AICPA Data Processing & Analysis Certificate | 14 CPE Credits

AICPA Data Processing and Analysis Certificate — Turn Raw Data into Decisions That Drive Financial Performance

80% of a data professional’s time is spent preparing data — not analyzing it. This certificate teaches you how to do it right.

Data scientists spend 60% of their time cleaning and organizing data and another 19% collecting it — yet 76% say data preparation is the least enjoyable part of their work. For accountants and finance professionals stepping into analytics, this is where most projects succeed or fail — long before any chart is built or insight is shared.

The AICPA Data Processing and Analysis Certificate is a 14-CPE-credit, four-part program that takes you from requirements gathering through data profiling, cleansing, mining, and modeling. It’s the hands-on, practical follow-up to the Data Analytics Core Concepts Certificate — designed to give you the skills to actually work with data, not just understand it conceptually.

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The $12.9 Million Problem This Course Solves

• Gartner estimates that organizations lose an average of $12.9 million per year due to poor data quality.
• In finance and insurance specifically, bad data costs $5,991 per employee annually — 2x the cross-industry baseline.
• More than a quarter of organizations estimate annual losses exceeding $5 million due to poor data quality, according to Forrester, while 43% of COOs cite data quality as their top data priority (IBM IBV 2025).
• Companies with clean data achieve a 6:1 lifetime value-to-CAC ratio, compared to 3:1 for those with data quality issues — and experience month-end closing cycles that are up to 35% faster.

As an accountant or finance professional, you’re often the last line of defense before data becomes a financial statement, a forecast, or a board presentation. If the underlying data is flawed, everything built on top of it collapses. This certificate gives you the structured framework to ensure that doesn’t happen.

What You’ll Master — The Four-Part Curriculum

This certificate is structured as four progressive courses that mirror the real-world data analytics workflow:

1. Requirements Gathering

Discover a structured framework for understanding stakeholder needs and defining the right data objectives. You’ll learn to scope a data analytics project, identify what questions the data needs to answer, and align your approach with business goals — before touching a single dataset.

2. Data Profiling and Collection

Enhance your understanding of data sources and learn to identify, assess, and collect the right data. This module covers evaluating data quality at the source level, understanding data structures, and ensuring the datasets you gather align with your project’s objectives.

3. Data Cleansing

Learn the techniques and processes to ensure data integrity and quality. You’ll tackle inconsistencies, duplicates, missing values, and formatting errors — the issues that cause 23% increases in operational costs when left unresolved. This is where you ensure every row and column is reliable before it feeds into analysis or reporting.

4. Data Mining and Modeling

Discover hidden relationships and opportunities to improve financial performance. You’ll learn how to analyze historical data (what happened) and build models to forecast future outcomes (what may happen) — the skill that transforms an accountant from a reporter of the past into an advisor for the future.

Learning Outcomes 

1. Recall the definition and purpose of requirements gathering, data profiling and collection, data cleansing, and data mining and modeling
2. Recognize how each stage fits into a complete data analytics project lifecycle
3. Recall the steps to follow when gathering requirements and profiling, collecting, cleansing, mining, and modeling data
4. Apply techniques learned to common data processing and analysis scenarios in finance and accounting
5. Identify risks and considerations associated with each stage of data processing

Who Should Enroll

• Chartered Accountants (CAs) moving beyond compliance into advisory roles that require hands-on data skills — particularly those in audit, FP&A, or management accounting
• CPAs and CPA candidates preparing for the data analytics components of the CPA Evolution exam model
• Controllers, finance directors, and CFOs who need to validate and trust the data their teams present before making strategic decisions
• ACCA, CMA, and CIMA members who work with large datasets and need to ensure data integrity for reporting and analysis
• Analysts and junior accountants who want to build the practical data preparation skills that senior roles demand
• Any finance professional tired of making decisions on data they don’t fully trust

Where This Course Sits — AICPA Data Analytics Learning Pathway

This certificate is Stage 2 in AICPA’s structured learning pathway. It’s designed to be taken after the foundational course and before the communication/visualization certificate:

Why This Course Has the Most CPE Credits

At 14 CPE credits, this is the largest single certificate in the AICPA Data Analytics pathway — because data preparation is where the real work happens. While the Core Concepts certificate teaches you how to think about data and the Visualization certificate teaches you how to present data, this course teaches you how to actually work with data. It’s the technical backbone of the entire pathway.

 Real-World Applications for Finance Professionals

Earn 14 NASBA-Recognized CPE Credits

14 CPE credits from a single certificate covers more than a third of the annual requirement for most U.S. states. Combined with the full AICPA Data Analytics pathway (37 total CPE credits), you can meet nearly a full year’s CPE obligation while building career-defining skills.

Course Details at a Glance

Your AICPA Digital Badge

• Can be added directly to your LinkedIn profile
• Is downloadable as a PDF certificate
• Contains verifiable metadata — anyone clicking the badge can confirm the issuer, skills earned, and completion date
• Proves your data preparation, cleansing, and modeling expertise — the practical skills employers test for in interviews

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