Ana provides several specialized tools to help you interact with and analyze data effectively. Each tool serves a specific purpose in the data analysis workflow.

​
Available Tools

Object ExplorerA tool for querying structured data directly from the data warehouse using the loaded ontology.
Metric ExplorerQuery data using a metrics-based format, supporting complex aggregations and filtering.
SearchFast dataset search functionality for quick access to relevant data.

​
Tool Selection

Ana automatically selects the appropriate tool based on your needs. Each tool is designed for specific tasks in the data analysis workflow, from data retrieval to computation and visualization.

​
Tools

​
Object Explorer

The Object Explorer is primarily Ana’s tool for accessing and querying your data warehouse. Object Explorer can also be used manually, giving users direct control over the data in a chat.
TextQL is currently working to add additional figures to this doc. Check back later for an image of the Object Explorer interface highlighting Ana’s integration and manual controls.

​
How Ana Uses Object Explorer

When you ask Ana questions that require data access, she leverages the Object Explorer through its search mode to find and retrieve the necessary information. Here’s how it works:
  1. Question Analysis
    • Ana identifies data-related questions
    • Determines required data sources
    • Plans the query approach
  2. Search Mode Integration
    • Automatically translates your question to a structured query
    • Uses search mode to locate relevant data
    • Optimizes the query for efficiency
  3. Data Retrieval and Presentation
    • Executes the optimized query
    • Processes the results
    • Presents the findings in a clear format
TextQL is currently working to add additional figures to this doc. Check back later for an image showing Ana’s workflow with the Object Explorer, from natural language input to data retrieval.

​
Manual Operation

To manually operate the Object Explorer:
  1. Access the Object Explorer
    • Look for the green plus button next to the chat prompt bar
    • Click the plus button to open the tools menu
    • Select “Object Explorer” from the available options
  2. Using the Modal
    • Browse available data objects in the left panel
    • Select fields and conditions for your query
    • Preview your query results in real-time
    • Execute queries to retrieve data
TextQL is currently working to add additional figures to this doc. Check back later for an image showing the plus button location and Object Explorer modal interface.

​
Best Practices for Manual Operation

  • Preview queries before execution
  • Use filters to narrow down results
  • Save frequently used queries
  • Export results when needed

​
Metric Explorer

The Metric Explorer enables structured queries for metrics data with support for various granularities and filtering options. Metrics are not visible to users until queried, making this tool essential for data discovery and analysis.

​
Key Features

  • Metrics-based querying
  • Granularity control
  • Complex filtering
  • Measurement aggregation
  • Time-based analysis
  • Multi-metric comparison
  • Hidden metrics discovery

​
Query Capabilities

Available Granularities
  • day (YYYY-MM-DD format) 
    {"target": {"name": "sale_date", "granularity": "day"}, "operator": "between", "value": ["2023-01-01", "2023-01-31"]}
  • week (integer week number) 
    {"target": {"name": "sale_date", "granularity": "week"}, "operator": "equals", "value": 23}
  • month (YYYY-MM format) 
    {"target": {"name": "sale_date", "granularity": "month"}, "operator": "equals", "value": "2023-01"}
  • quarter (YYYY-Q format) 
    {"target": {"name": "sale_date", "granularity": "quarter"}, "operator": "equals", "value": "2023-Q1"}
  • year (YYYY format) 
    {"target": {"name": "sale_date", "granularity": "year"}, "operator": "equals", "value": 2023}

​
Filter Operators

  • equals/not_equals (supports arrays for multiple values)
  • greater_than/less_than/less_than_or_equal
  • contains/not_contains
  • starts_with/not_starts_with
  • ends_with/not_ends_with
  • is null/is not null
  • between (array of two elements: dates or numbers)

​
Query Structure

{
  "metrics": [
    {"measure": "Revenue"},
    {"measure": "Total Quantity Sold"}
  ],
  "dimensions": [
    "product_id",
    {"name": "sale_date", "granularity": "month"}
  ],
  "filters": [
    {"target": {"name": "sale_date", "granularity": "year"}, "operator": "equals", "value": "2023"},
    {"target": {"measure": "Revenue"}, "operator": "greater_than", "value": {"amount": 1000, "currency": "USD"}}
  ],
  "order": [
    {"measure": "Revenue"}
  ],
  "direction": "desc"
}
The Meta Search tool enables quick dataset discovery and exploration of available resources. It provides comprehensive search capabilities across metrics, object types, CSVs, and dashboards.

​
Key Features

  • Fast dataset search
  • Multi-source search (metrics, objects, CSVs, dashboards)
  • Precise result matching
  • Resource discovery
  • Content indexing
  • Metadata exploration
  • Result type categorization
  • Relevance assessment

​
When Used

  • Dataset discovery
  • Resource location
  • Initial exploration
  • Quick information lookup
  • Metadata review
  • Availability check
  • Partial match validation
  • Alternative data source identification

​
Search Capabilities

Result Types
  1. Metrics
    • Time-series data
    • Aggregated measurements
    • Performance indicators
  2. Object Types
    • Data structures
    • Field definitions
    • Relationship mappings
  3. CSV Files
    • Static datasets
    • Reference data
    • Supplementary information
  4. Tableau Dashboards
    • Visualized analytics
    • Interactive reports
    • Supplemental analysis

​
Result Handling

Exact Matches
  • Direct field matches
  • Precise metric alignment
  • Complete data coverage
  • Immediate usability
Partial Matches
  • Similar field names
  • Related metrics
  • Potential calculations
  • Required transformations
Empty Results
  • Alternative search terms
  • Broader categories
  • Different approaches
  • Mode switching (e.g., to help mode)

​
Custom Tools

TextQL collaborates with customers to create custom tools that address their specific data analysis and workflow needs. While our standard toolkit provides powerful capabilities for most use cases, we recognize that organizations sometimes require specialized tools to maximize their efficiency. Custom tools become particularly valuable when your team needs to integrate specific methodologies, proprietary algorithms, or unique data processing approaches. For instance, if your organization has developed specialized analysis techniques or requires integration with internal tools, we can build custom solutions that seamlessly incorporate these requirements into the TextQL platform. We recommend first exploring our existing tools and capabilities, as they represent proven solutions for many common scenarios. However, if you find that your requirements extend beyond our standard offerings, we’re here to help develop tools that perfectly match your needs. To discuss custom tool development for your organization, please contact support@textql.com. We’ll collaborate to understand your specific requirements and create tools that enhance your team’s capabilities within TextQL.