home / skills / jeremylongshore / claude-code-plugins-plus-skills / guidewire-data-handling

This skill helps you implement Guidewire data handling best practices for entity management, migrations, batch operations, and governance to ensure data

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill guidewire-data-handling

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
24.8 KB
---
name: guidewire-data-handling
description: |
  Data handling best practices for Guidewire InsuranceSuite including entity management,
  data migration, batch operations, and data governance.
  Trigger with phrases like "guidewire data", "entity management",
  "data migration", "batch processing", "data governance guidewire".
allowed-tools: Read, Write, Edit, Bash(curl:*), Bash(gradle:*), Grep
version: 1.0.0
license: MIT
author: Jeremy Longshore <[email protected]>
---

# Guidewire Data Handling

## Overview

Best practices for data handling in Guidewire InsuranceSuite including entity management, CRUD operations, data migration, batch processing, and data governance.

## Prerequisites

- Understanding of Guidewire data model
- Access to Guidewire documentation
- Familiarity with Gosu programming

## Data Model Overview

```
┌─────────────────────────────────────────────────────────────────────────────────┐
│                        Guidewire Core Data Model                                 │
├─────────────────────────────────────────────────────────────────────────────────┤
│                                                                                  │
│  ┌───────────────────────────────────────────────────────────────────────────┐  │
│  │                            PolicyCenter                                    │  │
│  │  ┌─────────┐    ┌─────────┐    ┌─────────┐    ┌─────────┐               │  │
│  │  │ Account │───▶│  Policy │───▶│ Period  │───▶│Coverage │               │  │
│  │  │         │    │         │    │         │    │         │               │  │
│  │  │Contacts │    │ Jobs    │    │ Lines   │    │ Terms   │               │  │
│  │  └─────────┘    └─────────┘    └─────────┘    └─────────┘               │  │
│  └───────────────────────────────────────────────────────────────────────────┘  │
│                                                                                  │
│  ┌───────────────────────────────────────────────────────────────────────────┐  │
│  │                            ClaimCenter                                     │  │
│  │  ┌─────────┐    ┌─────────┐    ┌─────────┐    ┌─────────┐               │  │
│  │  │  Claim  │───▶│Exposure │───▶│ Reserve │───▶│ Payment │               │  │
│  │  │         │    │         │    │         │    │         │               │  │
│  │  │Incidents│    │Claimants│    │ Checks  │    │Recovery │               │  │
│  │  └─────────┘    └─────────┘    └─────────┘    └─────────┘               │  │
│  └───────────────────────────────────────────────────────────────────────────┘  │
│                                                                                  │
│  ┌───────────────────────────────────────────────────────────────────────────┐  │
│  │                           BillingCenter                                    │  │
│  │  ┌─────────┐    ┌─────────┐    ┌─────────┐    ┌─────────┐               │  │
│  │  │ Account │───▶│ Invoice │───▶│ Charge  │───▶│ Payment │               │  │
│  │  │         │    │         │    │         │    │         │               │  │
│  │  │ Policy  │    │  Items  │    │ Credits │    │Disbursement│            │  │
│  │  └─────────┘    └─────────┘    └─────────┘    └─────────┘               │  │
│  └───────────────────────────────────────────────────────────────────────────┘  │
│                                                                                  │
└─────────────────────────────────────────────────────────────────────────────────┘
```

