AICPA Certification : Data Analytics Modeling Certificate
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How It Works β Enrollment to Certification
Step 1: Purchase on EduyushΒ β You'll receive an order confirmation immediately.
Step 2: AICPA Activation (within 3 working days)Β β AICPA sends your login credentials directly to the email used during checkout.β
Step 3: Self-Paced LearningΒ β Access all course modules online. Study at your own pace within the 12-month access window.
Step 4: Pass Module AssessmentsΒ β Each module ends with an MCQ evaluation. Score 70% or above to pass. You can retake assessments unlimited times.β
Step 5: Earn Your Certificate & Digital BadgeΒ β Once all modules are cleared, your certification is granted. You'll receive a badge notification fromΒ admin@credly.comΒ within approximately 15 business days.β
Step 6: Share on LinkedInΒ β Accept your badge on Credly and add it to your LinkedIn profile under Licenses & Certifications.
Your AICPA Digital Badge
What is a digital badge?
A digital badge is a verified, portable credential issued through Credly (formerly Acclaim) that validates you've completed an AICPA & CIMA certificate program. It contains embedded metadata about what you learned and the criteria you met.β
How do I receive it?
Within approximately 15 business days of completing all modules, you'll get an email fromΒ admin@credly.comΒ with a link to accept your badge.β
Where can I display it?
LinkedIn (under Licenses & Certifications), email signatures, personal websites, resumes, and professional portfolios. Credly provides direct share buttons for major platforms.
Is it verifiable?
Yes. Every badge has a unique URL linked to your verified profile on Credly. Anyone can click the badge to confirm it's authentic and see the specific competencies it represents.β
Does it expire?
The badge itself doesn't expire. It's a permanent record of your achievement.
Access, Activation & Course Format
- Format:Β 100% online, self-paced eLearning
- Activation:Β Within 3 working days of purchase, AICPA sends credentials to your registered email
- Access Duration:Β 12 months from activation date
- Assessment Format:Β MCQ evaluations at the end of each module
- Passing Score:Β 70% per module
- Retakes:Β Unlimited β no additional fees
- Prerequisites:Β No prior data analytics experience required (individual product pages note recommended prior certificates where applicable)
- Language:Β English
- Device Compatibility:Β Desktop and laptop recommended for best experience
CPE Credits & NASBA Recognition
What are CPE credits?
Continuing Professional Education (CPE) credits are required by licensing boards (including State Boards of Accountancy) for CPAs and other finance professionals to maintain their credentials. These AICPA certificates count toward your annual CPE requirement.
Is this NASBA-recognized?
Yes. AICPA is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education. These courses meet NASBA QAS standards.
Fields of Study:
Varies per certificate (Information Technology, Communications & Marketing, Personal Development). Shown in each product's Key Course Details section.
Data Analytics Modeling Certificate
Earners of this certificate drive successful analytics practices by defining clear business outcomes to ensure efforts align with organizational strategic direction. Badge earners manipulate and work with structured and unstructured data, profile data, and apply cleansing techniques to maintain data quality throughout the data-life cycle. These candidates apply ETL (extract, transform, load) techniques to data models and use sophisticated tools for managing an ongoing data practice.
Why?
This certificate is Part 3 of theΒ Data Analyst Certificates BundleΒ β a comprehensive five-part program that provides training and practical guidance on the topic of data analytics.
The Data Analytics Modeling Certificate will expand your ability to work with structured and unstructured data to drive a successful analytics practice. To start, you will learn to define clear business outcomes for your analytics practice to ensure your efforts align with your organization's strategic direction and create value. Next, you will learn data profiling and data cleansing techniques to maintain data quality throughout the data life cycle. You'll practice ETL (extract, transform, load) techniques and work with different data models and analytics tools. Finally, you will learn how to institute sophisticated tools for managing an ongoing enterprise data practice, including tools for data warehousing, managing the data life cycle, and working with structured and unstructured data.
Note:Β It is recommended that you complete theΒ Application of Data Analysis Essentials Certificate, or ensure you have equivalent knowledge and skills, before starting this certificate course.
Learning Labs:Β This is an interactive learning program that includes bonus simulated learning labs with step-by-step guidance that will expose you to the tools needed to implement an analytics practice in a practical way and equip you to deploy those tools as needed within your organization. You will practice using various technologies for preparing, analyzing and managing datasets in the real world. *Time spent on learning labs does not award CPE and completing learning labs is not a requirement for earning the certificate
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Who?
Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations make informed, data-driven business decisions.
Other information| CPE Credits |
14 |
|---|---|
| Format: | Course - Online |
| Access: | This is a digital product. You will have access to the content for a year after purchase date. |
Learning Outcomes
- Identify opportunities, processes, and necessary data for solving analytical problems.
- Apply data profiling and data cleansing techniques to available data.
- Use data preparation and enrichment tools.
- Use ETL (extract, transform, load) tools.
- Compare data warehousing techniques.
- Use data warehousing and data management tools.
- Align the outcomes of your data analytics practice with your organization's strategic direction and create value
Key Topics covered
- Defining value and tying analytics to value-driven business cases
- Understanding the characteristics of data and how they can be leveraged to gather insights from information
- Identifying project constructs for data analytics
- Identifying different types of data with which analysts will be expected to interact
- Profiling data for accurate analysis initiatives
- Understanding tool capabilities for working with data
- Cleansing data with appropriate tools to increases analytics accuracy
- Managing data quality and integrity
- Extracting, transforming, and loading data
- Implementing a data warehouse
- Managing the data life cycle
- Creating and using different types of data models
- Tools for working with both structured and unstructured data
