Volatility
The degree to which data values change over time.
- •Accurate reflection of highly dynamic data environments where change is frequent and expected.
- •Ability to track and analyze rapid changes for time-sensitive decision making.
- •Systems designed to handle high change rates can maintain accuracy and currency.
- •Understanding data volatility helps in designing appropriate data refresh and validation strategies.
- •Difficulty in maintaining data accuracy and currency if data changes faster than update processes can cope.
- •Increased risk of decisions based on stale data in highly dynamic environments.
- •Higher data management overhead to track and reconcile frequent changes.
- •Instability in reports or analyses if based on constantly shifting, unmanaged volatile data.
%
Logistics: Reference data like ISO country codes or port UN/LOCODEs are very stable and change extremely infrequently, making them reliable for long-term use.
Stock Market: Historical end-of-day stock prices are static once the trading day is closed and verified.
Product Catalog: Core product attributes like 'Material Safety Data Sheet (MSDS) ID' for a chemical product are non-volatile once established.
Logistics: Customer contact information (e.g., primary contact person, phone number for a shipping company) changes frequently, but the update process for the master data is slow and manual, leading to many outdated records.
Stock Market: Real-time stock prices are highly volatile, changing many times per second, requiring very frequent updates for accurate trading systems.
Product Catalog: Product prices in a fast-moving consumer goods (FMCG) industry change weekly due to promotions, but the pricing system is only updated monthly.