# China ERP Data Cleansing Tracker Worksheet

> Source: https://netray.co/tools/china-erp-data-cleansing-tracker-worksheet
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

An editable tracker for data objects in a Kingdee, Yonyou or Inspur migration, with error rate and completion calculated per row.

## Category

erp-migration

## Region

China

## Audience

- ERP project manager
- Data migration lead

## Tool

**Kind:** worksheet

**Mode:** editable

**Columns:**

#### Data object

**Key:** object

**Type:** text

#### Owner

**Key:** owner

**Type:** text

#### Records in legacy

**Key:** total

**Type:** number

#### Records with errors

**Key:** errors

**Type:** number

#### Errors fixed

**Key:** fixed

**Type:** number

#### Error rate

**Key:** err_pct

**Type:** number

**Expr:** errors / total * 100

**Format:** percent

#### Errors open

**Key:** open

**Type:** number

**Expr:** max(errors - fixed, 0)

#### Fix progress

**Key:** done_pct

**Type:** number

**Expr:** if(gt(errors,0), fixed / errors * 100, 100)

**Format:** percent

#### Status

**Key:** status

**Type:** select

**Options:**

- Not started
- In progress
- Blocked
- Signed off

#### Target date

**Key:** due

**Type:** date

**Rows:**

**Object:** Materials

**Owner:** Planning

**Total:** 18400

**Errors:** 2100

**Fixed:** 1500

**Status:** In progress

**Due:** 2026-11-15

**Object:** Vendors

**Owner:** Procurement

**Total:** 1250

**Errors:** 310

**Fixed:** 310

**Status:** Signed off

**Due:** 2026-11-01

**Object:** Customers

**Owner:** Sales

**Total:** 2400

**Errors:** 180

**Fixed:** 60

**Status:** In progress

**Due:** 2026-11-20

**Object:** BOM headers

**Owner:** Engineering

**Total:** 3900

**Errors:** 640

**Fixed:** 120

**Status:** Blocked

**Due:** 2026-12-01

**Object:** Open purchase orders

**Owner:** Procurement

**Total:** 760

**Errors:** 40

**Fixed:** 0

**Status:** Not started

**Due:** 2026-12-10

**Totals:**

#### Total records

**Key:** total

**Agg:** sum

**Format:** integer

#### Total errors

**Key:** errors

**Agg:** sum

**Format:** integer

#### Open errors

**Key:** open

**Agg:** sum

**Format:** integer

**Summary:**

#### Overall error rate

**Key:** overall_err

**Expr:** sum_errors / sum_total * 100

**Format:** percent

**Primary:** true

#### Overall fix progress

**Key:** overall_done

**Expr:** sum_fixed / sum_errors * 100

**Format:** percent

**Notes:** Count an error once per record. Add a row for each load object such as work centres, routings, opening balances and fixed assets. Chinese and English names should be in separate fields in the load file.

## Content

**Intro:** Most China ERP projects slip on data, not software. This tracker gives each load object an owner, an error rate and a clear fix percentage so the steering group sees real progress before cutover.

**Sections:**

#### How to use it

**Body:** List every data object you will load: materials, vendors, customers, BOMs, routings, open orders, opening balances and fixed assets. Enter record counts from the legacy system and error counts from your validation checks. Update fixed counts weekly. The calculated columns show error rate, open errors and fix progress, and the summary gives one overall number for the status report.

#### What counts as an error

**Body:** Use rules agreed with the business before you count. Typical rules are duplicate keys, missing unit of measure, missing tax code, inactive references, wrong decimal precision and mixed Chinese and English descriptions. Agree on a threshold such as signing off an object only when open errors are zero, or when the remaining errors are explicitly accepted by the owner.

**Bullets:**

- Duplicate vendors and customers
- Materials without unit of measure or category
- BOMs referencing obsolete components
- Open orders with closed vendors

#### Common mistakes

**Body:** Teams count errors once at the start and never again, so the percentage looks fine until a trial load. Re-run validation after each mock load and update the row. Another mistake is letting IT own all fixes; business owners know which duplicate is correct. Keep the owner column filled with a named person, not a department.

**Cta:** Netray can help build repeatable validation queries against your legacy and target ERP data if the manual counts are getting heavy.

**Faq:**

#### Can I use this for non-Chinese ERPs?

**Answer:** Yes. The structure fits any migration. The China angle is the guidance on bilingual names, tax codes and fapiao related fields.

#### How many mock loads should I plan?

**Answer:** Most projects plan at least two or three trial loads before cutover. Update this tracker after each one so trends are visible.

#### What does fix progress show?

**Answer:** Errors fixed divided by errors found for that object. An object with no errors shows 100 percent.

#### Does it export to Excel?

**Answer:** Yes, the worksheet exports to Excel and CSV so you can share it with the steering group.

## Search terms

erp data cleansing tracker, erp data migration tracker excel, china erp data migration, kingdee data migration worksheet, yonyou data cleansing, master data cleansing template, data migration status report

---
Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json