1. Abstract
Board Foresight contains a broad library of internal and external data. Using filters, tags, and search operators helps users quickly narrow results to the most relevant indicators for their analysis.
2. Context
Use this best practice whenever browsing data in the Global Intelligence Cloud or Discover Engine, particularly when building Workbenches that require specific geographies, frequencies, or data types.
3. Content
3.1 Why It Matters
Without filters, searching large data libraries can be slow and overwhelming. Users may miss high-quality indicators or spend time evaluating irrelevant datasets.
Effective use of filters and search operators:
- Reduces noise in search results
- Speeds up data discovery
- Improves consistency across analyses and teams
3.2 How to Apply
- Open the Data Search or Discover interface.
- Use the left-hand filter panel to narrow results by:
- Geography or country
- Data category
- Frequency or source
- Use search operators directly in the search bar:
- # before a term to apply a tag (for example, #GDP)
- + before a term to require it in results
- - before a term to exclude it from results
- Combine filters and operators for precise searches.
3.3 Example
An analyst searching for U.S. consumer sentiment data applies:
- Country filter: United States
- Category filter: #Wages
- Search term: +Retail
This quickly surfaces indicators such as “Real Total Weekly Earnings of All Employees: Retail Trade” without reviewing dozens of unrelated datasets.
3.4 Common Pitfalls
- Over-restricting searches by applying too many filters at once
- Forgetting that filters remain active between searches
- Ignoring tag definitions and misinterpreting similarly named indicators
3.5 Expected Results
- Faster access to relevant, high-quality data
- More consistent indicator selection across users
- Reduced time spent evaluating unsuitable datasets
- A smoother transition from data discovery to modeling
