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
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
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.
Talk to Our Experts Today
Insights In Your Inbox
Receive perspectives on the industries and issues that matter.