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Datastore Tags Introduction

Overview

Tags on datastores allow you to categorize, organize, and filter your data sources. A single datastore can have multiple tags, and a single tag can be applied to many datastores — providing a flexible, multi-dimensional classification system.

When you assign a tag to a datastore, it automatically inherits down to all containers (tables/files), fields, checks, and anomalies within that datastore. This means you can tag at the datastore level and instantly have all related assets categorized.

Tags vs. Datastore Tags

This page covers how tags work in the context of source datastores — inheritance, operation filtering, and quality score impact. For the general concepts behind tags in Qualytics (tag types, properties, creating, editing, deleting), see the Tags documentation.

Why Use Tags on Datastores?

Tags on datastores serve several purposes specific to the datastore context:

  • Categorization — Classify datastores by environment (Production, Staging, Development), compliance (HIPAA, PCI, SOX), team (Engineering, Finance, Marketing), or any custom category.
  • Operation Filtering — Use tags to scope Profile and Scan operations to specific containers. Instead of selecting containers individually, you can run an operation on all containers tagged with Critical.
  • Quality Score Weighting — Tags have a weight modifier that influences how container quality scores are calculated. Higher-weighted tags make their containers more impactful in the overall datastore quality score.
  • Navigation — Quickly find and access datastores using tag-based filtering in the navigation tree.

Tag Inheritance

When you assign a tag to a datastore, the tag cascades immediately and synchronously to all child assets — there is no delay or background processing.

graph TD
    A["<b>Datastore</b><br/>Tag: Production"] --> B["<b>Container</b> (Table/File)<br/>Inherits: Production"]
    B --> C["<b>Field</b> (Column)<br/>Inherits: Production"]
    B --> D["<b>Check</b> (Quality Rule)<br/>Inherits: Production"]
    D --> E["<b>Anomaly</b><br/>Inherits: Production"]

Tagging a datastore is a powerful way to classify your entire data lineage in one action. When tags change on a datastore, all child assets are updated in real time — containers, fields, and checks are re-tagged, and quality score weights are recalculated immediately.

Using Tags in Operations

Tags can be used to filter which containers are included in Profile and Scan operations:

  • When scheduling or running an operation, you can specify container tags instead of selecting individual containers.
  • Only containers that have the specified tags will be included in the operation.
  • This is especially useful for large datastores where you want to focus quality checks on specific subsets of data.

Configuring Tag Filters in Operations

When running a Profile or Scan operation, select the Tag option in the container selection step to filter by tags. See the Scan Operation or Profile Operation documentation for step-by-step instructions.

Note

Tags and container selection are mutually exclusive in operations — you can filter by tags or by specific container names, but not both at the same time.

Quality Score Impact

When tags with a weight modifier are assigned to a datastore, Qualytics recalculates the relative importance of each container in the quality score:

  1. The weight modifiers of all tags on each container are summed.
  2. The minimum sum across all containers is used as a baseline offset so that all weights are at least 1.
  3. The final weight formula is: weight = sum(tag modifiers) + abs(min_weight) + 1.
  4. Higher-weighted containers have more impact on the overall datastore quality score via weighted average.

Removing a tag with a weight modifier triggers an automatic recalculation of all container quality scores within the datastore.

Weight Modifier Example

Suppose a datastore has 3 containers and 2 tags:

  • Tag: Critical — weight modifier: 3
  • Tag: Standard — weight modifier: 1

Step 1 — Sum tag modifiers per container:

Container Tags Sum of Modifiers
orders Critical 3
customers Critical, Standard 4
logs Standard 1

Step 2 — Apply formula (weight = sum + abs(min) + 1, where min = 1):

Container Sum Weight (sum + 1 + 1) Relative Impact
orders 3 5 Medium
customers 4 6 Highest
logs 1 3 Lowest

When calculating the datastore quality score, each container's score is multiplied by its weight and divided by the total weight (5 + 6 + 3 = 14). A quality issue in customers (weight 6) has twice the impact of the same issue in logs (weight 3).

Note

Weight modifiers range from -10 to +10 per tag. The formula guarantees all final weights are at least 1, even when negative modifiers are used. Weights are not normalized to sum to 100% — they are raw multipliers used in a weighted average calculation.

Info

For more details on weight modifiers and how they affect scoring, see the Weighting documentation.

Next Steps

  • Assign a Tag

    Assign an existing tag to a source datastore.

    Assign a Tag

  • Unassign a Tag

    Remove a tag from a source datastore.

    Unassign a Tag