Data tables

Data Tables provide a structured way to store and manage information that requires precise retrieval and presentation.

Unlike the Knowledge Base, which handles less structured and context-heavy content, Data Tables are ideal for organized, formatted data where accuracy is crucial.

Example of a table

Overview

Data Tables enable you to:

• Store structured information in a tabular format

• Ensure accurate data retrieval

• Generate visual cards during conversations

• Filter and query specific information

Data Types

Data Tables support various types of content:

Selecting data type for a column

Note that a column's data type can only be assigned upon creation, it cannot be changed later on.

Basic Types

• String: Text content

• Number: Numerical values

• Boolean: True/false values

• Date: Calendar dates

• DateTime: Dates with time information

Rich Content Types

• Image: Visual content

• JSON: Structured data objects

• Code: Programming code snippets

Working with Tables

Creating Tables

1. Navigate to Data Tables section

2. Click "Add table"

3. Define table structure:

   • Add columns

   • Specify data types

   • Add descriptions (optional)

Adding Columns

Each column requires:

• Column name

• Data type selection

• Optional description for clarity

Managing Records

• Add records individually

• Edit existing records

• Delete outdated information

Using Data Tables in Conversations

Data Retrieval

Data Tables excel in scenarios requiring precise information:

• Product specifications

• Pricing information

• Service details

• Configuration data

Filtering and Queries

In Conversation Flows, you can:

• Filter records based on specific criteria

• Search for exact matches

• Compare numerical values

• Check date ranges

Visual Cards

Data Tables can generate visual cards during conversations:

• Present structured information clearly

• Show product details

• Display different options in a visual manner

Best Practices

Table Structure

• Use clear, consistent column names

• Choose appropriate data types (cannot be changed after the column is created)

• Add descriptions for complex fields

• Keep table structure simple and focused

Data Management

• Regular updates to maintain accuracy

• Archive outdated information

• Validate data during entry

• Monitor table size and performance

Integration Tips

• Use tables for factual, structured data

• Combine with Knowledge Base for comprehensive responses

• Design tables with conversation flow needs in mind

Example Use Cases

Product Catalog

The Product Catalog use case is ideal for e-commerce and retail applications where your virtual being needs to access accurate product information.

Columns:
- Product ID (String)
- Name (String)
- Price (Number)
- Image (Image)
- Specifications (JSON)

This structure enables your virtual being to:

• Present products with consistent information

• Show visual product representations in cards

• Answer detailed questions about specifications

• Provide accurate pricing information

• Filter and sort products based on attributes

Service Pricing

Perfect for subscription-based services or tiered pricing models where accurate pricing and feature information is crucial.

Columns:
- Plan Name (String)
- Price (Number)
- Features (JSON)
- Availability (Boolean)

This structure allows your virtual being to:

• Compare different service tiers

• Present accurate pricing information

• Detail included features per plan

• Show only currently available options

• Create visual pricing comparison cards

Configuration Settings

Ideal for managing system settings, preferences, or any time-sensitive configuration data that needs tracking.

Columns:
- Setting Name (String)
- Value (String)
- Last Updated (DateTime)
- Status (Boolean)

This structure helps your virtual being:

• Provide accurate system settings information

• Track configuration changes over time

• Verify setting validity before use

• Manage feature toggles and states

Remember that Data Tables are best used for structured, factual information where accuracy is crucial. For more narrative or context-heavy content, consider using the Knowledge Base instead.