in control as your business grows.
We use the following tools in our work:
- Analytical and BI platforms — for scenario analysis, forecasting, and combining models with business logic. Power BI and tabular models allow us to visualize the consequences of decisions and work with multidimensional calculations.
- Data processing and transformation systems — for preparing information for modeling. Azure Data Factory, Databricks, and Spark provide stable pipelines, incremental updates, and work with large data sets.
- Cloud infrastructure and computing environments — for scaling models and fast calculations. Azure, Databricks, and Spark allow us to maintain performance as the load increases.
- Performance measurement and business logic models — for implementing scenarios, dependencies, and complex financial and operational calculations. DAX, SSAS Tabular, and SQL are used as the semantic layer.
- Data source integration tools — for collecting information from ERP, CRM, marketing platforms, and external services into a single analytical system.
- Automation and regular updates — for stable forecasting. Orchestration in Azure Data Factory, Airflow, and Databricks ensures automatic recalculation and change control.
Order data science consultations to work with accurate scenarios, keep your business under control, and make optimal decisions in advance.
Clients Value Our Data Processing Consulting Firm
We provide consultancy in data science that help businesses work with forecasts, scenarios, and complex dependencies in practice. Clients choose us for our practical results in complex environments. We have implemented hundreds of analytical solutions in more than 20 industries: finance, retail, distribution, manufacturing, medicine, and fintech. We work with forecasting demand, revenue, costs, and risks in systems with millions of records, where a mistake in the model directly affects money.
Trust is built through numbers and consistent results. Our solutions are used by companies with a combined annual turnover of billions of dollars, which confirms their economic efficiency. The team combines expertise in analytics, finance, and technology: Power BI, Azure, modern BI platforms, and forecasting tools. This combination allows us to quickly scale forecasting algorithms and implement analytics as a working management mechanism.
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
Simpatik – cosmetics factory
Result:
- Integrated Power BI with ERP. The volume of the ERP database for analytics is 800 GB per year.
- We created a data mart and implemented the calculation of the main analytical metrics on DAX
- Connected Excel with Power BI data model in Azure Analysis Services.
Industry-focused case studies designed for your needs
The Results That Businesses Get From Consulting Data Science
Looking for an expert who doesn’t just build analytics, but influences money, control, and manageability? Our data processing consultants work with management decisions, not abstract reports — and the numbers prove it.
☑️ Analytical solutions support over $12 billion in annual customer turnover — forecasts and scenarios are directly used in financial planning and operational management.
☑️ Over 70 clients in 5 countries — working with different industries, business models, and levels of management maturity.
☑️ Over 15 years of experience in analytics and IT — each solution is based on the practice of complex business systems, not templates.
☑️ Consulting is on average 25% more effective than maintaining your own analytics team — access to expertise without ongoing staffing costs.
☑️ 457 dashboards implemented per year — rapid implementation of analytics without compromising data accuracy and quality.
☑️ Our own team of 25 specialists — full responsibility for architecture, calculations, and results, without outsourcing work to contractors.
Need control, predictability, and decisions you can trust? Order data sciences consulting and build an analytics system that provides support for planning, risk management, and financial stability for your company.
Turn Analytics Into a Management System with Cobit Solutions
Our approach combines data, models, and business logic into a single system that allows you to quickly see the consequences of each management step.
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FAQs Data Science Consulting Services
How does data science consultancy give businesses a competitive edge?
In short: you make decisions before the problem or opportunity becomes apparent. We build analytics to answer the question “what to do next,” not just to record the result after the period ends. In the distribution case, this allowed us to see how costs were growing faster than sales, even at the planning stage, rather than in the annual P&L. In e-commerce and infobusiness, traffic analytics showed channels with a ROMI of over 450%. At the same time, managers identified tens of thousands of dollars in wasted spending. The competitive advantage here is that you change course in advance, rather than reacting when the room for maneuver has already narrowed.
Which industries do your data science consultants specialize in?
We have worked with retail, financial companies, manufacturing, distribution, pharmaceuticals, IT, and service businesses. Experience has shown that the logic of data in finance, retail chains, and manufacturing is different. We now take this into account. In fashion retail, for example, seasonality is more important than average indicators. In microcredit, customer behavior is more important than a beautiful display of reports.
How long does it take to implement a data science strategy?
The duration depends on the complexity of the task, the state of the data, and the level of integration with business processes. In practice, there are projects where the first solutions are launched within 2–3 weeks. Therefore, the first management insights usually appear immediately after implementation. A full-fledged system can take months, not days, to build. For example, we once identified a critical problem at a financial company in the first month, even though it had been “living” for over a year.
What level of data readiness is required to get started?
Not perfect. And that’s good news. If the data is in Excel, CRM, accounting systems, internal databases, or even in the form of scattered files and tables, that’s enough to get started. We regularly get involved in projects where the owner says, “We don’t have much data here, but we need a solution right now.” We work with what we have, put things in order as we go, and don’t wait for the mythical “perfect state.”
Do you provide post-launch data science management consulting and scaling support?
Yes, and this is where it gets interesting. After launch, businesses usually want more: new metrics, different scenarios, expansion into networks, regions, or new areas. In retail, we scaled analytics from a few stores to over 100 locations without interrupting operations. Our task is to ensure that the system does not break down with every change but develops along with the business.