--- sourceDocument: Australia Platform Analytics sourceDocumentLink: https://www.servicenow.com/docs/r/australia/now-intelligence Release : - australia ft:locale : - en-US ft:publication_title : - Australia Platform Analytics ft:clusterId : - par bundleId : - par workflow : - Platform --- # Indicator vs Table data source selection # Indicator vs Table data source selection {#ariaid-title1} Release version: Australia Updated September 8, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Indicator vs Table data source selection When using AI Data Explorer on the ServiceNow AI Platform®, the system determines whether to use table data or indicator (KPI) data based on keywords in your query or predefined settings. Tables provide current, real-time data, while indicators show trends by aggregating data over time from tables or other indicators. Understanding how AI Data Explorer selects the data source helps you frame queries effectively to get the most relevant and accurate results. Show full answer Show less ## How Data Source Selection Works * The system analyzes your query for specific keywords to choose between table or indicator data. * If no keywords or context are found, it defaults to a system property setting (default is table data). * AI Data Explorer can operate in agentic or non-agentic modes, influencing how the source type is selected when ambiguous. * Keywords that favor indicator data include: **indicator** , **indicators** , **KPI** , **key performance indicator**. * Keywords that favor table data include: **table** , **list** , **live data** , **live query** , **right now** , **at this time** , **this moment** , and **as of today**. ## Context and Follow-up Queries * If a query is a follow-up or launched from a visualization, existing context influences the data source choice. * If the context has both table and indicator sources, the system uses the more recent source type. * Queries requesting record-level data, live values, more than two breakdowns, or unsupported date ranges cause the context to switch from indicator to table data. * When switching from indicator to table, the system retains related conditions and aggregates from contributing indicators. ## Limitations and Support for Breakdown Elements * Indicators support up to two levels of breakdowns (automated and scripted). * Queries requiring three or more breakdowns automatically fall back to table data. * Combining multiple breakdown elements depends on the indicator type and configuration: * Formula indicators require aggregation enabled and all contributing indicators to support score aggregation. * Automated indicators support aggregation differently based on aggregate type: Count and Sum support multiple breakdowns; Average and Count Distinct do not. * If an indicator cannot support the requested combination of breakdown elements, the system defaults to one element and notifies you accordingly. ## Important Considerations * AI Data Explorer supports automated and formula indicators only; manual/external indicators, targets, thresholds, forecasts, and benchmarking indicators are excluded. * Understanding the data source selection helps you tailor queries for live, current data or trend analysis over time. After you submit a query to AI Data Explorer, the system checks the query for specific keywords that indicate whether to use table or indicator data. If there are no such keywords, it falls back on a default set in a system property. Tables on the ServiceNow AI Platform® contain current data. To view trends in this data over time, you need an [indicator (KPI)](https://www.servicenow.com/docs/0BmHD84G7z5nj9ylwlJX_g#gloss-indicator "A performance measurement taken at regular intervals of a business service, an activity, or organizational behavior. These performance measurements result in a series of indicator scores over time. Businesses track these scores to measure current conditions and to forecast trends."). Indicators are calculated from table values that are collected over time. They may be calculated directly from table data or from other indicators in a formula. Important: AI Data Explorer supports [automated indicators](https://www.servicenow.com/docs/0BmHD84G7z5nj9ylwlJX_g#gloss-automated-indicator "An automated indicator uses an indicator source as its data set. The indicator source specifies a table or database view, conditions for filtering records from that source, and the frequency at which you expect to display the data. The indicator applies an aggregator and optional conditions to this data. The indicator also specifies a data collection job and any breakdowns to apply.") and [formula indicators](https://www.servicenow.com/docs/0BmHD84G7z5nj9ylwlJX_g#gloss-formula-indicator "Produces a computed indicator score from one or more other indicators. Besides indicator scores, the formula can include calculations such as the gap between an indicator score and the indicator target."). It does not support manual or external indicators, [targets](https://www.servicenow.com/docs/0BmHD84G7z5nj9ylwlJX_g#gloss-target "The future hoped-for indicator scores that represent goals that your organization wants to achieve. A target can be global or can be personal to one user."), [thresholds](https://www.servicenow.com/docs/0BmHD84G7z5nj9ylwlJX_g#gloss-threshold "The user-defined top or bottom limit of the normal range of scores for an indicator. You can set up an alert to let you know when a threshold is breached and how. For example, you can set up an alert to let you know when a score reaches an all-time high or low."), or [forecasts](https://www.servicenow.com/docs/0BmHD84G7z5nj9ylwlJX_g#gloss-forecast "A prediction of future Performance Analytics indicator scores based on past behavior. Visible in time series data visualizations/widgets and KPI Details."). Benchmarking indicators are excluded from indicator search results, whether the benchmarking indicator is itself automated or is a contributor within a formula indicator. The system searches your query for the following content to determine the appropriate data source type: 1. Keywords 2. Context, if present If the query does not show whether table or indicator data is preferred, and there is no context, the system responds differently depending on whether AI Data Explorer is agentic. If AI Data Explorer is non-agentic, the system uses the fallback source type defined in the system property sn_query_gen.default_source_type. The default value is `table`. If AI Data Explorer is agentic, the agent uses textual clues to determine which data source type to use. Table data is the default. Keywords in the query have the highest priority. To influence the choice, include the following keywords: * To use an indicator as the data source: * indicator * indicators * KPI * key performance indicator * To use a table as the data source: * table * list * live data * live query * right now * at this time * this moment * as of today If your query is a follow-up question or launched from a data visualization, you already start with a context. If the system returns a successful result from the same source as the context, it keeps that source type. If the context has both an indicator and a table, the system goes with the more recent source type. If your current context is an indicator, the following follow-up questions cause the context to switch to a table data source: * Asking for record-level data * Asking for live values * Asking for more than 2 breakdowns, such as asking for a third breakdown in a follow-up question * Asking for a date range the indicator does not have When the context switches from an indicator to a table, the system converts it to the table, conditions, and aggregate field of its [contributing indicators](https://www.servicenow.com/docs/x0mDmqkqRmP~pfxjRS7_7g "If you’re viewing a formula indicator in KPI Details, you can list the contributing indicators to that formula. Depending on the KPI Details configuration, you can open the contributing indicators in KPI Details."). The context is not dropped, and neither is the formula passed through unconverted. For indicator data sources, both automated and scripted breakdowns are supported, but only to two levels. If a query cannot be answered with fewer than three breakdowns, the system falls back to table data sources. An indicator's support for combining more than one breakdown element in a single result depends on the indicator type. For a formula indicator, this depends on whether Allow aggregation of multiple breakdown element scores is selected on the indicator record. All contributing indicators must also support score aggregation. For an automated indicator, aggregate score support depends on the indicator's aggregate: Count and Sum support combining multiple breakdown elements, while Average and Count Distinct do not. If the matched indicator does not support combining the requested breakdown elements, the system uses only one of the requested elements to generate the result. It then notifies you that the result reflects a single breakdown element instead of the full combination you requested. **Related tasks** * [Create a Formula Indicator](https://www.servicenow.com/docs/X7sQLl4RZjsF17c7MjDX5g "Calculate scores from the scores of one or more other indicators. Apply mathematical operations or a preset method, such as the method to calculate the gap between an indicator score and the indicator target.") * [Create an automated indicator](https://www.servicenow.com/docs/eVnN3Dg5W5_J5Lb0TAgLZA#t_CreateAnAutomatedIndicator "To analyze the performance of a business process that is recorded in a ServiceNow table, use an automated indicator. If a suitable indicator is not provided in a Platform Analytics Solution, create a new one.")