# Assessing the Reliability of Computer-Processed Data Course (Self-Paced)

Canonical URL: <https://www.graduateschool.edu/courses/assessing-the-reliability-of-computer-processed-data-course-self-paced>

## Overview

Develop the necessary skills to evaluate the reliability of computer-processed data regardless of the environment in which it is generated and/or processed. Learn some of the more common techniques used by auditors to assess system controls, reliability, and the processes employed to accomplish the assessments. Practice with GAO planning and documentation worksheets used in real assessments.

## What you'll learn

- Define the professional standards, policies, and guidelines governing audit activity related to data processing and data reliability.
- Define and discuss the concept of, and responsibility for, data reliability assessments.
- Discuss the framework for conducting a data reliability assessment and presenting the appropriate disclosure in the audit report.
- Review a structured approach for performing and documenting the data reliability assessment process.

## Curriculum

#### Module 1: Government Audit Standards, Policies, and Guidelines

- Review GAO Government Auditing Standards (Yellow Book) requirements for sufficient, appropriate evidence and overall assessment of evidence.
- Understand when and how to evaluate information systems (general, application, and user) controls that affect data reliability.
- Apply guidance on using the work of others and specialists, and documenting qualifications, scope, and quality.
- Identify required report content (objectives, scope, methodology) and how to disclose limitations and uncertainties.

#### Module 2: Data Reliability Considerations

- Define data reliability (completeness, accuracy, validity, and consistency) and why it matters for audit findings.
- Recognize common forms of computer-processed data (extracts, enterprise systems, spreadsheets, surveys) and typical reliability issues.
- Use CAATs (e.g., ACL, IDEA) and three audit methodologies — auditing with, through, and around the computer — to evaluate data.
- Understand common problems (incomplete, untimely, incorrect, or incompatible data) and their causes.

#### Module 3: Overall Framework for Assessments

- Decide whether a data reliability assessment is needed based on planned use and risk.
- Scope the extent of assessment using expected importance, corroborating evidence, and risk of using the data.
- Focus effort on portions of data relevant to audit objectives; consider leveraging information/system control reviews when efficient.
- Follow the framework stages: determine need and plan, conduct work, make the determination, and include appropriate report language.

#### Module 4: Planning and Performing the Assessment

- Initiate reliability work early; determine timing, level of detail (record- vs. summary-level), and documentation needs.
- Collect existing information: interview knowledgeable officials; obtain data dictionaries, system docs, and prior reviews.
- Test data (counts, missing values, duplicates, ranges, identifiers, dates, relationships) and, when needed, trace to/from source documents.
- Document plans, procedures, results, and conclusions clearly, using provided planning and summary worksheets.

#### Module 5: Documenting and Reporting Assessment Results

- Synthesize testing and control information into an overall reliability determination tied to audit objectives.
- Disclose limitations/uncertainties, describe data sources and methods, and explain population, period, and sampling as applicable.
- Tailor report wording so users can reasonably interpret findings without being misled; describe any constraints on scope or access.
- Determine whether data are sufficiently reliable, not sufficiently reliable, or of undetermined reliability, and understand the course of action for each outcome.

#### Module 6: Structured Approach for Assessing Reliability of Data

- Apply a structured five-phase approach — from determining audit procedures and obtaining data through extraction, verification, and reliability testing — aligned with GAO’s ADR guidance.
- Leverage existing information, involve stakeholders, and perform only the work necessary to conclude “use or not.”
- Use standardized tools (planning templates, documentation requests, and example data tests) to streamline assessments.

#### Module 7: Case Study

- Apply skills to a federal personnel/payroll case study: develop data reliability assessment steps (Part I) and draft appropriate audit report language (Part II).
- Practice documenting decisions, communicating limitations, and drafting appropriate report language.
- Evaluate three reporting scenarios with varying data reliability outcomes and draft methodology language for each.

## Pricing

**Tuition:** $1049