Glossary
What is data silo?
A data silo is a collection of data that is locked into one system or department and cannot easily be combined with other data. Data silos often lead to different figures for the same concept.
Data silo explained
Data silos form naturally: each department chooses the software that suits its work, such as an ERP for finance, a CRM for sales and a separate tool for the web shop. Each system has its own customer numbers, definitions and exports, and nobody sees the whole picture.
The result is more than spreadsheet hassle. Questions that span departments, such as "what is the margin per customer including returns and service costs", are almost impossible to answer. And anyone who merges data by hand makes mistakes that nobody notices.
You break down silos by bringing data from the systems together in a data warehouse, with shared keys such as a customer number that means the same in every source. It is also an organisational matter: departments have to agree whose definition takes precedence.
Example
At Acme Groothandel, orders live in the ERP, customer contacts in the CRM and returns in a customer service spreadsheet. Only when the three come together in one warehouse does the commercial director see which customers buy a lot but also return a lot.
Data silo in ENABLE
ENABLE uses one PostgreSQL data warehouse per customer, in which Data Analytics brings the sources together outside the portal. Dashboards, the SQL Explorer and the Data API then all work on that same data.
FAQ
Frequently asked questions
How do data silos form?
Data silos form when departments each use their own systems and spreadsheets without shared connections or definitions. It often happens gradually as an organisation grows and buys more software.
How do you break down data silos?
Bring the data from the different systems together in a data warehouse, with shared keys and agreed definitions. Then make sure reporting reads from that central source rather than from separate exports.
What is the downside of data silos?
You get different figures for the same concept, a lot of manual work and cross-department questions that cannot be answered. That costs time and undermines trust in the figures.
Further reading
- SolutionSingle source of truth: one version of the truthOne central source for your business data, so every department sees the same figures.Read more
- SolutionData integration: connect data sources for insightConnect data sources for reporting and AI, via one central data warehouse.Read more
- ResourcesWhat is a data warehouse? Explained and comparedA data warehouse is a central database in which you bring together data from different source systems, such as your ERP, CRM and webshop, clean it up and organise it so that you can report on it and analyse it effectively. A source system is built to process transactions; a data warehouse is built for reading, comparing and keeping history. A data lake stores raw data in any format, and a data lakehouse combines the storage of a lake with the structure of a warehouse.Read more
- ResourcesGlossary of data, AI and Power BI termsWhat is a service principal, row-level security, a semantic model, text-to-SQL or RAG? Short, clear definitions of terms around data, Power BI and AI.Read more
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