Microsoft Planner as a data source

Bring data from Microsoft Planner to Nekt.

Microsoft Planner is a task management application included in Microsoft 365. It allows teams to create plans, organize and assign tasks, share files, and communicate progress, providing a visual way to manage work within Microsoft Teams and other Microsoft 365 apps.

Configuring Microsoft Planner as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Microsoft Planner option from the list of connectors.

Click Next and you’ll be prompted to add your access.

1. Add account access

You’ll need to authorize Nekt to access your Microsoft Planner data using OAuth. Click on the Microsoft Authorization button and log in with your Microsoft account that has access to the Planner plans you want to sync.

The authorization flow will request the following permissions:

• Access to Microsoft Graph API
• Read access to Groups and Planner data

Once you’re done authorizing the Nekt application, click Next.

You may need the approval of an administrator to grant the necessary permissions to the Nekt application.

If you are not an administrator, you can request the approval from an administrator by clicking on the Request approval button and providing the reason for the approval.

The administrator will then need to approve the request by clicking on the Approve button on the Microsoft Entra ID portal.

Once the approval is granted, the Nekt application will have the necessary permissions to access your Microsoft Planner data.

2. Select streams

Choose which data streams you want to sync. For faster extractions, select only the streams that are relevant to your analysis.

Tip: The stream can be found more easily by typing its name.

Select the streams and click Next.

3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table (which will effectively contain the fetched data) and the type of sync.

• Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables as the extraction runs successfully.
• Folder: a folder can be created inside the selected layer to group all tables being created from this new data source.
• Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once and make this process faster!
• Sync Type: FULL_TABLE sync is used for all streams.

Incremental sync is not supported. The Microsoft Planner API does not provide reliable modification timestamps for incremental syncing, so all streams use full table sync.

Once you are done configuring, click Next.

4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters.

To define your Trigger, consider how often you want data to be extracted from this source. This decision usually depends on how frequently you need the new table data updated (every day, once a week, or only at specific times).

Optionally, you can define some additional settings:

• Configure Delta Log Retention and determine for how long we should store old states of this table as it gets updated. Read more about this resource here.

Once you are ready, click Next to finalize the setup.

5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.

For you to be able to see it on your Catalog, you need at least one successful source run.

Streams and Fields

Below you’ll find all available data streams from Microsoft Planner and their corresponding fields:

Groups

Stream containing Microsoft 365 groups that can have Planner plans.

Field	Type	Description
id	String	Unique identifier for the group
displayName	String	Group display name
description	String	Group description
createdDateTime	Datetime	When the group was created
mail	String	Group email address
mailNickname	String	Mail nickname/alias
visibility	String	Group visibility (Public or Private)
classification	String	Classification level (e.g., low, medium, high business impact)
groupTypes[]	Array	Array of group types (e.g., “Unified” for Microsoft 365 groups)
expirationDateTime	Datetime	When the group is set to expire (if applicable)

Plans

Stream containing Planner plans within Microsoft 365 groups.

Field	Type	Description
id	String	Unique identifier for the plan
title	String	Plan title/name
createdDateTime	Datetime	When the plan was created
owner	String	(Deprecated) Owner group ID; use container.containerId instead
container.containerId	String	ID of the group or roster containing the plan
container.type	String	Type of container (e.g., “group”)
container.url	String	URL of the container resource
createdBy.user.id	String	ID of the user who created the plan
createdBy.user.displayName	String	Display name of the creator
createdBy.application.id	String	ID of the application used to create the plan
createdBy.application.displayName	String	Application display name

Buckets

Stream containing buckets (columns) within Planner plans for organizing tasks.

Field	Type	Description
id	String	Unique identifier for the bucket
name	String	Bucket display name (e.g., “To Do”, “In Progress”, “Done”)
planId	String	ID of the plan this bucket belongs to
orderHint	String	Order hint for displaying buckets in list view

Labels

Stream containing plan category labels (up to 25 custom labels per plan).

Field	Type	Description
id	String	Plan ID (matches plans.id)
category1 to category25	String	Custom label names defined for the plan

Labels are stored at the plan level. Tasks reference these labels via appliedCategories (e.g., category1: true means the task has the first label applied).

Tasks

Stream containing individual tasks within Planner plans.

