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Merge pull request #5130 from segmentio/fix-plan-notes
Added plan-grid note to frontmatter
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src/connections/destinations/actions.md

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title: Destination Actions
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plan: dest-actions
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---
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{% include content/plan-grid.md name="dest-actions" %}
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The Destination Actions framework improves on classic destinations by enabling you to see and control how Segment sends the event data it receives from your sources, to actions-based destinations. Each Action in a destination lists the event data it requires, and the event data that is optional.
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You can also choose which event types, event names, or event property values trigger an Action. These Triggers and mappings make it possible to send different versions of the Action, depending on the context from which it is triggered.

src/connections/storage/data-lakes/comparison.md

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title: Comparing Data Lakes and Warehouses
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plan: data-lakes
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---
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{% include content/plan-grid.md name="data-lakes" %}
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As Segment builds new data storage products, each product evolves from prior products to best support the needs of customers. Segment Data Lakes is an evolution of the Warehouses product that meets the changing needs of customers.
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src/connections/storage/data-lakes/data-lakes-manual-setup.md

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hidden: true
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title: Configure the Data Lakes AWS Environment
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plan: data-lakes
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---
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{% include content/plan-grid.md name="data-lakes" %}
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The instructions below will guide you through the process required to configure the environment required to begin loading data into your Segment Data Lake. For a more automated process, see [Set Up Segment Data Lakes](/docs/connections/storage/catalog/data-lakes).
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src/connections/storage/data-lakes/index.md

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title: Segment Data Lakes Overview
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redirect_from: '/connections/destinations/catalog/data-lakes/'
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plan: data-lakes
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---
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{% include content/plan-grid.md name="data-lakes" %}
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> warning "Segment Data Lakes (Azure) deletion policies"
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> Data deletion is not supported by Segment Data Lakes (Azure), as customers retain data in systems that they manage.
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src/connections/storage/data-lakes/lake-formation.md

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title: Lake Formation
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plan: data-lakes
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{% include content/plan-grid.md name="data-lakes" %}
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Lake Formation is a fully managed service built on top of the AWS Glue Data Catalog that provides one central set of tools to build and manage a Data Lake. These tools help import, catalog, transform, and deduplicate data, as well as provide strategies to optimize data storage and security. To learn more about Lake Formation features, see [Amazon Web Services documentation](https://aws.amazon.com/lake-formation/features/){:target="_blank"}.
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The security policies in Lake Formation use two layers of permissions: each resource is protected by Lake Formation permissions (which control access to Data Catalog resources and S3 locations) and IAM permissions (which control access to Lake Formation and AWS Glue API resources). When any user or role reads or writes to a resource, that action must pass a both a Lake Formation and an IAM resource check: for example, a user trying to create a new table in the Data Catalog may have Lake Formation access to the Data Catalog, but if they don't have the correct Glue API permissions, they will be unable to create the table.

src/connections/storage/data-lakes/sync-history.md

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title: Data Lakes Sync History and Health
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plan: data-lakes
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{% include content/plan-grid.md name="data-lakes" %}
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The Segment Data Lakes sync history and health tabs generate real-time information about data syncs so you can monitor the health and performance of your data lakes. These tools provide monitoring and debugging capabilities within the Data Lakes UI, so you can identify and proactively address data sync or data pipeline failures.
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src/connections/storage/data-lakes/sync-reports.md

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title: Data Lakes Sync Reports and Errors
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plan: data-lakes
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{% include content/plan-grid.md name="data-lakes" %}
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Segment Data Lakes generates reports with operational metrics about each sync to your data lake so you can monitor sync performance. These sync reports are stored in your S3 bucket and Glue Data Catalog. This means you have access to the raw data, so you can query it to answer questions and set up alerting and monitoring tools.
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src/connections/storage/warehouses/index.md

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title: Data Warehouses
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redirect_from: '/connections/warehouses/'
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plan: warehouses
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---
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{% include content/plan-grid.md name="warehouses" %}
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## What's a Warehouse?
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{% include content/whats-a-warehouse.md %}

src/guides/what-is-replay.md

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title: Replay
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plan: replay
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{% include content/plan-grid.md name="replay" %}
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Replay takes an archived copy of your Segment data, and re-sends it to new or existing tools.
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On the surface this doesn't sound like much, but this can grant huge benefits to mature data systems: By archiving and replaying data, you can avoid vendor lock-in, and protect your system against data loss.

src/privacy/data-controls.md

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title: Privacy Controls & Alerts
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plan: privacy
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{% include content/plan-grid.md name="privacy" %}
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The Privacy Portal gives you control over whether specific data is allowed to
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enter Segment.

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