MatchbookAI Documentation

Matchbook AI is a data management and matching tool designed to help businesses maintain and optimize their data quality, improve data governance, and streamline data stewardship workflows. By centralizing data from multiple sources, Matchbook enables users to manage, cleanse, enrich, and match records to ensure accuracy and consistency across business functions. The tool’s automated matching algorithms and data enrichment processes allow users to handle large volumes of records with varying confidence levels, effectively identifying and managing duplicate or conflicting entries.

Contents:

• Getting Started
  • Login
    • Using your Matchbook email ID and password
    • Login with Google
    • Login with Microsoft
    • Login with Okta
    • Send Sign in Link
  • Forgot Password
  • Navigation
    • Dashboard
    • Import Data
    • Data Stewardship
    • Prospecting
    • Export Data
    • Compliance
    • Reports
    • Settings
• Dashboard
  • Overview
  • Active Data Queue Statistics
  • Background Process Statistics
    • Cleanse Match
    • Data Enrichment
  • Low Confidence Match Candidate Statistics
    • Top Candidates (Priority records for review)
    • All Candidates
  • Data Stewardship Statistics
  • API Usage Statistics
• Import Data
  • Manually Upload Data
  • Automating Data Upload
  • Import Data Process
  • Manually Upload Data
  • 1. Import Data from File
  • 2. Import Data from Single Record
    • Enrichment Only
  • Automating Data Upload
  • 1. Import Data from External Source
  • 2. Import Data from Rest APIs
  • Data Mapping
    • Additional Fields
    • Alternate Addresses
    • Reference Fields
    • Ordinal Mapping
  • File Template
  • 1. Add Template
  • 2. Edit Template
  • 3. Delete a Template
  • Tags
  • Data Integration
  • Template Configuration
  • Source Folder Path
  • File Name Pattern
• Data Stewardship
  • Overview
  • Review Match Candidate
  • Low Confidence
    • Reject Records
    • Reject Records on the Page
    • Accept Records from File
    • Apply Match Rules
    • Configure Scoring
  • No Match
    • Purge
    • Re-match
  • Preview Matched Data
• Prospecting
  • Overview
    • 1. Search Data
    • 2. Build a List
    • Search Data
    • Build a List
  • Action Buttons
• Export Data
  • Overview
  • Export Data
    • Step 1: Apply Filters (Optional)
    • Step 2: Select Output
    • Step 3: Select Output Format
    • Step 4: Select Encryption Key (Optional)
    • Step 5: Select External Data Source (Optional)
    • Step 6: Finalize Export (Optional)
    • Scheduled Export Details
• Reports
  • Overview
    • Base Report
    • Investigation Report
  • Metrics Dashboard
    • Stewards Metrics
    • Import File Metrics
    • Identity Resolution Metrics
• Settings
  • Overview
    • Portal
  • DnB
    • General Settings
    • License
    • Identity Resolution
      • Minimum Match criteria
        • Global Minimum Match Criteria
        • Minimum Match Criteria Override
          • Override Detail
          • Override List
      • Exclusions
        • Exclusion Options
      • Auto Acceptance
        • Additional Auto-Accept Filter
        • Additional Auto-Accept Rules
          • Additional Actions
          • Creating and Editing Auto-Acceptance Rules
            • Add New Auto Acceptance Rule
            • Edit Auto Acceptance Rule
            • Delete Rule
      • Auto-Acceptance Directives
        • Limiting Directives
        • Preference Directives
      • Multi-Pass Configuration
      • Scoring Configuration
• Connector- Snowflake
  • User Guide
  • Log in to Snowflake
  • Access Snowflake account for individual
  • Setting Up the Database and Schema
    • Creating Database and Schema
  • Creating Worksheets
    • Create Separate worksheet
    • Configuring Database and Schema
    • Adding source data assets
    • Load data
  • Deploying Scripts and Sharing Data in Snowflake
    • Managing the key vault
    • Managing Auth token
    • Retrieving the Token for the Client
    • Process Enrichment Data
      • Optimization
      • Run Jobs
      • Running the Cleansematch Process
        • Initial Setup
        • Configuration and Validation
        • Database and Table Management
      • Process Enrichment Data
      • Downloading Matched Data
  • Implementation guide
  • Implementation Commands.sql
  • General Requirements
    • Secrets Management
    • Cleanup
    • Logging
    • Onboarding
    • Common Configuration
    • Retrieval
  • Workflow
    • Cleansematch (main.py)
      • Job Configurations
      • Process
      • Columns added by Matchbook AI in the destination_table
    • Download Matched Data (refresh_records.py)
      • Job Configurations
      • Source Table Schema
      • Process
    • Process Enrichment Data (process_enchrichment_data.py)
      • Job Configurations
      • Destination Table Schema
      • Process Flow
    • Monitoring
  • Data Movement with Status
    • Cleansematch
    • Download Matched Data
    • Process Enrichment Data
  • API Calls Guidelines
  • Task Scheduling
    • Create a Warehouse for Task Execution
    • Task Setup
      • Option 1: Monitoring Job Every 5 mins
      • Option 2: Production Job Sequence with Dependencies
    • Activating Tasks
    • Running Tasks Manually (Optional)
  • Monitor Task Execution
• Connector- Databricks
  • Navigating Databricks and Delta Sharing
    • Retrieve the Sharing Identifier
    • Create Separate Catalogs
    • Task Scheduling / Workflows
      • How to start the workflow
      • How to schedule recurring workflow run
    • Sharing the catalog
      • Use case:
    • Share Data
      • Share Name
      • Adding Data assets
      • Adding Notebooks
      • Add Recipient
    • Managing the key vault
    • Managing Auth token
    • Retrieving the Token for the Client
    • Import Data
    • Process Enrichment Data
      • Optimization
      • Run Jobs
      • Assign Jobs to Clients
      • Running the Cleansematch Process
        • Initial Setup
        • Configuration and Validation
      • Process Enrichment Data
      • Downloading Matched Data
      • Monitoring