Field	Type	Description
id	String	Unique identifier for the task
title	String	Task title
description	String	Task description (if hasDescription is true)
planId	String	ID of the plan containing this task
bucketId	String	ID of the bucket (column) this task is in
percentComplete	Integer	Completion percentage (0, 25, 50, 75, or 100)
priority	Integer	Priority level (0-10, where lower is higher priority)
hasDescription	Boolean	Whether the task has a description
createdDateTime	Datetime	When the task was created
startDateTime	Datetime	Task start date
dueDateTime	Datetime	Task due date
completedDateTime	Datetime	When the task was completed
assignments	String	JSON string of user assignments (user ID → assignment details)
appliedCategories	String	JSON string of applied labels (category1-category25)
createdBy.user.id	String	ID of user who created the task
createdBy.user.displayName	String	Display name of creator
completedBy.user.id	String	ID of user who completed the task
completedBy.user.displayName	String	Display name of completer
checklistItemCount	Integer	Total number of checklist items
activeChecklistItemCount	Integer	Number of incomplete checklist items
referenceCount	Integer	Number of external references/attachments
orderHint	String	Order hint for list view
assigneePriority	String	Order hint for assignee’s task list
conversationThreadId	String	ID of the conversation thread
previewType	String	Task preview type (automatic, noPreview, checklist, description, reference)

Task Details

Stream containing deeper details for Planner tasks, such as rich descriptions, checklist items, and external references. This is a child stream of Tasks.

Field	Type	Description
task_id	String	Task ID (matches tasks.id)
description	String	Task notes/description content
previewType	String	Preview type
checklist	String	Checklist items, formatted as a JSON string
references	String	External references/links, formatted as a JSON string

Data Model

The following diagram illustrates the relationships between the data streams in Microsoft Planner. Groups contain Plans, which in turn contain Buckets, Tasks, and Labels. Tasks further contain Task Details.

Use Cases for Data Analysis

This guide outlines valuable business intelligence use cases when consolidating Microsoft Planner data, along with ready-to-use SQL queries that you can run on Explorer.

1. Task Completion Overview

Track task completion rates across plans and identify bottlenecks.

Business Value:

• Monitor project progress
• Identify overdue tasks
• Track team productivity

SQL query

AWS

WITH task_metrics AS (
    SELECT
        p.title AS plan_name,
        COUNT(*) AS total_tasks,
        SUM(CASE WHEN t.percentComplete = 100 THEN 1 ELSE 0 END) AS completed_tasks,
        SUM(CASE WHEN t.dueDateTime < CURRENT_TIMESTAMP AND t.percentComplete < 100 THEN 1 ELSE 0 END) AS overdue_tasks,
        AVG(t.percentComplete) AS avg_completion
    FROM
        nekt_raw.microsoft_planner_tasks t
        JOIN nekt_raw.microsoft_planner_plans p ON t.planId = p.id
    GROUP BY
        p.title
)
SELECT
    plan_name,
    total_tasks,
    completed_tasks,
    overdue_tasks,
    ROUND(avg_completion, 1) AS avg_completion_pct,
    ROUND(completed_tasks * 100.0 / NULLIF(total_tasks, 0), 1) AS completion_rate_pct
FROM
    task_metrics
ORDER BY
    total_tasks DESC

GCP

WITH task_metrics AS (
    SELECT
        p.title AS plan_name,
        COUNT(*) AS total_tasks,
        SUM(CASE WHEN t.percentComplete = 100 THEN 1 ELSE 0 END) AS completed_tasks,
        SUM(CASE WHEN t.dueDateTime < CURRENT_TIMESTAMP() AND t.percentComplete < 100 THEN 1 ELSE 0 END) AS overdue_tasks,
        AVG(t.percentComplete) AS avg_completion
    FROM
        `nekt_raw.microsoft_planner_tasks` t
        JOIN `nekt_raw.microsoft_planner_plans` p ON t.planId = p.id
    GROUP BY
        p.title
)
SELECT
    plan_name,
    total_tasks,
    completed_tasks,
    overdue_tasks,
    ROUND(avg_completion, 1) AS avg_completion_pct,
    ROUND(SAFE_DIVIDE(completed_tasks * 100.0, total_tasks), 1) AS completion_rate_pct
FROM
    task_metrics
ORDER BY
    total_tasks DESC

Sample Result

plan_name	total_tasks	completed_tasks	overdue_tasks	avg_completion_pct	completion_rate_pct
Q1 Marketing Campaign	45	32	5	71.1	71.1
Product Launch 2024	38	28	2	73.7	73.7
Website Redesign	52	18	12	34.6	34.6
Customer Onboarding	23	20	0	87.0	87.0

2. Tasks by Bucket (Status Distribution)

Analyze task distribution across buckets to understand workflow status.

Business Value:

• Visualize work-in-progress
• Identify workflow bottlenecks
• Balance workload across stages

SQL query

AWS

SELECT
    p.title AS plan_name,
    b.name AS bucket_name,
    COUNT(*) AS task_count,
    SUM(CASE WHEN t.percentComplete = 100 THEN 1 ELSE 0 END) AS completed,
    SUM(CASE WHEN t.percentComplete > 0 AND t.percentComplete < 100 THEN 1 ELSE 0 END) AS in_progress,
    SUM(CASE WHEN t.percentComplete = 0 THEN 1 ELSE 0 END) AS not_started
FROM
    nekt_raw.microsoft_planner_tasks t
    JOIN nekt_raw.microsoft_planner_plans p ON t.planId = p.id
    JOIN nekt_raw.microsoft_planner_buckets b ON t.bucketId = b.id
GROUP BY
    p.title,
    b.name
ORDER BY
    p.title,
    task_count DESC

