Overview
1. Introduction
1.1 Purpose of the Overview page
The Overview page in the Context Engine provides a high-level snapshot of your Workspace activity. It serves as the starting point for understanding the overall state of your data environment — combining query performance, entity coverage, and data quality indicators in a single view.
Its main purpose is to:
Give a quick assessment of query outcomes, data structure coverage, and object health.
Highlight areas that may require further investigation, such as incorrect objects or columns with high percentages of null values.
Act as a navigation hub, allowing you to drill down into specific queries, entities, or quality metrics for more detailed insights.
By centralizing these insights, the Overview page enables you to quickly detect issues, monitor trends, and prioritize actions that will improve data accuracy and reliability across your Workspace.
1.2 Where to find it
The Overview page can be accessed from the Context Engine menu in the left navigation panel.
Click the Context Engine icon in the sidebar.
From the dropdown list, select Overview.
This will open the Overview page for the Workspace you are currently viewing (displayed in the Workspace selector at the top of the screen).
1.3 Interface layout
The Overview page is organized into distinct sections that display key information at a glance:
"General Info" section – Summarizes activity through query status charts and entity counts, giving a quick view of how many queries have been generated, edited, failed or marked incorrect. It also shows the overall number of databases, schemas, objects and columns in your Workspace.
"Quality" section – Highlights the health of your data objects. It includes visual indicators for object availability, incorrect objects grouped by schema and columns with the highest percentage of null values.
This layout is designed to allow quick scanning for problem areas while providing clear entry points to investigate specific issues in more detail.
1.4 Key benefits of using the "Overview" page
The Overview page delivers immediate value by combining activity tracking and data quality monitoring in one place. Its key benefits include:
Centralized insight – View query statuses, entity counts, and quality metrics without switching between multiple tools or screens.
Faster issue detection – Identify failed queries, incorrect objects, and high-null columns early, before they cause downstream problems.
Data-driven prioritization – Focus your efforts on the areas that will have the biggest impact on data accuracy and reliability.
Efficient navigation – Use the visual charts and counts as clickable entry points to drill down into detailed views for deeper analysis.
Proactive maintenance – Regularly monitor the health of your Workspace to prevent issues from escalating over time.
By providing both a snapshot and direct paths for investigation, the Overview page streamlines the process of keeping your Workspace accurate, consistent, and ready for use.
2. "General Info" section
2.1 Queries
The Queries panel in the General Info section shows the distribution of query statuses in your Workspace. It uses a donut chart for quick visual analysis and allows category-based filtering.
Query status categories
Edited – Queries manually adjusted after AI generation.
Failed – Queries that returned an error or could not be executed.
Generated – Queries created by AI and not yet reviewed by a user.
Incorrect – Queries automatically flagged by the system as containing issues that make them unreliable.
Filtering queries by category
Click a legend item to remove that category from the donut chart, adjusting the visual distribution.
Click a slice in the donut chart to open a new window showing only the queries in that category, allowing focused review and action.
2.2 Catalog
The Catalog panel in the General Info section displays the total count of key data components in your Workspace. It provides a quick snapshot of the scope of your available data structure:
Databases – The number of databases connected to your Workspace.
Schemas – The number of schemas detected across all connected databases.
Objects – The number of objects (such as tables or views) available.
Columns – The total number of columns across all objects.
Interacting with entity types
Clicking on an entity type opens the Catalog with the corresponding tab pre-selected:
Databases tab – Lists all connected databases, with schema and table counts.
Schema tab – Shows all schemas for the selected database, with related table counts.
Objects tab – Displays objects, their types, states (Available/Deleted), row counts, and sizes.
Columns tab – Lists columns, data types, states, descriptions, and data sensitivity flags.
This direct link between the Overview and Catalog makes it faster to explore the structure, inspect metadata and drill down into specific database elements without manual navigation.
2.3 Metricverse
The Metricverse panel provides a snapshot of how entities in your Workspace are being used. It highlights whether these entities are newly created, reused, or verified.
Usage categories:
Used once (unverified): Entities that appear for the first time and are not yet reviewed.
Reused (unverified): Entities that are leveraged multiple times but remain unverified.
Verified: Entities that have been reviewed and approved as trusted.
Purpose:
Track how consistently business logic is being applied.
Detect duplication and encourage reuse of existing entities.
Increase confidence by showing the proportion of verified components.
Interaction:
Hover over a bar to see exact counts by category.
Click on a usage category (e.g., Reused) to include or exclude it from the chart.
2.4 Human Input (coming soon)
3. Quality section
3.1 Object state
The Object State panel in the Quality section shows the availability status of objects in your Workspace. It helps you quickly determine whether your data sources are intact and usable.
Available vs Deleted/Unavailable objects
Available – Objects that are currently accessible and can be used in queries without issues.
Deleted/Unavailable – Objects that are no longer accessible, often due to changes or removals in the upstream data source. These may also appear if the connection to the source system is broken.
Impact on query results
Connecty AI automatically skips Deleted/Unavailable objects when generating or executing queries to avoid errors. However, if a previously available object becomes unavailable, any existing queries depending on it may fail or produce incomplete results.
Monitoring this panel regularly helps ensure that:
Your active queries are not relying on unavailable data.
You can take corrective action, such as updating queries to reference valid objects or restoring missing data sources.
3.2 Incorrect Objects per Schema
The Incorrect Objects per Schema panel shows the percentage of objects within each schema that have been flagged as incorrect. This provides a quick view of where data quality issues are concentrated at the schema level.
Purpose:
Identify schemas with a higher proportion of incorrect objects.
Quickly assess the relative health of different schemas in your Workspace.
3.3 Most % of Nulls (coming soon)
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