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ADP Learning Academy

Successful Compensation and Benefit Analysts consistently use data to drive their decisions in managing projects, tasks, and strategies. This course provides you with the foundational knowledge needed to develop essential skills in project management, data analytics, Microsoft Excel, and data visualization. You’ll have a chance to strengthen these skills throughout the rest of this Certificate program as you complete hands-on projects for your professional portfolio.

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What's inside

Syllabus

Module 1: Project Management Basics
This module focuses on a skill in high demand around the world: project management. You’ll start with basic definitions and concepts, then different methodologies – like waterfall, Agile, and critical path. You’ll also explore useful project tools and visuals. You’ll begin to apply your new knowledge by creating two common project artifacts: a RACI chart and a project timeline.
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what should give you pause
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Provides foundational knowledge in project management, data analytics, Microsoft Excel, and data visualization
Suitable for Compensation and Benefit Analysts seeking to enhance their decision-making skills through data-driven analysis
Emphasizes the practical application of learned skills through hands-on projects for professional portfolio development
Covers essential aspects of project management, including methodologies, tools, and timelines
Introduces concepts and techniques for data analytics, data privacy, and different types of data analysis
Guides learners in collecting data effectively through various methods and tools

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Reviews summary

Essential skills for comp & benefits

According to learners, this course is a highly relevant and practical introduction to essential skills for Compensation & Benefits professionals. Students particularly value the hands-on projects and clear explanations. The Excel exercises, especially on data cleaning and data visualization, are frequently cited as valuable for immediate workplace application. While providing a solid foundational knowledge, some more experienced learners noted the course might be too introductory regarding deeper data analytics concepts, suggesting it's ideal for beginners or those new to the field. Overall, it's considered well-organized and effective for its stated purpose.
Provides a solid foundation, though may be introductory for experienced pros.
"It's perfect for beginners in the field."
"Only useful if you're absolutely new to everything."
"Felt like a very broad overview rather than an in-depth dive. Good for total novices."
"A good entry point for someone transitioning into a Comp & Benefits role."
Clear and well-organized introduction to project management basics.
"The project management module was incredibly well-structured."
"I appreciated the emphasis on... structured approach to project management."
"The project management part was useful."
Strong focus on data cleaning and visualization in Excel.
"The Excel exercises were practical and directly applicable."
"The lessons on data cleaning in Excel were invaluable."
"I loved the hands-on data visualization section, it really helped me tell a story with data."
"The Excel tips were great."
Equips learners with directly applicable workplace skills.
"I can immediately apply these skills at work."
"The focus on practical, actionable skills is its strongest point."
"This course is a game-changer... directly applicable."
"I particularly enjoyed the practical application of concepts, especially the RACI chart exercise."
Offers a broad introduction, but some desired more in-depth coverage.
"I found the data analytics modules a bit too shallow."
"While it touches on relevant topics, it felt too superficial."
"For data analytics, I needed to supplement with other resources to get a deeper understanding."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Essential Skills for Comp & Benefits Professionals with these activities:
Review spreadsheet functions
Provide a fresh context and opportunity to practice using spreadsheet functions before the course begins
Browse courses on Microsoft Excel
Show steps
  • Look through your notes or textbooks from a previous course on spreadsheets
  • Go over basic functions such as SUM, AVERAGE, and COUNTIF
  • Try to apply these functions to a simple dataset
Learn about project management methodologies
Help students understand the different project management methodologies to prepare them for Module 1
Browse courses on Project Management
Show steps
  • Find online tutorials on project management methodologies
  • Watch the tutorials and take notes on the key concepts
  • Compare and contrast the different methodologies
Form a study group with other students
Facilitate collaboration and knowledge sharing among students
Show steps
  • Find other students who are taking the same course
  • Schedule regular study sessions
  • Discuss the course material and work on assignments together
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice creating data visualizations
Provide students with an opportunity to practice creating data visualizations to prepare them for Module 5
Browse courses on Data Visualization
Show steps
  • Choose a dataset to work with
  • Use a data visualization tool to create different types of visualizations
  • Analyze the visualizations and draw conclusions from the data
Develop a project plan
Allow students to apply the concepts they learn in Module 1 by developing a project plan for a real-world project
Browse courses on Project Management
Show steps
  • Define the project scope and objectives
  • Create a project timeline and budget
  • Identify the resources needed for the project
  • Develop a communication plan for the project
Write a white paper on a data analytics topic
Challenge students to synthesize their knowledge of data analytics and communicate it effectively in writing
Browse courses on Data Analytics
Show steps
  • Choose a specific data analytics topic to focus on
  • Conduct research on the topic
  • Develop a thesis statement and outline for the white paper
  • Write the white paper
  • Edit and proofread the white paper
Attend a data analytics conference or meetup
Encourage students to connect with professionals in the field of data analytics
Browse courses on Data Analytics
Show steps
  • Find a data analytics conference or meetup in your area
  • Register for the event
  • Attend the event and network with other attendees