## Instructions

### Step 1: Entity CRUD Operations

```gosu
// Gosu entity management patterns
package gw.data.entity

uses gw.api.database.Query
uses gw.api.util.Logger
uses gw.transaction.Transaction

class EntityManager {
  private static final var LOG = Logger.forCategory("EntityManager")

  // CREATE - Single entity
  static function createAccount(data : AccountData) : Account {
    return Transaction.runWithNewBundle(\bundle -> {
      var account = new Account(bundle)
      account.AccountNumber = generateAccountNumber()

      var contact = new Person(bundle)
      contact.FirstName = data.FirstName
      contact.LastName = data.LastName
      contact.DateOfBirth = data.DateOfBirth
      contact.EmailAddress1 = data.Email

      var address = new Address(bundle)
      address.AddressLine1 = data.AddressLine1
      address.City = data.City
      address.State = State.get(data.StateCode)
      address.PostalCode = data.PostalCode
      contact.PrimaryAddress = address

      account.AccountHolderContact = contact

      LOG.info("Created account: ${account.AccountNumber}")
      return account
    })
  }

  // READ - Single entity
  static function findAccountByNumber(accountNumber : String) : Account {
    return Query.make(Account)
      .compare(Account#AccountNumber, Equals, accountNumber)
      .select()
      .AtMostOneRow
  }

  // READ - Multiple entities with filtering
  static function findActiveAccountsByState(stateCode : String, limit : int = 100) : List<Account> {
    return Query.make(Account)
      .compare(Account#AccountStatus, Equals, AccountStatus.TC_ACTIVE)
      .join(Account#AccountHolderContact)
      .join(Contact#PrimaryAddress)
      .compare(Address#State, Equals, State.get(stateCode))
      .select()
      .orderBy(\a -> a.AccountNumber)
      .take(limit)
      .toList()
  }

  // UPDATE - Single entity
  static function updateAccount(accountNumber : String, data : AccountUpdateData) : Account {
    return Transaction.runWithNewBundle(\bundle -> {
      var account = findAccountByNumber(accountNumber)
      if (account == null) {
        throw new IllegalArgumentException("Account not found: ${accountNumber}")
      }

      account = bundle.add(account)

      if (data.Email != null) {
        account.AccountHolderContact.EmailAddress1 = data.Email
      }

      if (data.Phone != null) {
        account.AccountHolderContact.HomePhone = data.Phone
      }

      LOG.info("Updated account: ${accountNumber}")
      return account
    })
  }

  // DELETE - Single entity (soft delete)
  static function deactivateAccount(accountNumber : String) {
    Transaction.runWithNewBundle(\bundle -> {
      var account = findAccountByNumber(accountNumber)
      if (account == null) {
        throw new IllegalArgumentException("Account not found: ${accountNumber}")
      }

      account = bundle.add(account)
      account.AccountStatus = AccountStatus.TC_INACTIVE

      LOG.info("Deactivated account: ${accountNumber}")
    })
  }

  private static function generateAccountNumber() : String {
    return "ACC-${System.currentTimeMillis()}"
  }
}
```

### Step 2: Batch Data Operations

```gosu
// Batch processing patterns
package gw.data.batch

uses gw.api.database.Query
uses gw.api.util.Logger
uses gw.transaction.Transaction
uses java.util.concurrent.atomic.AtomicInteger

class BatchProcessor {
  private static final var LOG = Logger.forCategory("BatchProcessor")
  private static final var DEFAULT_BATCH_SIZE = 100

  // Process large datasets in batches
  static function processPolicies(processor(policy : Policy)) : BatchResult {
    var result = new BatchResult()
    var batchCount = new AtomicInteger(0)

    var query = Query.make(Policy)
      .compare(Policy#Status, Equals, PolicyStatus.TC_INFORCE)

    var iterator = query.select().iterator()
    var batch = new ArrayList<Policy>()

    while (iterator.hasNext()) {
      batch.add(iterator.next())

      if (batch.size() >= DEFAULT_BATCH_SIZE) {
        processBatch(batch, processor, result)
        batch.clear()
        batchCount.incrementAndGet()
        LOG.info("Processed batch ${batchCount.get()}")
      }
    }

    // Process remaining
    if (!batch.Empty) {
      processBatch(batch, processor, result)
    }

    LOG.info("Batch processing complete: ${result.Processed} processed, ${result.Failed} failed")
    return result
  }

  private static function processBatch(
    batch : List<Policy>,
    processor(policy : Policy),
    result : BatchResult
  ) {
    Transaction.runWithNewBundle(\bundle -> {
      batch.each(\policy -> {
        try {
          var p = bundle.add(policy)
          processor(p)
          result.incrementProcessed()
        } catch (e : Exception) {
          LOG.error("Failed to process policy ${policy.PolicyNumber}", e)
          result.addError(policy.PolicyNumber, e.Message)
          result.incrementFailed()
        }
      })
    })
  }

  // Parallel batch processing
  static function processParallel<T>(
    items : List<T>,
    processor(item : T),
    threadCount : int = 4
  ) : BatchResult {
    var result = new BatchResult()
    var executor = java.util.concurrent.Executors.newFixedThreadPool(threadCount)

    try {
      var futures = items.partition(DEFAULT_BATCH_SIZE).map(\batch -> {
        executor.submit(\-> {
          Transaction.runWithNewBundle(\bundle -> {
            batch.each(\item -> {
              try {
                processor(item)
                result.incrementProcessed()
              } catch (e : Exception) {
                LOG.error("Processing failed", e)
                result.incrementFailed()
              }
            })
          })
        })
      })

      // Wait for completion
      futures.each(\f -> f.get())
    } finally {
      executor.shutdown()
    }

    return result
  }
}

class BatchResult {
  private var _processed : AtomicInteger = new AtomicInteger(0)
  private var _failed : AtomicInteger = new AtomicInteger(0)
  private var _errors = new java.util.concurrent.ConcurrentHashMap<String, String>()

  property get Processed() : int { return _processed.get() }
  property get Failed() : int { return _failed.get() }
  property get Errors() : Map<String, String> { return _errors }

  function incrementProcessed() { _processed.incrementAndGet() }
  function incrementFailed() { _failed.incrementAndGet() }
  function addError(key : String, message : String) { _errors.put(key, message) }
}
```

