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System and Method for Service Modeling Data Validation Using Multiple Agents

IP.com Disclosure Number: IPCOM000245542D
Publication Date: 2016-Mar-15
Document File: 3 page(s) / 157K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system and method for validating service modeling data by combining statistical techniques and domain knowledge that are suitable for service delivery modeling with largely different and varied data sources.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

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System and Method for Service Modeling Data Validation Using Multiple Agents

Modeling and optimizing a service delivery environment typically involves collecting and validating a large amount of service data. However, data validation is often a challenging and time consuming task due to the existence of variations in data types, data repositories, delivery locations, customer accounts, and service line components. Challenges also come from manual entry errors and a lack of comprehensive set of validation rules.

The prior art typically uses the statistical approaches or validations for outlier detection. However, said approaches have to be well defined and comprehensive in order to be effective. Alternatively, manual check by subject matter experts (SMEs) can effectively leverage the domain knowledge, but are not scalable and lack standardization.

The novel contribution is a system and method for validating service modeling data by combining statistical techniques and domain knowledge that are suitable for service delivery modeling with largely different and varied data sources. The validations are conducted from different perspectives including:


• Validation structure that takes into account the execution steps of the service model

• Automated validation techniques that can be automatically coded and executed
• Manual validation by the SMEs (e.g., delivery team focals, data collection analysts, modelers, etc.); SME knowledge is leveraged to validate and fix issues

Specifically, the present solution is a distributed and structured data validation approach, comprising the steps of:


1. Collecting service modeling data


2. Validating data structure and format at the presentation layer


3. Validating internal data relationship at the data source layer


4. Validating external data relationship at the parameter layer


5. Validating model relationship at the model layer

Figure: Distributed Data Validation Architecture

1


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Layers of Validation Agents (for both Structure and Content Validation):


1. Presentation Layer (Spreadsheet)

A. Common data structure: four template files Invalid data structure is not allowed

    • Grouped all data in four data gathering templates • The templates are organized according to the data sources • The template structure is fixed despite the variability in data sources
B. Data format validation Invalid data entry is not allowed (e.g., date, numeric, etc.)

C. Date cell validation (rule based) Invalid data entry is not allowed
• Service Level Agreement (SLA): target time (B/C), attainment percentage, business hours

D. Benefit: Embedded validation provides immediate feedback t...