Career center

Learners who complete Essential Skills for Comp & Benefits Professionals will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 47 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Essential Skills for Comp & Benefits Professionals.
Seminal work on the grammar of graphics, a formal language for describing data visualizations. It covers a wide range of topics, from the basics of the grammar of graphics to the use of the grammar of graphics to create a variety of charts and graphs.
This classic book by Edward Tufte must-read for anyone interested in data visualization. It covers a wide range of topics, from the principles of visual perception to the design of effective charts and graphs.
Classic text on project management that provides a comprehensive overview of the field. It great resource for anyone who wants to learn about project management or improve their skills.
The third edition of the essential guide to data wrangling with pandas, NumPy, and Jupyter in Python. Updated for newer versions of the libraries, this book remains a core resource for anyone performing data analysis in Python. It widely used textbook and reference for its clear explanations and practical examples.
A more recent iteration of the comprehensive 'Bible' series, this book covers the features of Excel 2021. It serves as an excellent reference and learning tool for users who want a deep understanding of the software, from basic to advanced functionalities. It's suitable for a wide range of users.
Dives into contemporary Excel topics like Power Pivot and Power Query, which are crucial for handling and analyzing large datasets. It's a key resource for users looking to move beyond basic data analysis and leverage Excel's business intelligence capabilities. Recommended for intermediate to advanced users and professionals.
Specifically targets financial modeling using Excel, a key application in finance and accounting. is essential for students and professionals in these fields who need to build and analyze financial models. It covers relevant formulas, functions, and best practices.
Focuses on creating effective and advanced data visualizations using Excel, going beyond the default chart types. It's highly relevant to contemporary data analysis and communication. It provides step-by-step guides for creating various chart types and is valuable for users at all levels looking to improve their data storytelling.
Practical guide to agile project management that is full of tips and advice. It great resource for anyone who wants to learn how to use agile methods to improve their project management skills.
Comprehensive guide to project management that provides answers to common questions. It great resource for anyone who wants to learn more about project management or solve specific problems.
Provides a foundational understanding of the fundamental principles of data science and the data-analytic thinking necessary for extracting value from data in a business context. It is highly relevant for undergraduate business analytics programs and working professionals. It serves as a useful reference for understanding the business applications of data analysis and is commonly used as a textbook.
Provides a comprehensive overview of data visualization, covering the basics of visual perception, data types, and chart types. It great resource for beginners who want to learn the fundamentals of data visualization.
A focused guide on Power Query, a powerful tool for data extraction, transformation, and loading within Excel and Power BI. is crucial for anyone dealing with data from multiple sources and needing to clean and prepare it for analysis. It's a valuable resource for data professionals.
Practical guide to project management that is full of insights and advice. It great resource for anyone who wants to learn how to manage projects more effectively.
Addresses contemporary data analytics practices within Excel, focusing on modern techniques for cleaning, transforming, and analyzing data. It's highly relevant for those looking to update their skills and leverage Excel for more sophisticated data analysis tasks.
Focuses on applying Excel to solve business problems and analyze business data. It's a practical guide for students and professionals in business-related fields who need to use Excel for decision-making and analysis.
Focuses on the crucial skill of communicating insights from data effectively through compelling visualizations. is highly relevant for all levels, emphasizing the importance of clear and impactful data presentation. It is valuable additional reading that complements technical data analysis skills.
Dives deep into array formulas, a powerful technique for complex calculations in Excel. It's for users who want to deepen their understanding of advanced formulas and push the boundaries of what Excel can do. Recommended for intermediate to advanced users.
Ideal for beginners, this book provides a solid foundation in Excel basics with step-by-step guides. It covers a wide range of fundamental topics, making it a great starting point for those new to spreadsheets. While suitable for initial learning, it also touches upon more complex areas.
