Getting Started with Mapping Clarity

This guide provides a quick overview of the core workflow, from logging in to reviewing and downloading your mapped data.

Written By Andrew Sheridan

Last updated 3 months ago

1. Accessing Mapping Clarity

A. Log In or Sign Up

To begin using Mapping Clarity, you can log in or create your free account.

Sign up Page

2. Setting Up Data Targets

A "Target" is the specific classification or normalized value you want your raw data to map to (e.g., standard industry codes, standardized vendor names). You can use global, pre-defined targets, or create your own custom targets.

A. Creating Custom Targets

To define your own specific classifications, navigate to the Custom Targets section.

Action: Go to https://app.mappingclarity.com/custom-targets and select Create Custom Target.

B. Understanding Target Types

You must choose one of three types, which determines how the Mapping Clarity AI processes your data.

Target Type

Use Case & Description

Best For...

List + Definitions

Select this if your target is a defined list or taxonomy where each item has a written definition. The definition greatly improves the AI's understanding, leading to higher mapping accuracy.

Well-defined standards and comprehensive taxonomies.

List Only

Choose this if you have a defined list of values (e.g., a set of unique IDs) that the data must map to. The algorithm will strictly map only to items on this list.

Strict classification where no external values are permitted.

Pattern

Select this if you want the AI and algorithm to learn mapping based on context, previously uploaded examples, and real-world data patterns. You do not need a predetermined list.

Normalization tasks like "Vendor Normalization," where an exact target list doesn't exist yet.

3. Creating a Data Pipeline

A Pipeline defines which set of targets (custom or global) your incoming data will be mapped against.

Action: Create your pipeline at https://app.mappingclarity.com/pipelines.

  • If you intend to use the same targets repeatedly (e.g., for a weekly data load), create an enduring Pipeline here.

  • If you only need a temporary mapping for a one-off upload, you can create a simple pipeline during the upload process itself.

4. Uploading and Processing Data

Once your targets and pipeline are ready, you can upload your data file.

Action: Go to the Upload page at https://app.mappingclarity.com/upload, select your desired pipeline (or create a temporary one), and upload your data.

Pro Tip: Pre-Trained Columns If your uploaded data has a column header that exactly matches the name of one of your Targets, Mapping Clarity will treat the values in that column as "ground truth." This bypasses the mapping process for that column and uses the existing value. This feature is useful for uploading historical, correctly mapped data to pre-train the algorithm before processing new, unclassified data.

Tracking Progress

After uploading, data processing begins automatically. You can track the status of your job at https://app.mappingclarity.com/jobs. You will also receive an email notification once the job is complete.

5. Reviewing and Downloading Data

The final step is to review the AI's mapping results and download the final, cleansed data.

Action: Go to https://app.mappingclarity.com/upload and click on the specific job name to open the review screen.

Reviewing Mappings

Inside the job view, the mapped results are automatically ordered by confidence score. This allows you to quickly review and manually correct any mappings where the AI had low confidence.

Downloading Results

Once you have made any necessary corrections, finalize your data.

Action: Click the Download as CSV button to retrieve your final, fully mapped dataset.