Author : | Lenny Wu, CPA, CGA, MBA |
Course Length : | Pages: 20 ||| Review Questions: 5 ||| Final Exam Questions: 8 |
CPE Credits : | 1.5 |
IRS Credits : | 0 |
Price : | $21.95 |
Passing Score : | 70% |
Course Type: | Video - NASBA QAS - NASBA Registry |
Technical Designation: | NonTechnical |
Primary Subject-Field Of Study: | Computer Software & Applications - Computer Software & Applications for Course Id 2216 |
Description : | The course is presented in four parts. First, brief introduction to Power Pivot and discuss reasons it has become more versatile than the conventional pivot table:
Second part is to demonstrate basic maneuvers on how to:
Third, we demonstrate 6 fundamental DAX formulas in Power Pivot to get you started in building advanced models for effective analytics, including:
Last, we culminate the webinar with the best practices in Power Pivot modeling, including:
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Usage Rank : | 10000 |
Release : | 2023 |
Version : | 1.0 |
Prerequisites : | |
Experience Level : | Overview |
Additional Contents : | Complete, no additional material needed. |
Additional Links : |
The Importance of Excel in Business
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Advance Preparation : | |
Delivery Method : | QAS Self Study |
Intended Participants : | Anyone needing Continuing Professional Education (CPE). |
Revision Date : | 22-Jan-2024 |
NASBA Course Declaration : | Participants must complete the final examination within one year of purchase and with a minimum passing grade of 70% or better to receive CPE credit unless otherwise noted on the Course History page (i.e. California Ethics must score 90% or better). After logging in click on the Course History links on your My Courses page for the Begin date and Expire date for the Final Exam. |
Approved Audience : | Video - NASBA QAS - NASBA Registry - 2216 |
Keywords : | Computer Software & Applications, Power, Pivot, Big, Data, Analysis, Made, Easy, Video, cpe, cpa, online course |
Learning Objectives : |
Course Learning Objectives After this course, you will be able to:
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Course Contents : | Chapter 1 - Power Pivot: Big Data Analysis Made Easy Chapter 1 Review Questions Glossary/Index |