Chapter 1 - Getting Started with Data in Workspace
This chapter introduces core data groupings and practical workflows for finding and using data in LSEG Workspace.
Overview
Market data is commonly organized across several dimensions. Understanding these dimensions early helps users choose the right discovery path and data timing for analysis.
Users should think in terms of:
- Country-level universes
- Asset classes (equities, fixed income, FX, rates, commodities)
- Market and exchange context
- Data timeliness (real-time, delayed, historical)
Key Tools or Views
Use current Workspace tools for discovery and access:
- Search App for discovery by asset class, market, exchange, and geography
- Quote App and Instrument views for pricing context and asset-class displays such as Equities, FX, Fixed Income, Rates, and Commodities
- Chains (chain RICs) to view a family of related instruments for a market segment, tenor structure, or benchmark set
- Historical and reference data workflows through Workspace apps and enterprise data products
- LSEG Data Library (Python) for programmatic retrieval and downstream analytics
Concepts
1) Country-Level Data
Data associated with specific countries or regions, often used for macro comparison and market segmentation.
2) Asset-Class Data
Data grouped by instruments such as equities, fixed income, FX, and derivatives.
3) Market-Level Data
Data tied to exchanges, venues, or recognized market centers.
4) Real-Time vs Historical Data
The same instrument can have multiple timing dimensions:
- Real-time: updates as market events occur (subject to venue permissions and entitlements)
- Delayed: often available at no additional exchange fee, depending on venue policy
- Historical: time-series and archived reference context for backtesting, reporting, and research
5) Historical Data Access
Historical data is available across Workspace-connected and enterprise data offerings for use cases such as company reporting history, bond terms and conditions history, ratings history, and long-run price analysis.
6) Specialist Data
Specialist services provide deeper commentary and analysis coverage across market segments, including:
- Economic indicators and macroeconomic commentary
- Specialist analysis and commentary
- Specialist forecasting and technical analysis
- Specialist news services
- Specialist prices (including broker-contributed data)
Methods / Workflows
- Start with Search App and define your universe (country, asset class, exchange).
- Use Quote App to validate the asset-class view and quickly inspect key fields for the instrument or market.
- Open the relevant Chain when you need the broader instrument family (for example, related maturities, strikes, or constituents).
- Confirm required timeliness (real-time, delayed, historical).
- Validate exchange permissions and fee model for real-time exchange-traded data.
- If historical depth is required, use historical-capable products and APIs aligned to your use case.
- Record identifiers and metadata early to keep analytical workflows reproducible.
Examples
Data Classification Example
| Question | Interpretation in Workspace |
|---|---|
| Is this instrument country-scoped? | Filter by country/region in Search and compare related instruments. |
| Is this an asset-class workflow? | Filter by asset class, then refine by instrument type. |
| Is exchange context required? | Add exchange/venue constraints and validate entitlement requirements. |
| Do I need current or past values? | Choose real-time, delayed, or historical retrieval path. |
Real-Time vs Historical Decision Matrix
| Requirement | Recommended path |
|---|---|
| Immediate execution or intraday monitoring | Real-time feed (entitlements may apply) |
| Price indication without real-time entitlement | Delayed data where available |
| Backtesting, trend, model calibration | Historical data services or APIs |