### Step 3: Data Migration

```typescript
// API-based data migration
interface MigrationConfig {
  sourceSystem: string;
  targetEnvironment: string;
  batchSize: number;
  dryRun: boolean;
}

interface MigrationResult {
  totalRecords: number;
  successCount: number;
  errorCount: number;
  errors: Array<{ id: string; error: string }>;
  duration: number;
}

class DataMigration {
  private config: MigrationConfig;
  private guidewireClient: GuidewireClient;

  constructor(config: MigrationConfig) {
    this.config = config;
    this.guidewireClient = new GuidewireClient(config.targetEnvironment);
  }

  async migrateAccounts(sourceAccounts: SourceAccount[]): Promise<MigrationResult> {
    const startTime = Date.now();
    const result: MigrationResult = {
      totalRecords: sourceAccounts.length,
      successCount: 0,
      errorCount: 0,
      errors: [],
      duration: 0
    };

    console.log(`Starting migration of ${sourceAccounts.length} accounts`);

    // Process in batches
    for (let i = 0; i < sourceAccounts.length; i += this.config.batchSize) {
      const batch = sourceAccounts.slice(i, i + this.config.batchSize);
      console.log(`Processing batch ${Math.floor(i / this.config.batchSize) + 1}`);

      await Promise.all(batch.map(async (sourceAccount) => {
        try {
          const gwAccount = this.transformAccount(sourceAccount);

          if (!this.config.dryRun) {
            await this.guidewireClient.createAccount(gwAccount);
          }

          result.successCount++;
        } catch (error) {
          result.errorCount++;
          result.errors.push({
            id: sourceAccount.id,
            error: error instanceof Error ? error.message : 'Unknown error'
          });
        }
      }));

      // Rate limiting pause between batches
      await sleep(1000);
    }

    result.duration = Date.now() - startTime;
    console.log(`Migration complete: ${result.successCount} succeeded, ${result.errorCount} failed`);

    return result;
  }

  private transformAccount(source: SourceAccount): GuidewireAccount {
    return {
      accountHolder: {
        contactSubtype: source.isCompany ? 'Company' : 'Person',
        firstName: source.firstName,
        lastName: source.lastName,
        companyName: source.companyName,
        primaryAddress: {
          addressLine1: source.address.line1,
          addressLine2: source.address.line2,
          city: source.address.city,
          state: { code: this.mapStateCode(source.address.state) },
          postalCode: source.address.zip,
          country: { code: 'US' }
        },
        emailAddress1: source.email,
        homePhone: source.phone
      },
      producerCodes: [{ id: this.mapProducerCode(source.agentCode) }]
    };
  }

  private mapStateCode(sourceState: string): string {
    // Map source system state codes to Guidewire codes
    const stateMap: Record<string, string> = {
      'California': 'CA',
      'CA': 'CA',
      // Add more mappings
    };
    return stateMap[sourceState] || sourceState;
  }
}
```

