Surgent's Data Analytics Readiness Series: Visualizations and Reporting On-Demand Webcast

Overview

This one-hour course will serve as an introduction to data visualization and reporting using Power BI and Excel. Users will understand the benefits of using Power BI to create data visualizations and how Power BI differs from previous functions in Excel for visualizations. A hands-on exercise will be applied where the user will work alongside the instructor to create dashboarding for journal entry testing. Specific focus will be on the relation among various tools for data analytics: Power Query, Power Pivot, PivotTables, DAX formulas, and storyboarding.

This course is one in a ten-part certification series, Core Data Analytics: Excel and Power BI Skills for Accounting and Finance Professionals, by Surgent IQ.

Prerequisites

2+ years of experience working with Excel

Objectives

• Understand the applicable Excel skills that will be required in making the transition to data analyst 
• Understand what data visualization tools are available in Excel and Power BI and how they are superior to previous Excel tools
• Apply skills learned to create a dashboard for journal entry testing data
• Apply skills to present the output of analytical modeling in an easy to interpret form and evaluate the output of the analytics
• Be able to use the camera tool in Power BI to create dashboards

Highlights

• 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