CPE Catalog & Events

Leadership Development.

Leadership Development.

Topic 606, Revenue from Contracts with Customers, including recently issued ASUs impacting Topic 606 The FASB’s new five-step revenue recognition model, including hands-on examples and illustrations of the new guidance, including presentation and disclosure requirements Performing an effective risk assessment related to revenue Common internal controls and substantive audit procedures related to revenue

Why forecasts and budgets are frequently wrong: behavioral finance; improper goal setting, games, continuing the status quo, traditional budgeting techniques Incorporating strategy into budgets: improving measurement systems; common errors, developing strategies and appropriate measurements Expanding the budgeting framework: rolling forecasts; mission-based budgeting, zero-based budgeting, post-completion evaluations, contingency planning, black swan events, identifying improvements Big data: definition, challenges, goals, current uses/examples, sources of information Analytical tools: ration analysis, benchmarking, Pareto analysis, trend analysis, regression, simulation, dashboards

Recent trends: M&A activity; contributing factors/reasons for current levels; examples of recent transactions; IPOs (Initial Public Offering) and SPACs (Special-Purpose Acquisition Company); strategic spin-offs/splits; internal venture capital activities; incubators Expanded role of financial professionals: establishing strategy; valuation techniques; execution plan; due diligence; sources of industry information; goodwill; post-completion evaluations Negotiations: Improving your communication skills; establishing an environment for success; list of dos and don’ts Alliances and outsourcing: steps to forming an alliance; examples of recent alliances; determining if outsourcing (short and long-term) is correct for your organization; steps to improve results

Key to understanding array formulas is Implicit Intersection How to enter and evaluate an array formula Examples- array and DAX formulas Array formulas- Implicit Intersection Understanding DAX formulas Calculated columns and measures Evaluation context Context transition Implicit vs explicit measures Examples- DAX formulas Creating a calculated column in Power Pivot

Understanding difference between supervised and unsupervised learning Formulas in Excel (Correl and Trend and Forecast) Linear regression What is artificial intelligence? Examples- artificial intelligence Forecast function Trend function Regression in Excel with the data analysis ToolPak Creating a prediction model

Where can you create a calculated column? Understanding evaluation context- row and filter context When does evaluation of the formula occur (before, as, or after the data is loaded?) Understanding storage requirements of calculated columns Understanding the analytical data model of the Star Schema Dimensions Facts Exercises- calculated columns Adding a calculated column in a table in Excel Creating a dimension table in Power Query Creating a hierarchy in Excel with calculated columns Adding a calculated column in Power Query JE testing with calculated columns Other test- opening balances

Introduction to a Data Analytics Workflow (will be re-introduced in final class to bring all concepts together) Overview of various definitions of data analytics Data analytics needs multiple sources of data Introduction to Power Query (Get & Transform)- on data tab in Excel Exercise- connecting to various Data Sources Importing Excel workbook into Power Query Connecting to a website in Power Query

How to join tables using VLOOKUP Power Query- append queries and merge queries Power Pivot- Creating a relationship via diagram view Types of relationships Data integrity Normalization Facts vs dimension tables Exercises- data modeling VLOOKUP and index match formula Appending data in Power Query Merging data in Power Query Connection only queries Creating a relationship in Power Pivot

An ETL tool- Extract Transform and Load How Power Query ups your game in data analytics Interface components of Power Query Column level and table actions Power Query is a sequential macro recorder What is M Code? Exercise- cleaning and transforming a general ledger

Creating a table Parts to a table Benefits of an Excel table Structured references How it helps to create formulas Formulas are column based not cell based Tables are data sources for Power Query Exercises- tables Creating a table Resizing a table Removing duplicates Descriptive Statistics using the Total Row Inserting a slicer Creating formulas using structured references

Named ranges- how they help in creating formulas Naming conventions and why they are important What you need to know to master formulas How to audit your formulas to limit errors Exercises- formulas Named ranges How to enter a formula- best practices to improve skill levels

Fields in a PivotTable Benefits of PivotTable Contextual tabs for a PivotTable Field setting dialog box Value field setting dialog box Pivot table options Exercises- PivotTables Creating a PivotTable Grouping by date Sorting a PivotTable Filtering a PivotTable Calculations in a PivotTable Slicers and timelines Introduces OLAP (Online Analytical Processing) pivot tables in Power Pivot

Visualization tools in Excel (camera, slicers, and timelines) Data view- why it went away. Power BI is the visualization tool to use All concepts learned in course are brought together in this last class to create a dashboard: Power Query- to extract transform and load data for the dashboard Power Pivot -to create the data model for the dashboard DAX formulas- for pivot tables to calculate values needed for model Pivot tables and charts- to create visualizations Camera tool to create dashboard Exercise- Using the data analytics workflow introduced in first class of series- to create dashboard for JE testing Journal entry by month and income statement accounts Descriptive statistics of journal entries Number of journal entry by month Journal entries by day of week Round journal entries Evaluate output of journal entry analytic Other approaches What are the false positives (noise)? Next steps in data analytics journey

Definition of data analytics and big data; challenges and goals; establishing an environment for success; governance; common uses of analytics and current examples Behavioral forces that impact decisions; examples of inaccurate forecasts; identifying strategic measurements (KPIs); data sources Statistical tools, including median, mode, moving average, ratio analysis, Pareto analysis, trend analysis, regression, z-score, and simulation Software tools that are readily available and can assist in visually exploring data, expanding the scope of available data, as well as collecting, analyzing, and presenting results Specific ideas for using data analytics for accountants and financial managers, including current examples and areas for further consideration Lists of readings and next-level software for a participant’s future reference

New professional standards issued by the FASB and AICPA Guidance on likely COVID-19-related accounting issues that you are likely to face Insights on best practices in managing new working environments Other topics of importance for all accounting practitioners

New professional standards issued by the FASB and AICPA Guidance on likely COVID-19-related accounting issues that you are likely to face Insights on best practices in managing new working environments Other topics of importance for all accounting practitioners

New professional standards issued by the FASB and AICPA Guidance on likely COVID-19-related accounting issues that you are likely to face Insights on best practices in managing new working environments Other topics of importance for all accounting practitioners

New professional standards issued by the FASB and AICPA Guidance on likely COVID-19-related accounting issues that you are likely to face Insights on best practices in managing new working environments Other topics of importance for all accounting practitioners