Data Analysis Basic Course (Self-Paced)

This course includes

6 hours of project-based training from experts
Answers from real instructors
Proprietary workbook included
Retake for free within 1 year
Verified digital certificate of completion
Learn at an accredited institution

This course is self-paced. For live online or in-person instruction, take Data Analysis Basic.

Data Analysis Basic is a practical introduction to the core concepts and workflows used to transform raw data into meaningful information that supports analysis and informed decision making. The course covers foundational topics such as data structures and types, data quality, visualization, databases, governance, and reporting tools, along with guidance on communicating insights through data storytelling.

Learners will also explore where data originates, including internal and external sources, how analytical systems differ from transactional systems, and why clear definitions, privacy standards, and compliance requirements are essential when working with real world data. Hands on elements using Excel and example driven case studies reinforce techniques such as sorting, filtering, pivot tables, and common analytics patterns used in audit, operations, and business environments.

Full Tuition

$649
Due before the class starts

This course includes

6 hours of project-based training from experts
Answers from real instructors
Proprietary workbook included
Retake for free within 1 year
Verified digital certificate of completion
Learn at an accredited institution

Learning Experience Highlights

Training from government‑experienced instructors

Receive instruction from subject‑matter experts who bring proven government experience.

Specialized for government & DoD

Courses that are regularly updated based on feedback and industry developments, ensuring versions are mapped to federal competencies.

The instructor was wonderful and so knowledgeable. The course materials were extremely relevant to what my job is. I feel like I can be better because of this class.
— 2025 student

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Real-world solutions

Directly addressing the day-to-day challenges of federal employees.

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100% Online. Start Anytime

24/7 access to our premium course videos and projects.
Industry experts are assigned as your course instructor. Message your instructor with any questions.
Participate in GSUSA online discussion forums — share ideas and receive additional support.
Hands-on quizzes and mini projects to test and reinforce concepts.

Expert Instructors

Our instructors are industry experts and experienced educators, driven to help you succeed.

Bruce Gay

Instructor

Steve Pesklo

Instructor

Joe Mlakar

Instructor

Earn a Certificate of Completion

Upon completion of this course, you’ll receive an official certificate testifying to your mastery of the curriculum. We’ll send you a link where you can download your certificate, share it online with your friends, post it to your professional network on LinkedIn, and view all your earned certificates. Congratulations on your achievement!

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Sample credential for completion of Data Analysis Basic Course (Self-Paced)

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Data Analysis Basic Course (Self-Paced) Curriculum

What You'll Learn at a Glance

Explain why data analytics is valuable and how it supports decision making in business and audit contexts.
Distinguish between structured and unstructured data, and describe common internal and external data sources.
Compare transactional systems and analytical systems, including the purpose of data marts, data warehouses, and ETL processes.
Identify common data quality issues and apply basic normalization concepts to improve consistency when joining datasets.
Describe core data governance concepts, including data definitions and stewardship, and explain why they matter.
Recognize privacy and compliance considerations, including how to handle PII and PHI responsibly.
Use basic data visualization principles to communicate insights clearly and identify trends or outliers.
Apply foundational Excel techniques for analysis, including sorting, filtering, common functions, and pivot tables and charts.

Course Syllabus

Download Syllabus PDF

Module 1: Introduction to Data Analytics

Understand the role of data analytics in modern organizations.
Differentiate between data and information and recognize the importance of context.
Identify how questions and data availability shape analytical approaches.

Module 2: Data Structures & Types

Distinguish between structured and unstructured data.
Understand tables, databases, rows, and columns.
Recognize challenges in analyzing emails, images, PDFs, and other unstructured formats.

Module 3: Internal & External Data Sources

Identify common internal systems (ERP, HR, POS, financial systems).
Explore external data sources including government and partner data.
Evaluate privacy, quality, and legal considerations when using external data.

Module 4: Transactional vs. Analytical Systems

Compare transactional systems with data warehouses and data marts.
Understand ETL (Extract-Transform-Load) concepts.
Recognize how combining systems supports strategic decision-making.

Module 5: Data Quality & Governance

Identify common data mismatches and transformation challenges.
Understand data definitions, stewardship, and governance principles.
Learn how poor governance can lead to operational failures.

Module 6: Data Privacy & Compliance

Differentiate PII and PHI data types.
Review major privacy regulations such as GDPR and CCPA.
Apply best practices for handling sensitive data responsibly.

Module 7: Data Visualization

Understand why visualization enhances learning and insight discovery.
Differentiate between static and dynamic visualizations.
Use visualization techniques to identify trends and outliers.

Module 8: Reporting & Analytics Tools

Survey common tools such as Excel, Access, Tableau, and Power BI.
Understand when to use visualization, statistical, or audit-specific tools.
Recognize strengths and limitations of different analytics platforms.

Module 9: Excel for Data Analysis

Apply sorting, filtering, and common math functions.
Create pivot tables and pivot charts.
Use Excel to answer basic business and audit questions.

Module 10: Analytical Techniques & Case Studies

Perform stratification, duplicate detection, and normalization.
Analyze vendor, employee, and transaction data.
Apply techniques such as Benford’s Law, sampling, and date comparisons.

Module 11: AI & Emerging Trends in Data

Understand the growth of big data and AI-driven analytics.
Compare search engines and AI chat systems.
Apply AI best practices and prompt fundamentals responsibly.

Data Analytics Group Training

Since 1921, Graduate School USA has partnered with over 125 federal agencies and trained more than one million federal employees. Led by instructors with deep, real-world knowledge of federal regulations, policies, and practices, our private group programs are practical, mission-driven, and tailored to your agency’s objectives. We offer expertise across key federal domains—including human resources, financial management, acquisition and contracting, leadership, and more—to deliver training where and how your team needs it.

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Installments
	10% non-refundable deposit
$649.00	Total You Pay