AICPA Power Query Course for Accountants | 4 CPE
-
-
-
-
-
-
AICPA Power Query Course for Accountants and Finance Professionals
Introduction to Data Analytics with Power Query (Get and Transform) is an AICPA & CIMA online course for finance professionals who want to clean, combine and prepare data faster in Excel. It is especially useful if your monthly work still includes copy-paste reporting, manual data cleanup, repeated GL exports or messy spreadsheet consolidation.
Key takeaways for quick decision-making
- This course is best for accountants, auditors, FP&A analysts and finance managers who use Excel and want faster data preparation workflows.
- AICPA lists the official title as Introduction to Data Analytics with Power Query (Get and Transform), with product number BLI509919.
- The official course page lists 4 CPE credits, online format, Information Technology field of study, advanced level and 1-year availability.
- Power Query is useful for repeatable finance tasks such as importing data, transforming columns, combining files, loading to Excel or the Data Model, and refreshing queries.
- The official AICPA page does not state a digital badge for this SKU, so learners wanting a badge may also consider the Data Analytics Core Concepts Certificate.
What is Power Query in Excel for accountants?
Power Query, also called Get & Transform in Excel, helps users connect to external data, shape it, combine it and load it into Excel for reporting. Microsoft describes the four main phases as Connect, Transform, Combine and Load, which matches how accountants usually prepare data before analysis.
Microsoft also explains that Power Query records transformation steps and runs them automatically when a query is refreshed. That makes it useful for recurring finance work where the source file changes each month but the cleanup steps stay mostly the same.
| Power Query step | What it means in finance work | Simple example |
|---|---|---|
| Connect | Bring data into Excel from files, databases, web sources or other supported sources. | Connect to monthly sales files saved in a folder. |
| Transform | Clean and reshape data without changing the original source. | Remove blank rows, fix date formats and split account codes. |
| Combine | Append or merge multiple tables into a cleaner analysis view. | Combine twelve monthly GL exports into one table. |
| Load | Send prepared data to a worksheet or the Excel Data Model. | Load cleaned data into a management report model. |
External source: Microsoft guide to Power Query in Excel.
AICPA Introduction to Data Analytics with Power Query official course facts
The official AICPA & CIMA listing describes this course as an online advanced-level Information Technology course with 4 CPE credits. The page states that Power Query is used for extracting, transforming and preparing data for analysis.
| Course detail | Official information |
|---|---|
| Official title | Introduction to Data Analytics with Power Query (Get and Transform) |
| Product number / SKU | BLI509919 |
| Format | Online |
| CPE credits | 4 |
| NASBA field of study | Information Technology |
| Level | Advanced |
| Availability | 1 year |
| Author | Donald Tomoff |
| Who benefits | Any business professional responsible for managing and working with data |
| Digital badge | Not stated on the official product page for this SKU |
| Official source | AICPA & CIMA course page |
Last verified: May 13, 2026. Product facts, access terms and pricing can change, so check the official AICPA & CIMA page before publishing time-sensitive details.
Who should take the AICPA Power Query course for accountants?
This course fits professionals who already work with Excel data and want to reduce repetitive preparation work. It is not a beginner Excel course. It is better for users who understand tables, reports and finance data, and now want to make their preparation steps more repeatable.
| Learner profile | Why Power Query helps | Typical task improved |
|---|---|---|
| Accountant or senior accountant | Month-end files often need the same cleanup every period. | Standardising trial balance, GL and expense exports. |
| Auditor | Client data usually arrives in different formats and needs cleaning before testing. | Preparing transaction files for sampling or exception review. |
| FP&A analyst | Forecasts and management reports often pull from several files. | Combining actuals, budgets and revised forecasts. |
| Controller | Reporting packs become easier when recurring transformations are saved. | Refreshing monthly dashboards from updated source data. |
| Finance manager | Power Query helps check and reshape data before analysis. | Preparing sales, margin and working capital data for review. |
What will you learn in Introduction to Data Analytics with Power Query?
You will learn how to import data into Excel, transform it, choose between loading to a worksheet or the Data Model, and add fields that make analysis more flexible. The course is practical because it focuses on data preparation, which is usually the first step before reporting or analytics.
Official major topics
- Power Query, also known in Excel 2016 as Get and Transform.
- Extracting and transforming data as the first step to data analysis and reporting.
- Top features most important to accountants, including data source flexibility, appending queries and unpivoting.
- Real Power Query use cases that accountants can apply in work.
- Excel workbooks for participant practice, as stated on the AICPA listing.
Official learning objectives
- Import and transform basic data into Excel using Power Query.
- Understand and apply the data load capabilities of loading into Excel versus loading into the Data Model, and why it matters.
- Transform data and add extra fields to the data set to improve flexibility for analysis.
