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Data Virtualization

Data management and qualityAdvanced Level

A way to integrate systems by querying data where it lives through a virtual layer, instead of copying it into another database.

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What is Data Virtualization?

Data virtualization is a way to integrate systems such as an ERP, a PIM and a webshop by reading data where it lives through a virtual layer, instead of copying it. Replication is the opposite approach: it copies the data into the other system, on a schedule or whenever it changes. With virtualization, a query goes to the virtual layer, which fetches the answer from the source systems and combines it on the fly. Nothing is stored twice, so you always see the source value, but every read depends on the source being online and fast. Replication keeps a local copy that the receiving system can read and edit quickly, at the cost of keeping copies in sync. For ERP integration, most stores replicate product content and use live lookups only for fast-changing values such as stock. See PIM vs ERP for which system should own which data.

Why Data Virtualization matters for e-commerce

An online store combines data from several systems: content from a PIM, prices and stock from an ERP, and orders from the shop itself. How you connect them affects speed and reliability. Virtualization avoids duplicate data and suits reporting across systems. Replication suits storefronts and feeds, which need fast, always available data and cannot wait on a slow ERP. Choosing per data type, rather than one approach for everything, keeps both accuracy and page speed under control.

Examples of Data Virtualization

  • 1Data: stock level, Approach: virtualization, Why: the product page asks the ERP for the current value when it loads.
  • 2Data: product descriptions and attributes, Approach: replication, Why: the webshop needs a fast local copy to render pages and filters.
  • 3Data: sales, returns and content scores, Approach: virtualization, Why: a dashboard combines three systems without building a data warehouse.
  • 4Data: prices, Approach: replication on a schedule, Why: the ERP exports price lists daily and the store imports them.
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How WISEPIM Helps

  • Product import and scheduled imports via automations bring ERP and supplier data into one product record, the replication side of the integration.
  • Platform connections push saved changes to connected stores about 30 seconds after save when auto-sync is on.
  • Export gives other systems a copy of your product data when they need one.

Common mistakes with Data Virtualization

  • Virtualizing data the storefront reads on every page view, so a slow ERP slows down the whole shop.
  • Replicating without deciding which system owns each field, so copies overwrite each other.
  • Ignoring data quality because the data is not copied; bad source data stays bad in the virtual view.
  • Choosing one approach for everything instead of per data type.

Tips for Data Virtualization

  • List each data type (content, price, stock, orders) and choose virtualization or replication per type.
  • Test how fast your ERP answers before you put live lookups on product pages.
  • Give every field one owner system and sync in one direction only.
  • Clean source data first; neither approach fixes wrong values.

Trends around Data Virtualization

  • Data fabric setups that mix virtualization and replication behind one access layer.
  • Change data capture, which replicates only the changed records instead of full exports.
  • Caching in the virtual layer to reduce load on source systems.
  • AI-assisted schema mapping between source systems.

Tools for Data Virtualization

  • Denodo: a data virtualization platform that gives one access layer over many sources.
  • TIBCO Data Virtualization: builds virtual views across databases and applications.
  • Informatica: a data management suite with integration and virtualization options.
  • CData Virtuality: connects many sources behind one SQL interface.
  • WISEPIM: a PIM system that imports and syncs product data, the replication side of a stack.

Related Terms

Access Control (PIM)Attribute Dependency ManagementAttribute InheritanceAttribute ManagementAttribute mappingAttribute Scoping

Also Known As

Virtual data integrationLogical data warehouseData federation

Frequently Asked Questions

Virtualization reads ERP data on request through a virtual layer and stores no copy. Replication copies ERP data into the other system on a schedule or on every change. Virtualization always shows the source value; replication is faster to read and keeps working when the ERP is slow or offline.

Use it for values that change often and are read rarely, such as stock checks or cross-system reports. Use replication for data that a storefront or feed reads constantly, such as product content.

No. ETL extracts, transforms and loads data into a target system, which is a form of replication. Virtualization leaves the data in the source and combines it at query time.

No. It shows source data as it is, so missing or wrong values stay missing or wrong. You still need validation rules in the system that owns the data.

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