### Step 4: Data Validation

```gosu
// Data validation framework
package gw.data.validation

uses gw.api.util.Logger

class DataValidator {
  private static final var LOG = Logger.forCategory("DataValidator")

  // Validate account data
  static function validateAccount(account : Account) : ValidationResult {
    var result = new ValidationResult()

    // Required fields
    if (account.AccountHolderContact == null) {
      result.addError("AccountHolderContact", "Account holder contact is required")
    }

    if (account.AccountNumber == null || account.AccountNumber.Empty) {
      result.addError("AccountNumber", "Account number is required")
    }

    // Contact validation
    if (account.AccountHolderContact != null) {
      var contact = account.AccountHolderContact
      if (contact typeis Person) {
        if (contact.FirstName == null || contact.FirstName.Empty) {
          result.addError("FirstName", "First name is required for person")
        }
        if (contact.LastName == null || contact.LastName.Empty) {
          result.addError("LastName", "Last name is required for person")
        }
      } else if (contact typeis Company) {
        if (contact.Name == null || contact.Name.Empty) {
          result.addError("CompanyName", "Company name is required")
        }
      }

      // Address validation
      if (contact.PrimaryAddress != null) {
        validateAddress(contact.PrimaryAddress, result)
      } else {
        result.addError("PrimaryAddress", "Primary address is required")
      }
    }

    return result
  }

  private static function validateAddress(address : Address, result : ValidationResult) {
    if (address.AddressLine1 == null || address.AddressLine1.Empty) {
      result.addError("AddressLine1", "Address line 1 is required")
    }
    if (address.City == null || address.City.Empty) {
      result.addError("City", "City is required")
    }
    if (address.State == null) {
      result.addError("State", "State is required")
    }
    if (address.PostalCode == null || address.PostalCode.Empty) {
      result.addError("PostalCode", "Postal code is required")
    }

    // Postal code format validation
    if (address.PostalCode != null && !address.PostalCode.matches("^\\d{5}(-\\d{4})?$")) {
      result.addError("PostalCode", "Invalid postal code format")
    }
  }

  // Validate policy data
  static function validatePolicy(policy : Policy) : ValidationResult {
    var result = new ValidationResult()

    if (policy.Account == null) {
      result.addError("Account", "Policy must be associated with an account")
    }

    if (policy.EffectiveDate == null) {
      result.addError("EffectiveDate", "Effective date is required")
    }

    if (policy.ExpirationDate == null) {
      result.addError("ExpirationDate", "Expiration date is required")
    }

    if (policy.EffectiveDate != null && policy.ExpirationDate != null) {
      if (policy.ExpirationDate.before(policy.EffectiveDate)) {
        result.addError("ExpirationDate", "Expiration date must be after effective date")
      }
    }

    return result
  }
}

class ValidationResult {
  private var _errors = new ArrayList<ValidationError>()

  property get HasErrors() : boolean { return !_errors.Empty }
  property get Errors() : List<ValidationError> { return _errors }

  function addError(field : String, message : String) {
    _errors.add(new ValidationError(field, message))
  }

  function throwIfInvalid() {
    if (HasErrors) {
      throw new ValidationException(
        "Validation failed: " + _errors.map(\e -> e.toString()).join(", ")
      )
    }
  }
}
```

