CPE Catalog & Events

Structure of the ASC codification Content included and not included in the ASC Other information contained in the codification Best practices for performing effective and efficient accounting research

Preliminary analytical procedures as risk assessment procedures Performing final analytical procedures to assess the conclusions reached during the audit and evaluate the overall financial statement presentation. When to use substantive analytical procedures for efficiency and effectiveness Establishing expectations for substantive analytic procedures Setting a threshold for differences Following up on differences from expectations Concluding on substantive analytical procedures

Inventory observation procedures When attendance at the inventory observation is impractical Inventory under the control of a third party Consideration of the risk of fraud in inventory counts Sampling related to inventory observations Considerations related to retail inventories, multiple locations Considerations for inventory observations

Compare and contrast the basis and requirements of preparation, compilation, and review engagements Identifying key reporting elements of compilation and review reports Impact of special purpose accounting frameworks and other special issues

Relevant sections of SSARS No. 21, Clarification and Recodification Updates to SSARS No. 21 guidance due to issuance of SSARS Nos. 22-25 Review of AR-C Section 60 requirements for all SSARS engagements Detailed guidance on performing compilation engagements under AR-C Section 80

Relevant sections of SSARS No. 21, Clarification and Recodification Updates to SSARS No. 21 guidance due to issuance of SSARS Nos. 22-25 Review of AR-C Section 60 requirements for all SSARS engagements Detailed guidance on performing preparation engagements under AR-C Section 70

Differences between planning and budgeting Building change into the planning process The business model Strategic plan Marketing plan Financial forecasting Financial risk analysis Five-year operating plan

Demonstration in Power BI Desktop of the following data tools: Power Query, Power Pivot, and Power View Skills demonstrated: DAX, data visualizations including AI visuals, and data storytelling Demonstration of DAX function types: Aggregation, Iterator, CALCULATE, CALCULATE Modifiers, Time Intelligence, Ranking, and Percentages Demonstration of how to curate a visual in PBI Desktop with a variety of formatting tools; visuals for exploratory analysis; and AI visuals for exploratory analysis

Demonstration of publishing from the desktop to the service Demonstration of workspaces – who has access, and what can they do? Demonstration of pinning tiles to a dashboard: quick insights, questions and answers, and what you can pin Demonstration of sharing content: analyze in Excel, apps, and dataflows Demonstration of administrative settings in the service: security, data access, and data quality

Create a new column from existing columns Adding columns is determined by the data type of the column Adding new columns Hands-on examples: column from examples, merging columns, duplicate columns, custom columns, conditional column, index column

What is an append query? What are the data requirements for an append query? Hands-on examples: combining worksheets in the same workbook, listing all objects in a workbook, combining files in a folder

Functions and parameters Demonstration of invoking a function Basics of data modeling Power Query is everywhere Power BI preview features Hands-on examples: creating a data model from a flat file; transferring an Excel data model to Power BI desktop; preview feature: using text by examples in Power BI desktop

Workflow of a data transformation, including data cleaning, data enrichment, and data shaping How to perform data transformations Hands-on example: flattening a general ledger

What is the Power Query Editor? How can I launch the Power Query Editor? Review of the components of the Power Query Editor Preview pane Ribbon Queries pane Query settings pane Applied steps Formula bar

Learning formulas in Power Query Introduction to the “M” language Types of structured values in Power Query Other types of values in Power Query Types of errors in Power Query Custom columns Hands-on examples

What is Power Query? Why should I learn Power Query? What are the benefits of using Power Query? Power Query is not just for Excel Power Query versions are not the same What version of Power Query do I have? How to get Power Query Making your first connection in Power Query Hands-on examples: connection query, editing a query, duplicating a query

Workflow of making a connection Get data Navigator dialog box Query options Global and current workbook Data load options Queries and connections Data source settings Hands-on examples: importing files and databases

What is a merge query? What are the data requirements for a merge query? What are the types of joins for a merge query? Hands-on examples: creating merge queries, creating a full anti-join using an append query, grouping queries

Workflow of the data transformation for a general ledger with sub-accounts Loading a query Loading options for a query Changing the load destination of a query Hands-on examples: flattening a general ledger with sub-accounts; making a connection to the data source; reviewing and documenting the steps created by Power Query

Removing unwanted characters from a data set All data appears in one column Two categories appear in one column Extracting useful information from inconsistent data (Text Analytics) Have a sub-header that is in a row and should be in a column Hands-on examples