Power Query use cases for accounting, audit and FP&A teams
Power Query is valuable when the same messy data problem repeats every week or month. The tool records the preparation steps, so a finance professional can refresh the query when the next file arrives instead of rebuilding the cleanup manually.
| Manual finance problem | Power Query workflow | Why it matters |
|---|---|---|
| Monthly GL exports arrive with extra rows and inconsistent headings. | Remove rows, rename columns, set data types and save the query steps. | The trainee does not need to repeat the same cleanup from memory next month. |
| Sales data is split across twelve monthly files. | Append files into one combined query. | The CFO gets one clean sales table instead of a folder full of separate files. |
| Customer names differ between billing and collection reports. | Merge datasets using a common key where available. | Receivables review becomes easier because data sources can be compared in one place. |
| A trial balance export has columns that need to become rows. | Use unpivoting to reshape the table. | The data becomes suitable for pivot tables, dashboards and analysis. |
| A report must be rebuilt every month from the newest source file. | Refresh the query after replacing or updating the source file. | Reporting becomes less dependent on manual copy-paste steps. |
A small month-end example
A finance trainee receives a 60,000-line expense export every month. In April, she manually deletes unused columns, filters blank rows, fixes department names and adds a cost centre category. In May, Power Query can repeat those recorded steps after she refreshes the query. The work still needs review, but the boring part becomes much less fragile.
Where does Power Query fit in the AICPA data analytics learning pathway?
Power Query is the practical Excel tool layer of the data analytics journey. The AICPA data analytics certificate page lists certificates for accounting and finance professionals that cover foundational concepts, data processing techniques, visualization skills and communication of insights.
| Learning need | Recommended Eduyush page | How it connects |
|---|---|---|
| I need the foundation first | Data Analytics Core Concepts | Start here if you want the language and mindset of analytics. |
| I want to prepare and analyze data more deeply | Data Processing and Analysis | Move here for broader data preparation and analysis concepts. |
| I want to present insights better | Data Visualization and Communication | Use this when the challenge is charts, storytelling and stakeholder communication. |
| I want hands-on Excel automation | Power Query course | Use this course to apply data preparation ideas inside Excel. |
| I want to compare all data courses | Data analytics collection | Compare AICPA & CIMA data analytics options in one place. |
Official pathway source: AICPA & CIMA Data Analytics Certificates.
Why buy the AICPA Power Query course through Eduyush?
Eduyush supports eligible learners with regional purchase guidance, local payment convenience and activation help for AICPA & CIMA learning products. This is useful when you want to choose between a short Power Query course and a broader AICPA data analytics certificate.
| What you may need | How Eduyush helps |
|---|---|
| Course selection | Guidance on whether this 4 CPE Power Query course is enough or whether a certificate pathway is better. |
| Regional purchase support | Local purchase experience and regional pricing where available on Eduyush. |
| Activation support | Post-purchase help for access and activation queries. |
| Related learning path | Context across AICPA certificate programs, data analytics and finance upskilling pages. |
How to complete the AICPA Power Query course
Since this is a focused 4 CPE course, most learners should treat it as a practical Excel skill sprint. Keep one messy finance file ready while studying so the concepts connect to your actual work.
- Purchase the course through Eduyush.
- Complete activation and access the online course.
- Work through the Power Query examples and practice files where provided.
- Try one real finance use case from your own work, such as cleaning a GL export or combining monthly reports.
- Record the 4 CPE credits according to your professional body or state board requirements.
FAQs on the AICPA Power Query course for accountants
What is the official title of this Power Query course?
The official AICPA & CIMA title is Introduction to Data Analytics with Power Query (Get and Transform). The product number or SKU is BLI509919.
How many CPE credits does the course provide?
The official AICPA & CIMA listing shows 4 CPE credits. The NASBA field of study shown on the course page is Information Technology.
Is the course beginner level?
No. The official AICPA & CIMA listing shows the level as Advanced. It is best for users who are comfortable working with Excel data and want to learn Power Query for cleaner, repeatable data preparation.
Does this Power Query course include a digital badge?
The official AICPA product page for SKU BLI509919 does not state a digital badge. If you need a badge, compare the AICPA data analytics certificate products on Eduyush before purchasing.
Is Power Query useful for accountants?
Yes. Power Query is useful for accountants because many finance tasks involve importing, cleaning, combining and refreshing data. It is especially helpful for monthly reports, GL exports, sales files, budget files and recurring analysis packs.
Is Power Query the same as Get and Transform?
Microsoft describes Power Query as known as Get & Transform in Excel. It helps users connect, transform, combine and load data for reporting and analysis.
Should I take Data Analytics Core Concepts before this course?
It depends on your confidence. If you understand the basics of analytics and want hands-on Excel automation, this Power Query course can be a good fit. If you are new to analytics language and project framing, start with Data Analytics Core Concepts first.
Official sources and related Eduyush pages
- Official AICPA Power Query course page
- Microsoft Power Query guide
- Official AICPA data analytics certificates page
- Eduyush data analytics collection
- Data Analytics Core Concepts Certificate
- Data Processing and Analysis Certificate
- Data Visualization and Communication Certificate
- AICPA certificate programs on Eduyush
