📥 Importing Data with Data Sources in ServiceNow

CASE STUDY 1: 🌐 1. Introduction

Importing data is a key feature in ServiceNow that allows administrators and developers to bring external information into the platform.

• Data can come from spreadsheets, databases, LDAP directories, REST/SOAP APIs, or flat files.

• ServiceNow uses Data Sources as the foundation for defining where the data originates.

💡 Key Benefit: A well-defined Data Source ensures a smooth, automated pipeline from external systems into ServiceNow tables.

📑 2. What is a Data Source?

A Data Source in ServiceNow defines the location and format of data being imported. It tells the platform where to get the data and how to read it.

Common Types of Data Sources:

1. File-based Sources

   • Excel (.xls, .xlsx)

   • CSV files

   • XML

2. Database Sources

   • JDBC connections (e.g., Oracle, MySQL, SQL Server)

3. Directory Sources

   • LDAP (Active Directory integration)

4. Web Services

   • REST APIs

   • SOAP services

5. Other Sources

   • JSON files

   • IntegrationHub ETL connectors

🛠️ 3. Import Process Overview

The data import process in ServiceNow involves 3 main stages:

1. Define Data Source

   • Example: Upload an Excel file with employee data.

2. Import Set Table (Staging Table)

   • Data is first stored in a temporary table (u_import_employees).

3. Transform Map

   • Maps fields from Import Set Table → Target Table (e.g., sys_user).

   • Uses coalesce fields to prevent duplicates.

4. Load Data

   • Preview the transformation.

   • Commit the transformation into the target table.

CASE STUDY 2:📋 Example: Importing Users from CSV

Scenario: Importing employee details into sys_user.

Step 1: Create Data Source

• Navigate to System Import Sets → Load Data.

• Upload employees.csv.

Step 2: Generate Import Set Table

• System creates staging table u_import_employees.

Step 3: Create Transform Map

• Source: u_import_employees

• Target: sys_user

• Field Mapping:

  • u_name → name

  • u_email → email

  • u_department → department

Step 4: Coalesce on Email

• Ensures updates instead of duplicate records.

Step 5: Run Transform

• Data is inserted into sys_user.

⚡ Advanced Data Source Concepts

1. Scheduled Data Imports

   • Automatically run imports daily/weekly (e.g., HR feed from Workday).

2. Data Source Credentials

   • Securely store authentication for APIs and databases.

3. Transform Scripts

   • Add custom logic before/after import.

   (function transformEntry(source, target) {
       if (!target.active) {
           target.active = true; // auto-enable users
       }
   })(source, target);
   

4. Data Policies & Business Rules

   • Validate and enforce rules on imported data.

5. Reconciliation with CMDB (IRE)

   • Ensures CI uniqueness when importing into the CMDB.

6. IntegrationHub ETL

   • Advanced extraction, transformation, and loading for large-scale integrations.

CASE STUDY 3:📊 Real-World Examples

• HR Integration: Import new hires from Workday into sys_user daily.

• Asset Management: Import device inventory from an external asset system.

• CMDB Population: Import server inventory from AWS or Azure into cmdb_ci_server.

• Vendor Data: Import vendor contacts from a CSV file quarterly.

💡 Best Practices

• ✅ Always import data into staging tables first (never directly into target).

• ✅ Use coalesce fields to avoid duplicates.

• ✅ Automate imports with scheduled data sources.

• ✅ Test imports in sub-production instances.

• ✅ Document mappings and scripts for governance.

• ❌ Avoid importing massive datasets without batching (may affect performance).

🎬 Clean Conclusion

Data Sources are the backbone of ServiceNow data imports.

• They define where data comes from and how it enters ServiceNow.

• Paired with Import Sets and Transform Maps, they ensure accurate and reliable data migration.

• With scheduling, reconciliation, and ETL tools, ServiceNow supports both simple CSV imports and complex enterprise integrations.