Blog

Creating a Culture of Team Excellence

In this highly interactive and engaging full-day session, attendees will work collaboratively to determine their shared meaning of a culture of excellence.  Furthermore, each individual will be challenged to identify how he/she is “showing up” to be in alignment with that vision, how he/she wants to, and can, contribute to taking the team from good to great, and what mindset shifts need to occur at all levels to reach its greatest potential.  Most importantly, participants will complete assessments and exercises to gain self-awareness that will be shared within the team to increase an understanding and appreciation of one another.

Objectives:

  • To identify the meaning of a culture of excellence
  • To collaboratively create a team definition of excellence and evaluate if and how there is current alignment
  • To understand a personal mindset of excellence and how it impacts enduring success
  • To identify strategies that leverage a mindset of excellence to produce performance excellence
  • To understand the principles of building a high-performance team and identify strategies to achieve one
  • To gain awareness of the 3 virtues of being an ideal team player
  • To determine one’s standing as an ideal team player and strategies to create balance among the 3 virtues
  • To share aspects of themselves with their peers
  • To leave with agreed upon goals that leverage strengths, encourage collaboration and incorporate accountability to achieve the highest level of team success

Outcomes:

  • An agreed upon meaning and statement of team excellence, as well as tangible actions, decisions and behaviors to ensure alignment
  • An awareness of how mindset impacts success and identify the current state of individual and collective mindsets
  • Tangible strategies to create and leverage a mindset of excellence
  • Increased knowledge and understanding of fellow team members that will positively impact collaboration, engagement and interactions
  • An awareness of personal contributions and deterrents to the team’s ability to be highly performing
  • A more unified, aligned and motivated team

Assessments and Exercises:

  • Best of Me Activity: Participants will complete this prior to the session to identify the circumstances, conditions and environments that bring out the best and worse of the individual, what others can expect from them and how others can help
  • Six Basic Human Needs: Participants will complete this assessment prior to training to understand how their top needs impact their behaviors, interactions, decisions and fulfillment.
  • The Ideal Team Player Assessment: Participants will complete this during the training to identify their strengths and areas for development as a team player
Read More

Using ChatGPT for Data Analysis with Excel and Power BI

Click Here For More Information

Using ChatGPT for Data Analysis with Excel and Power BI

Virtual Live

Course Description Unlock the power of AI to elevate your data analysis skills in this interactive, instructor-led workshop. Using ChatGPT for Data Analysis with Excel and Power BI is a practical, hands-on […]

$225.00

Course Description

Unlock the power of AI to elevate your data analysis skills in this interactive, instructor-led workshop. Using ChatGPT for Data Analysis with Excel and Power BI is a practical, hands-on course designed for analysts, finance professionals, and Excel/Power BI users who want to streamline tasks, uncover insights faster, and automate repetitive processes using natural language.

Through guided activities and real-world scenarios, you’ll learn how to craft effective prompts, use ChatGPT to write formulas, debug code, build dashboards, and generate analysis summaries—all while understanding the limitations and best practices of AI assistance. This 4-hour course equips you with the tools to integrate ChatGPT into your day-to-day data workflow and communicate more effectively with your AI co-pilot.


Course Objectives

By the end of this course, participants will be able to:

  • Understand how ChatGPT supports data analysis in Excel and Power BI
  • Craft clear, targeted prompts to generate accurate and useful AI responses
  • Use ChatGPT to write and troubleshoot Excel formulas, Power Query M code, and simple macros
  • Apply ChatGPT to generate and explain DAX measures and Power BI visual design ideas
  • Automate report formatting and data cleanup using AI-generated scripts
  • Evaluate and refine ChatGPT outputs for reliability, accuracy, and clarity
  • Complete a full data analysis workflow—from cleaning to insight communication—using ChatGPT

Course Outline

Module 1: Getting Started with ChatGPT for Data Work

Topics Covered:

  • Role of ChatGPT in modern data workflows
  • Prompt writing fundamentals
  • Strengths and limitations of ChatGPT in analytics
  • Techniques to refine and improve prompts

Hands-On Activities:

