We connect data from ERP, CRM, applications, and spreadsheets, align metric definitions, and build analytics for management, finance, sales, and operations. We start with a specific problem: manually combining sources, working from a ready Excel file, or using a BI environment that users no longer trust. We work with Power BI and Microsoft Fabric, Tableau, Snowflake, Alteryx, Databricks, and Qlik Sense, while our DataFlow product organizes data preparation.
You do not need to know the target architecture or choose a platform. It is enough to identify the way of working with data that is blocking a decision.
DataFlow automates and controls data flows from ERP, CRM, databases, APIs, and files to Power BI, Tableau, or Excel. Logic, tests, and dependencies remain transparent, while AI suggestions go through validation and approval.
Explore DataFlow →BI Quick Start answers one business question. The deliverables include 5–10 KPIs, one management view, an optional diagnostic view, a basic model, a presentation of the result, and a recommendation for the next step—without building an extract, transform, and load (ETL) process.
Discuss BI Quick Start →BI Optimization Assessment identifies whether performance, architecture, data quality, report adoption, or governance should be addressed first. The deliverables include a risk map, priorities, and a change plan.
Explore the BI assessment scope →If the data for BI Quick Start requires integration or manual organization of multiple sources, we first implement DataFlow or a solution tailored to those data sources.
We also embed reports in specific processes: explore invoice workflow and cost analysis, as well as sales, orders, and customer service.
We implement new solutions, develop existing environments, and organize the data path from source to report. We select technology based on architecture, users, security, and the maintenance model.
We implement and develop Power BI reports, semantic models, integrations, and permissions. We prepare data in the Microsoft Fabric ecosystem, organize the publishing process, run migrations, and maintain production environments.
See Power BI →See Microsoft Fabric →
We implement Tableau Server and Tableau Cloud, design dashboards, and prepare data sources and models. We develop environments, organize reports and permissions, improve performance, and take over maintenance.
See Tableau →
We design and develop the data layer used by teams and analytics tools.
See Snowflake →
We develop and organize Alteryx workflows that prepare data and automate repeatable analyses. Our DataFlow is an alternative; we also offer Alteryx clients a migration to DataFlow or KNIME.
See Alteryx →
We build pipelines and a data layer for analytics and AI solutions, with monitoring and connections to BI tools.
See Databricks →
We develop models, reports, and integrations, improve performance, and maintain existing Qlik environments.
See Qlik Sense →Other technologies: we maintain informational pages about Looker Studio and Google Data Studio, Amazon QuickSight, and the R language.
Published references cover data integration, BI platform implementations, report development, and work with business users.
“Astrafox delivered and successfully implemented a Business Intelligence solution based on the Tableau ecosystem in our organization. […] The implemented solution made it possible to integrate data distributed across the organization, accelerate analytical and reporting work for business users, and reduce the IT department’s workload by decreasing its involvement in preparing data sources and reports for the company’s business departments.” (translated from Polish)
“Astrafox Sp. z o.o. delivered Tableau Prep training and developed analytical reports for the organization. The cooperation proceeded without issues, and we rate the quality of the services very highly. The consultants’ experience and skills enabled effective project delivery. The employees use the latest technologies and have expert knowledge and many years of experience, as we saw during our cooperation.” (translated from Polish)
“[…] Astrafox Sp. z o.o., based in Warsaw, increased adoption of Alteryx during its implementation in the company. It trained our users to build data models in Alteryx. The Alteryx BI solution accelerates data preparation for analysis and advanced analytics in the organization. Designed primarily for business users, it is simple and flexible and gives users freedom to clean, combine, and analyze structured and unstructured data from any source. The service was delivered without issues and according to the agreed schedule.” (translated from Polish)
In data and BI, we work with companies including Allegro, Polkomtel, Novartis, Grupa Pracuj, DPD Polska, and Candid Group.
We migrate solutions between technologies, develop production environments, and take responsibility for their maintenance. Each service is described in detail on a separate page.
We migrate valuable reports, models, and data preparation processes, including from Alteryx to Microsoft Fabric. We audit the existing logic, map dependencies, recreate schedules and quality controls, and validate results before and after the change.
See migrations →We monitor the environment, fix errors, develop reports and data flows, and deliver an agreed backlog of changes. We support administrators, add sources, improve performance, and clarify responsibility for development.
See BI development →We define ticket categories, response times, contact channels, and rules for further solution development. A dedicated team knows the environment, manages tickets, supports administrators, and delivers minor enhancements.
See SLA support →A dashboard is one stage of the work. Value comes from the entire chain: decision, data, model, analysis, action, and maintenance.
