Combining data from various sources: how to gain a complete picture

Data is one of the most important assets of any organization today. However, quantity alone is not enough – real business value only emerges when data is viewed holistically.

Yet in many companies, data still exists in silos: each department has its own source of information. The sales team works with different data than finance, and logistics reports don’t include production data. The result? A lack of consistency, delayed responses to change, and an incomplete picture of operational reality.

Data scattered across systems

A typical scenario: a company stores sales data in an ERP system, customer data in a CRM, inventory in a separate WMS system, and revenue forecasts arrive via Excel spreadsheets sent by email once a week. Each source contains a piece of the puzzle, but no one sees the full picture.

In such conditions, coherent reporting and quick reactions to change are nearly impossible. By the time the data is gathered, compared, and standardized, the business situation has already changed.

Why integrate data?

Combining data from different sources allows for the creation of a so-called „single source of truth” – a central view that enables real-time analysis and eliminates the need for manual data stitching. As a result:

• Executives have access to a complete view of the company without having to manually combine data,
• Analysts don’t need to clean and match data from different systems themselves,
• Operational teams can make decisions based on current and consistent information.

This isn’t just convenient – it’s a concrete competitive advantage.

„Siloed data may be suitable for local analysis, but strategic decisions require integration. Without a shared data model, we risk contradictions, incorrect conclusions, and duplicated effort. Only integrated data allows us to build predictive analytics, automate processes, and scale reporting.”

Karolina Skowrońska

Data Analyst

What does it look like in practice?

At 3Soft, we support organizations in building a unified data layer – regardless of whether the source is an ERP, CRM, e-commerce platform, external data (e.g., via APIs), or local Excel or flat files. The process includes:

• Assessing data availability and quality,
• Preparing the integration layer (ETL/ELT),
• Mapping and standardizing data structures,
• Building a central data repository (e.g., a data warehouse),
• Creating reports and dashboards based on the integrated data.

As a result, the client gains access to a single, coherent reporting system – without needing to „patch together” data from spreadsheets or emails.

Data quality – a prerequisite for effective integration

Successful integration isn’t possible without ensuring data quality. Structural differences, incomplete records, or inconsistent formats can all block further analysis. That’s why every integration project begins with a data audit and cleanup – both technically and logically.This topic is explored in more detail in the article: „Data quality – the foundation of effective analysis”.

Data integration and analysis automation

Integrated data paves the way for implementing more advanced reporting features – such as alerts that automatically inform users about significant changes or anomalies in real time. To learn how these solutions work in practice, read also: „Alerts in reports – how data can report problems on its own”.

Tangible business value

Bringing together data from different sources is one of the most important steps toward mature analytics. It enables better reporting but more importantly – faster and more accurate decision-making based on a complete understanding of the situation.

At 3Soft, we offer comprehensive support to organizations: from identifying data sources, through integration and cleansing, to the deployment and maintenance of tools that meaningfully support day-to-day operational and strategic work.