  • Rewriting vague prompts for clarity
  • Prompting ChatGPT to design a data cleanup strategy in Excel

Module 2: Using ChatGPT with Excel

Topics Covered:

  • Generating advanced Excel formulas using natural language
  • Troubleshooting formulas with AI assistance
  • Writing Power Query M code with ChatGPT
  • Automating tasks with macros or Office Scripts

Hands-On Activities:

  • Practice prompt testing for formulas and macros
  • Build a report in Excel using ChatGPT-generated calculations and formatting scripts

Module 3: Using ChatGPT with Power BI

Topics Covered:

  • Writing and interpreting DAX with ChatGPT
  • Fixing common issues in DAX or M code
  • Visual suggestions for effective dashboards
  • Using ChatGPT to write summaries for stakeholders

Hands-On Activities:

  • Generate and implement DAX measures in Power BI
  • Use ChatGPT to suggest visuals and build a basic dashboard
  • Draft an executive summary based on your data story

Module 4: Final Challenge – AI-Powered Business Analysis

Topics Covered:

  • Prompt engineering for end-to-end analysis
  • AI-guided workflow from raw data to insight
  • Critically assessing ChatGPT output for quality and completeness

Hands-On Final Project:

  • Clean, analyze, and summarize a retail sales dataset
  • Build a final report/dashboard in Excel or Power BI using ChatGPT guidance
  • Deliver a one-page summary using AI-generated content

Bonus Task (Optional):

    • Use ChatGPT to generate automation code (macro or script) to enhance your final report

 

IMPORTANT INFORMATION ABOUT PARTICIPATION:  As part of our sponsorship with NASBA, we have agreed to provide at least three (3) instances of engagement per CPE hour (50 minutes).  These may come in the form of open-ended questions, hand-raising, polling, and other techniques.  You MUST answer or respond to all three opportunities to engage in order to receive credit for that CPE hour.   Knowledge Source Inc. retains these responses after all CPE classes for audit purposes.

Knowledge Source Inc. is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.

Read More

Introduction to AI in Excel for Financial Professionals

Click Here For More Information

COURSE DESCRIPTION:

This course is designed for financial professionals to enhance financial insight through intelligent analytics. It is practical and immediately applicable, with a focus on how AI can support financial analysis, auditing, forecasting, fraud detection, and reporting in Excel.

COURSE OBJECTIVES:

By the end of the course, participants will:

  • Use Excel’s built-in AI features to analyze financial data
  • Automate common reporting and audit tasks using intelligent tools
  • Build forecasts and detect anomalies in cash flow and expenses
  • Apply AI-driven features like Analyze Data, Forecast Sheet, and Power Query

 Lesson 1: Introduction & Overview

  • The role of AI in modern financial reporting
  • Overview of AI tools in Excel

Lesson 2: AI-Driven Insights with Analyze Data & Natural Language

  • Asking Excel questions in plain English
  • Practical: Explore a trial balance and let Excel find insights
  • Use case: Variance and audit reviews

Lesson 3: Forecasting & Trend Analysis o Creating time-based forecasts using Forecast Sheet

  • Best practices for interpreting Excel forecasts
  • Visualizing trends with Sparklines and Conditional Formatting
  • Hands-on: Forecasting monthly expenses or cash flows

Lesson 4: Data Cleaning & Automation with Power Query

  • Using Power Query for intelligent data import and cleanup
  • Automated data transformations and column detection
  • Use case: Preparing large transaction logs or bank feeds
  • Exercise: Clean and combine multiple financial files

Lesson 5: Anomaly Detection & Fraud Flags

  • Flagging outliers with formulas and Z-score logic
  • Highlighting risky transactions with Conditional Formatting o Introduction to Power Pivot for custom financial logic
  • Exercise: Build a dashboard that flags expense anomalies

Lesson 6: Case Study & Wrap-Up

Case Study: AI-assisted monthly close checklist

Discussion: Use cases from participants

Resources & next steps

Read More

Advanced Microsoft SQL Programming – Level III

Click Here For More Information

Course Description: Take your SQL skills to the next level with this hands-on, advanced course designed for professionals who want to master complex data operations and performance optimization. You’ll learn how to write sophisticated queries using Common Table Expressions (CTEs), recursion, and pivoting techniques. Dive into stored procedures, user-defined functions, and triggers to build powerful, automated database solutions. Explore transactional control, robust error handling, and key strategies for tuning and optimizing query performance. You’ll also gain practical experience in securing data and managing large-scale data import/export operations. The course culminates in a real-world project that brings together all the advanced features in a practical business scenario.

