| name | enterprise-data-parsing |
| description | Strategies for reading and indexing diverse enterprise data formats located in a flat directory or specific path. |
When retrieving information from enterprise data (like /root/DATA), first identify the file structure. Enterprise data often consists of mixed formats (PDF, CSV, JSON, TXT, or Markdown).
- Inventory: List all files in the directory to determine the scope.
import os
data_path = "/root/DATA"
files = os.listdir(data_path)
- Reading Techniques:
- Text/Markdown: Use standard
open().read().
- JSON: Use
json.load().
- CSV: Use
pandas.read_csv() for structured queries.
- Indexing: If the dataset is large, create a simple keyword index or use a search function to map keywords from the questions to specific filenames to narrow the search space.