Frequently Asked Questions

BI is about real-time visibility: dashboards, reports, metric control. Business analytics is about analyzing causes, forecasting, and scenario modeling. Conventionally: BI shows profit dropped in September, analytics explains why, what happened to customer behavior, and how to fix it. We usually combine both approaches.

Not necessarily. If you have Microsoft 365 – we can implement basic BI in Power BI without extra costs. For custom analytics – we build a turnkey web platform.

Yes, we train teams to work with their real dashboards: how to filter, interpret, what each metric means. Format depends on needs: from instructions to live sessions with an analyst.

The first analytics work block typically takes 6-10 weeks from the start of diagnostics to dashboard launch. Full implementation with all blocks (finance, sales, operations) takes an average of 3-5 months depending on the number of data sources, the state of current systems, and client priorities. The phased approach allows you to see initial results before the entire project is completed.

The BI system is built on top of the existing infrastructure: it connects to ERP, CRM, and accounting systems and retrieves data from them through integration. There is no need to replace or abandon current systems. On the contrary, they become the sources for a unified analytical environment.

At minimum, one relevant representative from the client side: a financial director or head of the respective department to validate business logic. Participation is required at specific points: during requirements alignment sessions and results verification. IT resources are only needed to provide system access.

A modular approach is standard practice. We begin with the module where there is the greatest management pain point or the highest value from quick results. Financial analytics, sales analysis, or the operational module—any of them can be launched first, and then the system can be scaled up.

After system handover, we can provide support: technical, analytical, and consulting. When business logic changes or new tasks arise, the system is updated within the SLA framework.

The analytical model is developed according to the specific client's business logic. The approach works regardless of industry: retail, distribution, manufacturing, agriculture, services. There are no ready-made templates for everyone; everything is built around the company's real management tasks.

For one-off projects, we include a technical support period for stable operation. If the BI system updates ongoing – we can provide continuous maintenance. For example, add new metrics, adjust dashboards, scale structure. We stay in touch for new questions or ideas.

Yes. We connect CRM, ERP, databases, Excel, Google Sheets, third-party APIs. If you already have internal dashboards, we can implement new ones in the same ecosystem. We've worked with both modern products and legacy on old platforms. The key is that the system truly works in your business context.

Yes. Not every employee should see all salaries, financial flows, or margin percentages. We configure access by roles, locations, departments, or even specific metrics. For example, a regional manager sees only their sales points, top management – the overall picture. This is standard for responsible analytics.

ETL is Extract, Transform, Load: pull data, clean it, and load into the analytics environment. In most BI projects, ETL is essential to avoid charts on skewed or outdated data. We build custom pipelines or use ready tools if volume and complexity allow. Good ETL is like a restaurant kitchen: you don't think where the dish came from – just get the clean result.

Yes, if it makes sense for the task. Data from CRM, ERP, websites, or mobile apps can flow into the BI system with minimal delay. But understand: not all metrics warrant minute-by-minute updates. Some are better aggregated hourly or daily, and we always explain where real-time pays off and where it just raises costs without value.

We start with security, not end with it. We treat data as an asset protected at all levels: from storage to access. If analytics shows profits, salaries, conversions, stock levels, or personal data – these figures can't float uncontrolled in tables. We implement clear roles, restrict field and source access, isolate environments. In complex cases, add encryption, multi-factor authentication, action audits. Security supports BI use, not complicates it. You control who sees what and what they do with it.

Yes, of course. Every business has its logic, and standard templates often provide no value. We design dashboards understanding who will use them and why: for CEO, marketing, logistics, or production. They can even be role-specific panels.

This is a standard situation, and we don't require perfect data order before starting. On the contrary, we help identify what can be salvaged, normalized, cleaned, or supplemented. Often we show exactly which data is missing for the needed insights. After that, the company starts collecting and storing info better, seeing its impact on strategic decisions.

Practically any: CRM, ERP, marketing platforms, websites, Google Sheets, databases, third-party APIs. Our task is to make data collect automatically, without manual intervention, with clear logic.

From 3 weeks to several months, depending on complexity and your data state. If structured sources and clear specs already exist – we can quickly assemble an MVP with basic dashboards.

Data alone gives nothing. But properly presented information speeds up decisions, reveals problems, and shows growth points. BI lets you focus on profitable directions and optimize costs. For example, you see conversion dropped in one region and launch a new strategy test within an hour.