Course Objectives: 

By the end of this course, you will be able to:

  • Write complex SQL queries using CTEs, recursion, and pivot/unpivot operations
  • Create and manage stored procedures and user-defined functions
  • Use triggers and transactions to automate and control database operations
  • Implement error handling with TRY…CATCH and custom messages
  • Optimize query performance using indexes and execution plans
  • Apply security best practices, including roles, permissions, and encryption
  • Import, export, and transform data effectively
  • Build a real-world SQL application using advanced techniques

Lesson 1: Complex SQL Queries

  • Using Common Table Expressions (CTEs)
  • Recursive queries with CTEs
  • Pivot and Unpivot operations for data transformation

Lesson 2: Stored Procedures and Functions

  • Creating and using stored procedures
  • Passing parameters to stored procedures
  • Writing and executing functions in SQL

Lesson 3: Triggers and Transactions

  • What are triggers? (e.g., BEFORE, AFTER)
  • Creating and managing triggers for automation
  • Introduction to Transactions and ACID properties
  • COMMIT, ROLLBACK, and SAVEPOINT

Lesson 4: Error Handling

  • TRY…CATCH blocks in SQL Server
  • Custom error messages

Lesson 5: Performance Tuning and Query Optimization

  • Understanding query execution plans
  • Index optimization and strategies
  • Using the SQL Server Profiler to diagnose performance issues
  • Query optimization techniques (e.g., eliminating suboptimal queries)

Lesson 6: Database Security Managing user roles and permissions

  • Implementing security measures (e.g., encryption, data masking)

Lesson 7: Data Import and Export

  • Bulk insert, export, and import data
  • Data transformation during import/export

Project: Design a real-world business application using advanced SQL features. This could involve creating stored procedures for data processing, optimizing queries for large datasets, and implementing triggers for automated actions.

Read More

Intermediate Microsoft SQL Programming – Level II

Click Here For More Information

Course Description

This advanced SQL course is designed for users who are ready to move beyond the basics and tackle more complex queries. Participants will learn to write advanced SELECT statements with refined filtering, perform a variety of joins (including outer, self, and cross joins), and master subqueries for dynamic data retrieval.

The course also covers set operations (UNION, INTERSECT, EXCEPT) and advanced aggregation techniques using GROUP BY, CASE, and powerful window functions like ROW_NUMBER() and RANK(). Through hands-on exercises, learners will develop the skills to build efficient, scalable, and insightful queries for real-world data analysis.

Course Objectives

  • Write Advanced SQL SELECT Statements with Complex Filtering and Deduplication Techniques
  • Perform Complex Joins Including Outer, Self, and Cross Joins to Retrieve Related Data
  • Use Subqueries in Various Clauses to Support Nested and Correlated Data Retrieval
  • Apply SQL Set Operations to Combine and Compare Query Results Effectively
  • Implement Advanced Aggregation, Grouping, and Window Functions for Analytical Queries

Course Outline

Lesson 1:  Advanced SQL SELECT Statement

  • Using DISTINCT to eliminate duplicates
  • Advanced filtering with LIKE, IN, and BETWEEN operators
  • Combining conditions with AND/OR

Lesson 2: Advanced Joins

  • LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN
  • Self Joins and Cross Joins

Lesson 3: Subqueries

  • Using subqueries in SELECT, WHERE, and FROM clauses
  • Correlated subqueries vs. non-correlated subqueries
  • Nested queries for complex data retrieval Lesson

4: Set Operations

  • UNION, UNION ALL, INTERSECT, EXCEPT
  • When to use each set operation

Lesson 5: Advanced Aggregation and Grouping

  • GROUP BY with multiple columns
  • Using CASE statements for conditional aggregation
  • Window Functions (ROW_NUMBER(), RANK(), DENSE_RANK())
Read More

Introduction to AI in Power BI

Click Here For More Information

COURSE DESCRIPTION:

This course is designed to learn the fundamentals of the several AI-powered topics you can explore within Power BI, particularly relevant for business intelligence, financial analytics, or forecasting use cases.

