Overview
UMS Group was engaged to examine and repair data on substation assets in SAP:
- What information is stored in SAP for each asset type?
- Where are there errors or gaps that can be repaired now?
- What pull-down lists are available to users when characterizing each asset?
- Define new standards for each characteristic
- Define a correction strategy for moving to the new data standards
Methodology
Data Fields:
Example 1: Data cleansing process for the “Manufacturer” field:
- Compiled a list of unique entries
- Standardized the naming convention
- Updated the Manufacturer name to reflect mergers and acquisitions through research, e.g.
Example 2: Parsing Out and Correcting Individual Data Columns:
Functional Location Description field
Example 3: Added new fields for asset attributes that were parsed out of existing fields
1. Metal Clad (Y/N) – based on Description
2. Transmission or Distribution – based on FD Class
3. Interrupting Medium – based on Interrupt Medium
4. Single or Multi-Pressure – based on Description
5. Single or Multi-Tank – for Oil Breakers, based on Number of Tanks
Example 4: Filled in missing fields from correlating to other sources:
1. Substation Name – 5,506 rows added
2. Zip Code – 250 rows added
3. Substation Address – 82 rows added, – now 98.3% complete
Results
We identified 15 (of the original 100) fields are empty or have only garbage data in them, and recommended deletion to clean up the data – decluttering it by 15% and making room for new more useful fields.
We looked for opportunities to develop and fill in missing data…
The project ultimately resulted in a more accurate, complete, and robust data set with the confidence of the client, including new data standards and strategies for improved data governance going forward.
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