We connect sources, control quality, align definitions and KPIs, and design the model, automation, permissions, governance, and data readiness for AI. This lets the team trace a result back to the rule and source instead of manually comparing more spreadsheets.
We design analysis around the decision, user, and context of a variance—not as a catalog of available visualizations. The user sees the appropriate level of detail, the metric definition, and a path to the data explaining the result.
We define the environment owner, monitoring, performance, security, change backlog, and maintenance model. The report remains part of the decision-making process rather than a one-time project with no accountability after launch.
We first organize metric definitions, sources, and permissions. Then we configure existing models for the task: querying data, detecting variances, explaining models, or preparing a recommended change.
The product combines data from multiple systems into one report of strategic metrics. AI prepares insights and recommendations, while the user can move from a metric to source records. The solution does not require a BI engine.
Explore the product →We define the decision and definitions first. Only then do we design the data, report, and maintenance model.
Together, we define the problem, decisions, users, KPIs, data sources, and success criteria. We choose the smallest scope that can validate the solution in a real business situation.
We assess data, architecture, security, integrations, and risks. The client provides access and identifies the owners of data, reports, and business definitions.
We integrate and transform data and build the model, semantics, quality controls, and permissions. IT and source owners participate in validating rules and access.
We create KPIs, reports, and analytical processes around decisions, not a catalog of charts. Key users validate the logic, clarity, and usefulness of the result.
Together, we run tests, make corrections, and launch the solution. Documentation and knowledge transfer enable the team to understand the sources, definitions, and way of working.
We monitor and optimize the solution and deliver the change backlog. The client sets business priorities, while the agreed accountability model protects reporting continuity.
Expand only the area needed at this stage. The full content remains available without lengthening the page’s primary path.
Before: revenue is growing, but discounts, logistics, returns, and service costs are analyzed separately. After: one view shows the path from price to margin, customer segments, and contracts with the greatest erosion. We measure metrics including margin after discounts and service costs, price loss against the price list, cost to serve, and the impact of the sales mix on margin.
Before: the forecast is prepared manually, and invoice due dates do not account for payment history. After: the forecast shows scenarios, risk concentration, and the receivables with the greatest impact. We measure cash buffer, forecast accuracy, receivables concentration, average collection period, and the value of overdue items.
Before: the average status looks correct even though cases return for correction or wait too long. After: the process owner sees working and waiting time, rework paths, bottlenecks, and cases requiring attention. We measure total case time, working and waiting time, rework rate, and the value of cases at risk of delay.
Before: inventory value rises while critical products are unavailable. After: products are assessed together by value, variability, and availability risk. We measure capital tied up in inventory, demand fulfillment, excess and slow-moving inventory, and lead-time variability.
Before: models and KPIs are duplicated, reports are slow, and no one knows which are critical. After: the portfolio shows what to develop, fix, combine, or retire. We measure report usage, duplication, performance, resource consumption, and AI readiness.
Priorities, source map, definitions, accountabilities, and a development plan for management, CFOs, CIOs, and people responsible for BI.
Analysis, cleansing, standardization, and transformation of data, automated model feeds, and quality controls for data from ERP, CRM, applications, APIs, databases, and files. Data preparation →
Interactive reports combining multiple sources. We select the tool, metrics, filters, and presentation method for the users and their decisions. Reports and dashboards →
Use cases, predictive analytics, signal detection, and criteria for validating results. Data Science →
A management view of a process covering timeliness, stage duration, rework, workload, and bottlenecks in AMODIT or another BPM system. Process reporting →
A decision layer over sales, finance, inventory, purchasing, and manufacturing, combined with other sources when needed.
Shared data, semantics, and governance as the foundation for BI and AI, plus ongoing support, monitoring, performance optimization, and a development plan.
Support for the entire project or a selected stage from experts in Power BI, Tableau, Alteryx, Snowflake, Python, R, and other data technologies. Expert outsourcing → · BI consulting → · BI Assistance →
Pharmaceuticals and consumer health are among the areas where we have the most BI experience. We report on market share and sell-out, sales force effectiveness, product launches, and omnichannel sales. We are responsible for the reporting layer, data, development, and maintenance of these solutions.
Data in Snowflake was incorporated into a Power BI reporting architecture. The scope included a Power BI application, Power Automate and Power Apps, row-level security (RLS), shared KPIs, and self-service for business users.
For an international client, the scope included a workflow audit, logic mapping, migration, recreation of schedules and quality controls, result validation, and team training. The qualitative outcome was a simpler architecture, less dependence on Alteryx, and better integration with Power BI.
Microsoft Fabric with Copilot in Power BI and Snowflake Cortex were compared using the same data and questions as the basis for an architecture decision.