Course Objectives:

By the end of this course, participants will:

  • Understand the Role of AI in Power BI for Business Intelligence and Analytics
  • Apply Descriptive and Diagnostic AI Tools to Explore and Explain Data Trends
  • Use Predictive AI Techniques to Forecast and Model Business Outcomes
  • Leverage Generative and Cognitive AI Features to Automate Insights and Enhance Reports
  • Integrate Custom AI Models and Scripts Using R, Python, and External APIs
  • Build Interactive, AI-Enriched Dashboards for Decision Support and Data Storytelling

Lesson 1: Descriptive & Diagnostic AI in Power BI

Key Influencers Visualization

  • Automatically detects and explains factors driving a particular metric (e.g., sales
    drop, customer churn).

Decomposition Tree

  • Uses AI to help users drill down into data hierarchies and root causes with
    dynamic ranking.

Q&A Visual (Natural Language Query)

  • Enables users to ask questions in natural language and get visual answers
    instantly.

Lesson 2: Predictive AI in Power BI

Forecasting in Time Series Visuals

  • Built-in forecasting using exponential smoothing to predict future values (e.g.,
    demand, revenue).

Regression & Classification via Azure ML Integration

  • Connect Power BI to Azure Machine Learning to run models directly in
    dashboards.

AutoML in Power BI Premium (via Dataflows)

  • Connect Power BI to Azure Machine Learning to run models directly in
    dashboards.

Lesson 3: Generative & Cognitive AI Features

Copilot in Power BI (Preview)

  • Generate DAX formulas, reports, summaries, or data stories using natural
    language prompts.

Smart Narratives

  • Automatically generates textual summaries of visuals, explaining trends, outliers,
    and key drivers.

Image Tagging or Text Recognition with Cognitive Services

  • Use Power BI + Azure Cognitive Services for sentiment analysis, image
    recognition, or text extraction.

Lesson 4: Custom AI Visuals

R & Python Scripting

  • Embed machine learning models and advanced visualizations using custom R/Python
    scripts.

Integration with OpenAI (via API)

  • Use Power Query to connect with GPT models for summarization, classification, or
    content generation.

 

Read More

Introduction to Microsoft SQL Programming – Level 1

Click Here For More Information

COURSE DESCRIPTION:

This course is designed to learn the fundamentals of the SQL and describe the Database relationship and introducing DML statements and DDL statements. Hands on action query and a SELECT query,  and more coding techniques that can make your SQL code easier to read and maintain.

COURSE OBJECTIVES:

By the end of this course, participants will be able to:

  • Understand the Structure and Purpose of Relational Databases
  • Write and Execute Basic SQL Statements
  • Develop Intermediate SQL Query Skills
  • Utilize SQL Functions and Expressions for Data Analysis
  • Perform Complex Joins Between Tables
  • Create and Maintain Database Structures
  • Write Efficient, Readable, and Maintainable SQL Code

Lesson 1: Introduction to Relational Databases and SQL

  • An introduction to the relational database model
  • DBMS, SQL, Query
  • Data Type
  • DML Statements and DDL Statements

Lesson 2: The essential SQL skills

  • An introduction to the 4-SQL statements
  • How to retrieve data from a single table
  • How to code summary queries
  • How to code subqueries

Lesson 3: More SQL Skills for Developers

  • SELECT statements and where clauses
  • How to work with data types
  • How to code the WHERE clause and how to use comparison operators
  • How to use the AND, OR, and NOT logical operators
  • How to use the IN operator
  • How to use the BETWEEN operator
  • How to use the LIKE operator
  • How to use the IS NULL clause and how to code the ORDER BY clause
  • How to sort a result set by a column name
  • How to sort a result set by an alias, an expression, or a column number
  • How to retrieve a range of selected rows