### Step 5: Data Export

```gosu
// Data export utilities
package gw.data.export

uses gw.api.database.Query
uses java.io.FileWriter
uses java.io.BufferedWriter

class DataExporter {

  // Export to CSV
  static function exportAccountsToCSV(filename : String, filter : AccountFilter = null) {
    var writer = new BufferedWriter(new FileWriter(filename))

    try {
      // Write header
      writer.write("AccountNumber,FirstName,LastName,Email,Phone,Address,City,State,Zip\\n")

      // Query accounts
      var query = Query.make(Account)
      if (filter != null) {
        if (filter.Status != null) {
          query.compare(Account#AccountStatus, Equals, filter.Status)
        }
        if (filter.CreatedAfter != null) {
          query.compare(Account#CreateTime, GreaterThan, filter.CreatedAfter)
        }
      }

      // Stream results to file
      query.select().each(\account -> {
        var contact = account.AccountHolderContact
        var address = contact.PrimaryAddress

        writer.write(escapeCSV(account.AccountNumber) + ",")
        writer.write(escapeCSV(contact typeis Person ? contact.FirstName : "") + ",")
        writer.write(escapeCSV(contact typeis Person ? contact.LastName : contact.Name) + ",")
        writer.write(escapeCSV(contact.EmailAddress1 ?: "") + ",")
        writer.write(escapeCSV(contact.HomePhone ?: "") + ",")
        writer.write(escapeCSV(address?.AddressLine1 ?: "") + ",")
        writer.write(escapeCSV(address?.City ?: "") + ",")
        writer.write(escapeCSV(address?.State?.Code ?: "") + ",")
        writer.write(escapeCSV(address?.PostalCode ?: "") + "\\n")
      })
    } finally {
      writer.close()
    }
  }

  // Export to JSON
  static function exportAccountsToJSON(filename : String, limit : int = 1000) : int {
    var accounts = Query.make(Account)
      .compare(Account#AccountStatus, Equals, AccountStatus.TC_ACTIVE)
      .select()
      .take(limit)
      .toList()

    var json = accounts.map(\a -> accountToMap(a))
    var jsonString = gw.api.json.JsonObject.toJson(json)

    var writer = new FileWriter(filename)
    writer.write(jsonString)
    writer.close()

    return accounts.Count
  }

  private static function accountToMap(account : Account) : Map<String, Object> {
    var contact = account.AccountHolderContact
    return {
      "accountNumber" -> account.AccountNumber,
      "status" -> account.AccountStatus.Code,
      "contact" -> {
        "name" -> contact.DisplayName,
        "email" -> contact.EmailAddress1,
        "phone" -> contact.HomePhone
      },
      "createdDate" -> account.CreateTime.toString()
    }
  }

  private static function escapeCSV(value : String) : String {
    if (value.contains(",") || value.contains("\"") || value.contains("\\n")) {
      return "\"" + value.replace("\"", "\"\"") + "\""
    }
    return value
  }
}
```

### Step 6: Data Governance

```typescript
// Data governance and PII handling
interface PIIField {
  fieldPath: string;
  classification: 'PII' | 'PHI' | 'PCI' | 'SENSITIVE';
  maskingRule: 'full' | 'partial' | 'hash';
}

const piiFields: PIIField[] = [
  { fieldPath: 'contact.ssn', classification: 'PII', maskingRule: 'partial' },
  { fieldPath: 'contact.dateOfBirth', classification: 'PII', maskingRule: 'partial' },
  { fieldPath: 'contact.emailAddress1', classification: 'PII', maskingRule: 'partial' },
  { fieldPath: 'bankAccount.accountNumber', classification: 'PCI', maskingRule: 'partial' },
  { fieldPath: 'bankAccount.routingNumber', classification: 'PCI', maskingRule: 'full' }
];

class PIIMasker {
  mask(data: any, fields: PIIField[]): any {
    const masked = JSON.parse(JSON.stringify(data));

    fields.forEach(field => {
      const value = this.getNestedValue(masked, field.fieldPath);
      if (value) {
        const maskedValue = this.applyMaskingRule(value, field.maskingRule);
        this.setNestedValue(masked, field.fieldPath, maskedValue);
      }
    });

    return masked;
  }

  private applyMaskingRule(value: string, rule: string): string {
    switch (rule) {
      case 'full':
        return '*'.repeat(value.length);
      case 'partial':
        if (value.length <= 4) return '****';
        return '*'.repeat(value.length - 4) + value.slice(-4);
      case 'hash':
        return this.hashValue(value);
      default:
        return '****';
    }
  }

  private hashValue(value: string): string {
    // SHA-256 hash for one-way masking
    const crypto = require('crypto');
    return crypto.createHash('sha256').update(value).digest('hex').substring(0, 16);
  }
}

// Data retention policy
class DataRetentionPolicy {
  private retentionRules: Map<string, number> = new Map([
    ['claim', 7 * 365],        // 7 years
    ['policy', 10 * 365],      // 10 years
    ['auditLog', 90],          // 90 days
    ['sessionData', 1],        // 1 day
  ]);

  async enforceRetention(): Promise<RetentionResult> {
    const result: RetentionResult = { deleted: {}, errors: [] };

    for (const [entityType, retentionDays] of this.retentionRules) {
      try {
        const cutoffDate = new Date();
        cutoffDate.setDate(cutoffDate.getDate() - retentionDays);

        const deletedCount = await this.deleteOldRecords(entityType, cutoffDate);
        result.deleted[entityType] = deletedCount;
      } catch (error) {
        result.errors.push({ entityType, error: error.message });
      }
    }

    return result;
  }
}
```