Organizations: midsize, large, and Enterprise organizations with multiple systems, companies, sources, and user groups. Reporting is secure, scalable, and maintainable.
Sponsors: management, CFO, COO, sales director, operations director, CIO, head of data or BI, and business process owner.
Buying trigger: Excel is no longer enough, reports do not agree, data is distributed across ERP, CRM, and AMODIT, BI is slow, or the organization is preparing data for AI.
Industry experience: pharmaceuticals and consumer health, finance, manufacturing, logistics, renewable energy and automotive, as well as FMCG and retail, telecommunications, media, and real estate.
“Astrafox Sp. z o.o. trained users to create analytical reports. The cooperation with the company was of a high standard, without issues or delays, and followed the planned schedule.” (translated from Polish)
“BI Expert Services team by Astrafox successfully improved interactive Tableau dashboards and created new budget, financial data, and Management Board dashboards. […] We work with BI Expert Services team by Astrafox also in terms of Alteryx services. […] The implemented solution allowed the integration of data dispersed throughout the organization, accelerate the analytical and reporting work of business users and relieve the IT department, reducing the time commitment in preparing data sources and the reports themselves for the company’s business departments. We recommend working with BI Expert Services team by Astrafox.”
“We have worked with Astrafox Sp. z o.o. since 2019. The company supplied Tableau licenses and trained our employees. The training covered visualization best practices, database connections, calculations, formatting, and dashboard creation. The employee training was delivered reliably and professionally, contributing to a fast and effective implementation of the tool in our organization. We are satisfied with the services provided.” (translated from Polish)
“Tableau BI is used as an analytics and reporting tool in our organization. Its drag-and-drop method makes it easy to create reports, statistics, forecasts, and other visualizations in seconds. Tableau completely changed how we think about data and enabled us to focus on analysis and valuable insights. The tool supports integration with data from more than one hundred different sources.” (translated from Polish)
“Astrafox Sp. z o.o. provides Otodom with services for designing and building analytical reports based on Tableau BI software. The consultants’ experience and skills enabled effective project delivery. They have extensive technical and business experience and deliver products according to the highest data visualization standards, resulting in high-quality reporting products. Their proactive approach, backed by many years of experience working with data, allowed us to quickly achieve our business goals and deliver projects to the highest standard.” (translated from Polish)
“Astrafox Sp. z o.o. has worked with us since 2017. The company supplied licenses and provides maintenance services for the delivered Business Intelligence software and data exchange service during the subscription periods. The services primarily include access to data, access to new software versions, technical support for administrators, and correction of reported errors.” (translated from Polish)
For the first conversation, one decision or report, the sources used today, and the person responsible for the outcome are enough.
Start with the decision the data needs to support: who makes it, how often, and what information is missing. Then we define the first report, the minimum set of sources, and how the result will be validated.
When the goal is to answer one business question, the data is ready and organized, and the scope fits within 5–10 KPIs, one management view, and an optional diagnostic view. Quick Start takes 2–3 days and costs EUR 2,000 net.
Quick Start does not include building an extract, transform, and load (ETL) process. If sources need to be connected, data organized, or the target architecture designed, the right next step is DataFlow or a custom implementation.
Not necessarily. We first identify which ERP data is needed and how to connect it with other sources. The access method depends on the system and its configuration.
The cause may be different definitions, dates, transaction statuses, filters, or sources. Before changing a chart, we agree on what the metric means and verify the data behind it.
No. We start with one question and the minimum data set needed to answer it, then expand the model.
Yes. We assess data, reports, performance, permissions, and usage, then improve individual views and data flows, run migrations, support users, or prepare a broader development plan.
No. DataFlow prepares and controls data flows that feed Power BI, Tableau, Excel, and other tools. It does not replace the client’s reports or data warehouse.
No. AI explains the model and errors and prepares a recommended change. The change goes through validation and review, and a person with the appropriate permissions publishes it.
We work with Power BI and Microsoft Fabric, Tableau, Snowflake, Alteryx, Databricks, and Qlik Sense. Our DataFlow product prepares and controls the data that feeds these tools. The choice depends on the data, existing environment, users, security, and maintenance model.
Since 1999, we have connected data with business processes and systems. We work with Power BI and Microsoft Fabric, Tableau, Snowflake, Alteryx, Databricks, and Qlik Sense. Our DataFlow product and integration expertise allow one team to cover data preparation, reporting, and maintenance.
Show us where the answer comes from today: ERP, CRM, a spreadsheet, an application, or a conversation with an analyst. We will determine what to organize first.
Describe your challenge