GCP

SELECT
    p.title AS plan_name,
    b.name AS bucket_name,
    COUNT(*) AS task_count,
    SUM(CASE WHEN t.percentComplete = 100 THEN 1 ELSE 0 END) AS completed,
    SUM(CASE WHEN t.percentComplete > 0 AND t.percentComplete < 100 THEN 1 ELSE 0 END) AS in_progress,
    SUM(CASE WHEN t.percentComplete = 0 THEN 1 ELSE 0 END) AS not_started
FROM
    `nekt_raw.microsoft_planner_tasks` t
    JOIN `nekt_raw.microsoft_planner_plans` p ON t.planId = p.id
    JOIN `nekt_raw.microsoft_planner_buckets` b ON t.bucketId = b.id
GROUP BY
    p.title,
    b.name
ORDER BY
    p.title,
    task_count DESC

Sample Result

plan_name	bucket_name	task_count	completed	in_progress	not_started
Q1 Marketing Campaign	To Do	15	0	3	12
Q1 Marketing Campaign	In Progress	12	0	12	0
Q1 Marketing Campaign	Done	18	18	0	0
Product Launch 2024	Backlog	8	0	0	8

3. Overdue Tasks Report

Identify tasks that are past their due date and need attention.

Business Value:

• Prioritize late tasks
• Track deadline adherence
• Improve project timeline management

SQL query

AWS

SELECT
    t.title AS task_title,
    p.title AS plan_name,
    b.name AS bucket_name,
    t.dueDateTime AS due_date,
    DATE_DIFF('day', t.dueDateTime, CURRENT_DATE) AS days_overdue,
    t.percentComplete AS percent_complete,
    t.priority
FROM
    nekt_raw.microsoft_planner_tasks t
    JOIN nekt_raw.microsoft_planner_plans p ON t.planId = p.id
    JOIN nekt_raw.microsoft_planner_buckets b ON t.bucketId = b.id
WHERE
    t.dueDateTime < CURRENT_TIMESTAMP
    AND t.percentComplete < 100
ORDER BY
    days_overdue DESC,
    t.priority ASC
LIMIT 20

GCP

SELECT
    t.title AS task_title,
    p.title AS plan_name,
    b.name AS bucket_name,
    t.dueDateTime AS due_date,
    DATE_DIFF(CURRENT_DATE(), DATE(t.dueDateTime), DAY) AS days_overdue,
    t.percentComplete AS percent_complete,
    t.priority
FROM
    `nekt_raw.microsoft_planner_tasks` t
    JOIN `nekt_raw.microsoft_planner_plans` p ON t.planId = p.id
    JOIN `nekt_raw.microsoft_planner_buckets` b ON t.bucketId = b.id
WHERE
    t.dueDateTime < CURRENT_TIMESTAMP()
    AND t.percentComplete < 100
ORDER BY
    days_overdue DESC,
    t.priority ASC
LIMIT 20

Sample Result

task_title	plan_name	bucket_name	due_date	days_overdue	percent_complete	priority
Update documentation	Website Redesign	In Progress	2024-11-01	26	50	1
Review contracts	Q1 Marketing Campaign	To Do	2024-11-10	17	0	3
Design mockups	Product Launch 2024	In Progress	2024-11-15	12	75	5

Implementation Notes

Stream Hierarchy

The connector extracts data using a parent-child relationship:

1. Groups are extracted first (Microsoft 365 groups with Planner enabled)
2. Plans are extracted for each group
3. Buckets, Labels, and Tasks are extracted for each plan
4. Task Details are extracted for each task

API Rate Limiting

To ensure reliable extractions and stay within Microsoft Graph API throttling limits, the connector implements proactive rate limiting. It limits API calls to a maximum of 4 requests per second. If a 429 (Too Many Requests) error does occur, the connector will automatically wait the specified time and retry the request.

JSON Fields

Some fields are stored as JSON strings for compatibility with data lake formats:

• tasks.assignments - Contains user assignment details
• tasks.appliedCategories - Contains applied label categories
• task_details.checklist - Contains checklist item details for a task
• task_details.references - Contains external links and references mapped to a task

Use JSON_EXTRACT or equivalent functions to parse these fields in your queries.

Priority Values

Task priority is stored as an integer (0-10):

• 1 = Urgent
• 3 = Important
• 5 = Medium (default)
• 9 = Low

Percent Complete Values

Microsoft Planner uses specific values for completion percentage:

• 0 = Not started
• 25 = Started
• 50 = Halfway
• 75 = Almost done
• 100 = Completed

Permissions Note

The connector only extracts data from Microsoft 365 groups that the authenticated user has access to. To extract data from all groups in an organization, ensure the account has appropriate permissions or use an admin account.

Skills for agents

Download Microsoft Planner skills file

Microsoft Planner connector documentation as plain markdown, for use in AI agent contexts.