A focused guide on mastering Excel formulas and functions, which are fundamental to using Excel effectively. is helpful for users looking to deepen their understanding of how to perform calculations and manipulate data. Relevant for all levels beyond the absolute beginner.
Bridges the gap between statistical theory and its practical application in data science using R and Python. It focuses on the statistical concepts most relevant to data scientists and provides code examples. It's a useful reference and learning resource for those applying statistics in their work.
Offers a hands-on approach to learning Excel VBA, with step-by-step instructions and exercises designed for quick learning. It's suitable for users who want to rapidly acquire VBA skills for automation and enhancing their Excel capabilities.
Offers a new way of thinking about data science and ethics informed by intersectional feminist thought. It challenges existing power structures within data and explores how data can be used to work towards justice. It's highly relevant for contemporary discussions around fairness and bias in data analysis.
Is an excellent starting point for anyone new to data analysis or statistics. It demystifies core statistical concepts without relying heavily on mathematical formulas, making it highly accessible for high school and undergraduate students. It provides a strong foundation in the intuition behind statistical analysis and helps readers understand how data can be used and misused. This is valuable background reading that builds prerequisite knowledge.
Provides a guide to creating effective and aesthetically pleasing data visualizations. It delves into the principles behind good visualization design, helping readers make informed choices about how to represent their data. It valuable reference for anyone creating visualizations, from students to professionals.
A beginner-friendly approach to learning Excel VBA programming. breaks down complex VBA concepts into easy-to-understand steps, making it accessible for those new to automation. It's a good starting point before moving on to more advanced VBA resources.
A comprehensive guide aiming to take users from beginner to expert. It covers a wide range of topics and can be used for both gaining a broad understanding and deepening knowledge. Its step-by-step approach makes it accessible for self-learners.
Provides a beginner-friendly introduction to data analysis techniques using Excel. It covers essential tools and methods for analyzing data within Excel, making it suitable for those new to data analysis or using Excel for this purpose.
Teaches probability and statistics using a computational approach with Python. It's ideal for students and professionals with programming experience who want to understand statistical concepts by doing. It helps solidify understanding through hands-on application.
Aimed at beginners, this book focuses on overcoming common Excel challenges and making the learning process engaging. It helps solidify foundational skills and provides practical tips for immediate use. It's a good supplementary read for those starting out.
Beginner's guide to using Tableau, one of the most popular data visualization tools. It covers the basics of Tableau, as well as how to use Tableau to create a variety of charts and graphs.
A timeless classic that remains highly relevant today. exposes common ways statistics can be manipulated or misinterpreted, fostering a critical eye essential for anyone working with data. It's valuable for all levels, from high school to professional, as it highlights the importance of data integrity and ethical considerations. This serves as crucial additional reading to develop data literacy.
SQL fundamental skill for data analysis, and this book delves into advanced techniques for working with data in databases. It's essential for anyone who needs to retrieve and manipulate data stored in relational databases. It serves as a valuable reference for more complex data extraction and transformation tasks.
Although an older edition, the Excel 2016 Bible is considered a classic for its comprehensive coverage by a highly respected author in the Excel community. While some features may be outdated, the core principles and in-depth explanations of formulas, functions, and features remain valuable for gaining a deep understanding.
Explores the world of prediction and forecasting across various fields, demonstrating how data analysis and statistical modeling are used in practice. It's particularly engaging for undergraduate and graduate students interested in the application of data analysis in real-world scenarios. It adds breadth by showcasing diverse applications and the challenges involved in making accurate predictions.
Provides a high-level overview of the data science process, from asking questions to interpreting results. It focuses on the principles and concepts rather than specific tools, making it suitable for a broad audience. It helps in gaining a broad understanding of the data analysis workflow.
While more focused on the engineering aspects of data systems, this book provides a deep understanding of the underlying infrastructure for data analysis. It's particularly valuable for graduate students and professionals involved in building and maintaining data pipelines and databases. It adds significant depth to understanding the data landscape.

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