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Client self-serve data slicing

Client self-serve slicing means your client opens a published Insight Hub and filters or explores data on their own. You choose which columns are available; they do the cuts without a new change order.

This guide combines steps from the dashboard explorable docs and the filter docs. Terminology in the product may say Story Dashboard or Dashboard; published hubs use the same publish and explorable settings.

Part 1: Publish and share the link (analyst)

Before clients can slice data, publish your dashboard and send them the link.

  1. Open your dashboard
  2. Click Actions → Manage Publishing
  3. Choose Publish on AddMaple.com (public) or Publish with password (private)
  4. Click Save Changes
  5. Copy the Public Link and send it to your client

See Publish a dashboard, Password protection, and Share with clients.

Part 2: Enable Data Explorable (analyst)

With the dashboard published, turn on explorable data and choose which columns clients can access.

  1. Open your dashboard
  2. Click Actions → Manage Publishing
  3. Turn on Data Explorable
  4. Select columns to include (required)
  5. Click Save Changes

Notes from the explorable guide:

  • Explorable controls are disabled when the dashboard is Unpublished — publish first (Part 1)
  • Column choices must exist in your dataset

See Make data explorable.

Privacy: If a hub will be shared widely, avoid selecting columns with personally identifiable information. The older report explorable guide notes that explorable data can be visible at the row level. See How to make your data explorable.

Part 3: What clients see

On a published hub with explorable data enabled, viewers see a notice that the Story Dashboard includes explorable data and an Explore button at the top.

When they click Explore, they open the selected columns in the full AddMaple interface (the same tools you use to filter and pivot, limited to the columns you chose).

The report explorable guide describes a similar viewer path with an Analyze this dataset link for older report publish flows.

Part 4: How clients slice data (viewer)

Once in explore mode, clients can filter using the same methods documented for analysts:

Filter button

From the summary, chart, table, or raw data views, click Filter at the top (or press /).

Choose a column and filter value. AddMaple applies the filter across the dataset instantly.

From a chart

Hover a bar (or equivalent) and choose Filter by this value.

From table view

Click an MC+ or MC value in a row to filter by it.

See Filter your data, Filter types, and How to pivot your data.

Subgroup views vs self-serve slicing

  • Subgroup views (analyst-built): You define the audience or segment and save charts for clients. See Subgroup views.
  • Self-serve slicing (client-built): You expose selected columns; clients filter and pivot on their own. This guide.

Many teams use both: pre-built mini-dashboards for key stories, plus explorable columns for ad hoc follow-ups.

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