## Data Handling Best Practices

| Practice | Description |
|----------|-------------|
| Use Bundles | Always use Transaction.runWithNewBundle for writes |
| Batch Processing | Process large datasets in batches of 100-500 |
| Lazy Loading | Use select() and iterate, don't toList() large results |
| Index Awareness | Query on indexed fields for performance |
| Validation First | Validate data before database operations |
| Audit Trail | Log all data modifications |
| PII Protection | Mask or encrypt sensitive data |

## Output

- Entity CRUD operations
- Batch processing framework
- Data migration utilities
- Validation framework
- Export capabilities
- Data governance tools

## Resources

- [Guidewire Data Model](https://docs.guidewire.com/cloud/)
- [Query API Documentation](https://docs.guidewire.com/cloud/pc/202503/apiref/)

## Next Steps

For role-based access control, see `guidewire-enterprise-rbac`.

Overview

This skill provides concise, practical best practices for data handling in Guidewire InsuranceSuite, covering entity management, CRUD patterns, batch processing, data migration, validation, and governance. It focuses on safe, auditable operations for PolicyCenter, ClaimCenter, and BillingCenter data models. Use it to standardize data workflows, reduce migration risk, and improve operational reliability.

How this skill works

The skill inspects common Guidewire patterns and prescribes concrete Gosu and API approaches for creating, reading, updating, and deactivating entities inside transaction bundles. It documents batch and parallel processing patterns with error aggregation and retry strategies. It also describes API-based migration flow with transformation, batching, rate limiting, and dry-run support, plus data validation checks and governance controls.

When to use it

  • When implementing entity CRUD operations across PolicyCenter, ClaimCenter, or BillingCenter.
  • During bulk updates, nightly jobs, or ETL tasks that require batch and parallel processing.
  • When planning or executing data migration between source systems and Guidewire environments.
  • To add automated data validation before persist operations or migration target writes.
  • When defining data governance controls, auditability, and soft-delete patterns for compliance.

Best practices

  • Always run entity mutations inside Transaction.runWithNewBundle to isolate changes and control rollbacks.
  • Use limited-size batches (default 50–200) and pause between batches for rate limiting and stability.
  • Aggregate errors with a concurrent-safe structure and surface summaries for rapid remediation; avoid failing entire jobs for single record errors.
  • Prefer soft deletes (status flags) over hard deletes to preserve audit trails and enable data recovery.
  • Implement dry-run and logging for migrations and add incremental checkpoints to resume interrupted runs.

Example use cases

  • Create accounts with linked contacts and addresses in a single transaction and log the generated account number.
  • Run periodic batch jobs to update active policies, using processBatch to control bundle scope and error handling.
  • Migrate accounts from a legacy CRM into Guidewire using transformAccount, state mapping, and configurable batchSize and dryRun.
  • Parallelize large processing tasks with a fixed thread pool while ensuring each thread operates within its own transaction bundle.
  • Validate incoming account records for required contact and address fields before persisting or sending to downstream systems.

FAQ

How do I avoid transactional contention during large batch jobs?

Use smaller batch sizes, limit concurrent threads, and keep bundles short-lived. Partition work by natural keys to reduce lock contention.

Should I use parallel processing for migrations?

Use parallelism selectively. It speeds throughput but increases complexity for transactions and retries; ensure each parallel worker uses isolated bundles and concurrency-safe error tracking.

How do I handle differing state codes between systems?

Maintain a central mapping function (mapStateCode) and enrich it with fallbacks. Log unmapped values and surface them for cleanup before final runs.