# IFS Cloud: How to Extract Data Directly From a Table

> Source: https://netray.co/erp-help/ifs-cloud-extract-data-directly-from-table
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: ERP Help

## Short answer

In IFS Cloud you can read data from the Oracle database only if your hosting model gives you database access, and even then you should read the views, not the underlying _TAB tables, and never write to them. For most reporting, use OData projections, information sources or a managed data feed instead of direct SQL.

## Kind

how-to

## System

ifs

## Erp

IFS Cloud

## Module

Reporting / Data access

## Query

ifs cloud extract data directly from table

## Alternate Queries

- ifs cloud read database tables
- ifs cloud sql access oracle views
- ifs cloud export data to data warehouse

## Applies To

IFS Cloud (and IFS Applications 10 lineage). Direct database access is generally unavailable on IFS Managed Cloud and possible on customer-hosted or on-prem installs.

## Steps

### How to extract IFS Cloud data safely

**Items:**

- Decide whether you truly need SQL. If the data is already exposed by a projection (OData), use that; it applies security and business logic for you.
- Find the entity in the application first: the page you see in Aurena maps to a logical unit (LU), which maps to a view named after the LU and a _TAB base table.
- Prefer the LU view (for example the CUSTOMER_ORDER_LINE view) over the CUSTOMER_ORDER_LINE_TAB table. Views translate stored codes into client values and include some derived columns.
- If you are customer-hosted, ask the DBA for a dedicated read-only schema or user with SELECT granted on the needed views, not on the application owner schema.
- Run extracts against a replica, standby or off-peak window; large scans on the production database slow online users.
- For incremental loads, pick a reliable change column (a rowversion or modified-date column on the table) and test that it changes on every update.
- For managed cloud, use projections or the vendor's supported data and analytics feed instead of asking for database credentials.
- Document every extract: source view, filters, schedule, owner. Re-test after each IFS update because view definitions can change.

## Sections

### Tables, views and why the difference matters

**Body:**

IFS stores business data in tables whose names end in _TAB, wrapped by views and by PL/SQL APIs (named with an _API suffix). Application logic, validation and security run through the APIs, so inserting or updating a _TAB directly can corrupt state that the application assumes is consistent.

Reading is far lower risk than writing, but views are still the better contract. Table structures can change between updates; the published projection or view is the thing IFS tries to keep stable.

### Supported options in order of preference

**Body:**

First choice is the OData projections used by Aurena. They are versioned, secured by permission sets and suitable for integrations and BI tools that speak OData. Throttle page sizes and use filters; do not try to export millions of rows through a single call.

Second is information sources and the reporting tools shipped with IFS, which respect the same security. Third, for warehouse-scale needs, use a data and analytics feed that IFS offers for your edition, or a read replica and a read-only schema on customer-hosted systems.

**Code:**

-- Read-only extract from a view (customer-hosted only; schema name varies)
SELECT order_no, line_no, catalog_no, buy_qty_due
FROM   customer_order_line
WHERE  rowversion > :last_extract_ts;

### Governance and licensing

**Body:**

Direct database access can fall outside your support and licence terms, and it bypasses the row-level and field-level security you configured in IFS. Check your contract before building a pipeline on it.

If sensitive data (export-controlled drawings, personal data) is in the system, an extract can silently widen who can see it. Apply the same classification to the extract as to the source.

## Pitfalls

- Writing to _TAB tables directly; it bypasses validation and can corrupt dependent state.
- Reading the application owner schema with a shared admin account instead of a dedicated read-only user.
- Building incremental loads on a column that is not updated by every code path.
- Large full-table scans on the production database during working hours.
- Forgetting that a managed cloud contract may forbid direct database access altogether.

## Ai Angle

Instead of extracting tables to a separate warehouse just to answer questions, a grounded assistant can query IFS through the supported interfaces with the user's own security, show the query it ran and return the answer. Netray deploys that layer on private models beside the IFS installation, read-only by default, so you avoid building and maintaining a shadow copy of the data for ad hoc needs.

## Faq

### Can I connect Power BI or another BI tool directly to IFS Cloud tables?

**Answer:** On customer-hosted databases it is technically possible against views, but it bypasses IFS security and may affect support. On managed cloud it is generally not available. Use OData projections or a supported data feed for BI.

### What is the difference between a _TAB table and a view in IFS?

**Answer:** The _TAB holds the stored data; the view of the same logical unit adds translated values and derived columns. The _API package is the supported way to change data. Read from views, write through the application.

### How do I find which table holds a given field?

**Answer:** Identify the page, then the logical unit behind it (the client shows it in the field and page details), and look up that LU's view and table in the database dictionary. Customisations may add custom-field tables.

### Is it safe to update an IFS table with SQL?

**Answer:** No. Updates should go through the application or its APIs so validation, history and dependent records stay consistent. Direct updates are a common cause of support incidents.

## Search terms

ifs cloud extract data from table, ifs cloud sql access, ifs odata projection export, ifs _tab table view, ifs cloud data warehouse, ifs read only database user, ifs cloud reporting data, ifs logical unit view

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