Frequently Asked Questions

The timeline depends on the scope of functionality, design, number of integrations, and content readiness. A simple MVP can be launched in as little as 1–3 months, while complex e-commerce systems with multiple roles, dashboards, and external services require more time for development and testing. Typically, it's best to launch a project in phases: first a basic version for sales, then add advanced features.

The cost of creating an online store depends on the catalog size, design, business logic, number of user roles, and required integrations with CRM, ERP, payment systems, inventory, and delivery services. Therefore, the price for developing an online store is determined after evaluating the specific project and its requirements.

Contact us to receive a preliminary estimate for your e-commerce project.

IWIS builds digital products around specific business needs: web portals, mobile apps, automation and BI analytics systems, and e-commerce platforms. We also provide consulting services for cases where you first need to figure out which direction to take and whether anything should be built at all.

Our clients include international brands, retail, manufacturing companies, and even the public sector. In every project we immerse ourselves in the business context and find the optimal solution.

Power BI in simple terms is a Microsoft platform that collects data from different systems and turns it into interactive reports and dashboards. It helps you quickly see the key metrics and the reasons they changed.

In Kyiv, but the team is distributed, and most of our processes have long been built without being tied to a single city or office. Our clients are based in Ukraine, Europe, the US, and Canada, and we work with all of them without losing communication quality — we simply adapt our rhythm to the time zone.

Power BI is used to analyse sales, finance, marketing, inventory and operational processes. It allows a company to automate reporting, keep track of KPIs and drill metrics down to an individual product, region or manager.

In 2017. We have delivered 90+ projects in industries that, at first glance, do not have much in common. But every time, the main question in front of us was the same: how to make technology solve a real business problem. Our experience allows us to quickly grasp new contexts and avoid wasting the client's time.

Yes. Power BI Desktop can be used free of charge to build reports, and the Fabric Free licence suits personal work in the service. Standard sharing requires Pro or PPU. Free users can also view content hosted on a Fabric F64 or larger capacity if they have been granted the relevant access.

Mostly the B2B segment: finance, retail, manufacturing, distribution, pharmaceuticals, e-commerce, media, and government institutions. Among those we have already worked with: British American Tobacco, Planeta Kino, GoodWine, Helen Marlen, Skarbnytsia, Nazovni.Online. We are equally comfortable taking on large corporate projects with complex infrastructure and mid-sized businesses where speed and a clear focus on results matter most.

Power BI Desktop is designed for preparing data, building models and creating reports. Power BI Service is used to publish them to the cloud, refresh them automatically, collaborate and manage access.

If there is a clear understanding of the task, we can start within days — as soon as the key parameters are defined, a team is assembled and the Discovery phase begins. If the request is still taking shape, we start by working together to understand what needs to be done and in what order.

For learning and local work the free Desktop is enough. Pro suits teams that need to publish and view reports together. PPU is chosen for personal access to Premium features, and Fabric capacity for dedicated resources or a wide audience.

Usually with a conversation. A short call or a free workshop where we break down the task and the business context together. What happens next depends on the request: a one-off consultation, an audit of an existing solution, or a full development kickoff.

Roughly, it looks like this: introduction and discussion of details → context analysis → agreement on the collaboration format → NDA signing if needed → start according to the agreed plan.

It is important to us that both sides understand what is happening before any work begins.

The best way to start is with a specific task and a small dataset. Connect an Excel file in Desktop, clean the data with Power Query, create a few basic measures and build your first Power BI report. This approach helps you grasp the logic of the platform faster than working through all its features one by one.

At the start, we agree not only on the scope of work but also on success metrics, areas of responsibility, and the communication rhythm. A team with relevant experience is assembled for each project. Throughout the work we hold regular meetings and provide reports, and every important point is documented. If something changes, we trigger a managed replanning process.

It is the infrastructure that collects data from all of a company's systems – CRM, ERP, advertising, warehouse – brings it into a single format and makes it available for analytics and automated decision-making. It is not a single database, but a combination of sources, storage, a processing layer and analytics tools that work as one whole.

Google Meet, email, messengers, and Jira for task tracking. If the client already has their own system — no problem, we integrate into it. If not, we suggest a convenient format and explain how it works. At any point, the client knows what stage the project is at and what will happen next.

Without one, departments calculate the same indicators differently and decisions are made on the basis of inconsistent figures. A unified data platform gives the whole company a single version of the truth: marketing, sales and finance see the same metrics, calculated with the same logic.

If priorities shift or new requirements appear during the work, we first assess how this affects the timeline, budget, and current scope.

Then, together with the client, we decide what is worth adding now and what is better to move to the next phase. This way, the project does not fall apart with every new idea, and changes remain manageable.

A data warehouse stores structured data in a fixed schema and suits financial reporting and well-defined BI dashboards. A data lake stores any data in raw form: files, logs, unprocessed datasets, and is better suited to large-volume analytics and ML models, where the structure is not known in advance.