Lesson 4: SQL FUNCTIONS AND EXPRESSIONS

  • Using DISTINCT
  • Using Arithmetic Expressions
  • Using FORMAT Function
  • Using Literals
  • Using String Functions
  • Extracting Text from a String.
  • Changing Part of a String
  • Finding a piece of text in a string.
  • Date Functions
  • Date Datatypes
  • Date Format
  • How to use the TOP clause to return a subset of selected rows

Lesson 5: How to work with inner joins

  • How to code an inner join
  • When and how to use correlation names
  • How to work with tables from different databases
  • How to use compound join conditions
  • How to use a self-join
  • Inner joins that join more than two tables
  • How to use the implicit inner join syntax

Lesson 6: How to create and maintain databases, tables, and sequences with SQL statements

  • An introduction to DDL
  • How to create databases, tables, and indexes
  • How to alter a table and how to delete an index, table, or database
  • How to work with views
  • How to view the database diagrams
Read More

Advanced Excel for Financial Professionals: Tools to Automate, Analyze, and Audit Financial Data

Click Here For More Information

Course Description:

Advanced Excel for Financial Professionals:   Tools to Automate, Analyze, and Audit Financial Data is designed specifically for accounting professionals who want to deepen their Excel skills for financial reporting, data analysis, and process automation. Participants will explore essential Excel tools and techniques used by CPAs to clean, analyze, and summarize financial data efficiently. Topics include PivotTables and PivotCharts, VLOOKUP and XLOOKUP, Data Validation, Conditional Formatting, Macros and VBA, Power Query, and Power Pivot. Through practical exercises and a final capstone challenge, learners will gain the skills to automate routine tasks, audit-proof spreadsheets, and deliver insightful, professional-grade reports.

Course Objectives:

By the end of this course, participants will be able to:

  • Summarize and visualize large volumes of financial data using PivotTables and PivotCharts.
  • Use VLOOKUP and XLOOKUP to cross-reference accounting records across multiple datasets.
  • Apply Data Validation techniques to prevent entry errors and ensure consistency.
  • Highlight risks, outliers, and key metrics using Conditional Formatting.
  • Record and edit Macros to automate repetitive month-end close tasks.
  • Clean and consolidate financial exports using Power Query.
  • Build Data Models and perform scenario analysis with Power Pivot and What-If Analysis tools.
  • Integrate all tools into an automated, audit-ready financial summary.

Course Outline:

Module 1: PivotTables and PivotCharts – Summarizing Financial Data

  • Creating dynamic PivotTables
  • Customizing PivotCharts
  • Using slicers for interactive dashboards

Module 2: Lookup Functions – Cross-Referencing Data with VLOOKUP & XLOOKUP

  • VLOOKUP vs. XLOOKUP
  • Error handling and validation use cases

Module 3: Data Validation – Ensuring Clean, Audit-Ready Spreadsheets

  • Drop-down lists and custom rules
  • Numeric and date validation
  • Preventing inconsistent data entry

Module 4: Conditional Formatting – Highlighting Risks and Exceptions

  • Built-in rules and custom formulas
  • Icon sets, data bars, and color scales
  • Advanced formatting for exception reporting

Module 5: Macros & VBA – Automating Month-End Close Tasks

  • Recording and running macros
  • Editing basic VBA
  • Assigning macros to buttons

Module 6: Power Query – Cleaning and Consolidating Financial Exports

  • Importing and transforming data
  • Merging queries
  • Automating data cleanup

Module 7: Power Pivot and What-If Analysis – Advanced Forecasting and Modeling

  • Building Data Models
  • Goal Seek, Scenario Manager, and Data Tables
  • Sensitivity analysis and financial planning

Final Challenge: Building an Automated Financial Summary

  • End-to-end case project integrating all tools
  • Hands-on financial dashboard with forecasting features

Appendices:

  • A: Excel Shortcut Cheat Sheet
  • B: Glossary of Key Terms
Read More