Data Quality in Practice – Focus on Excel
Practical introduction to the competent handling of data
Contents
- Excel Basics (optional after needs assessment): In this chapter, you will learn the basics of using Excel that you need to structure and prepare data in tables. Using a practical example on the topic of financial planning, you will learn everything you need to know when creating an Excel file—for example, how to format columns and cell values correctly and why it is worth formatting important cell ranges as table objects. You will apply formulas and functions for simple calculations and learn to distinguish between relative, absolute, and mixed cell references. You will learn how to make your formulas even easier to understand with structured references and how to filter and sort tables to get a better overview of your data.
- Understanding Data: In this chapter, you will learn how to summarize, analyze, and visualize data in order to gain insights. And as practically as possible! You will learn how to use and interpret basic statistical metrics, pivot tables, and data slices for simple analyses. You will learn how to use named ranges to make formulas easier to understand and conditional formatting to highlight important data points. With functions such as XLOOKUP(), you will learn how to use Excel as an effective tool for data organization. And, of course, in addition to metrics and aggregated tables, you will also learn how to use visualizations effectively to understand your data. At the end, you can look forward to an exciting interim project where you can put all your data and Excel skills to the test once again.
- Ensuring Data Quality: This chapter deals with ensuring data quality standards – at every stage of the value chain. You will learn about the dimensions of data quality and how to deal with unclean data. But not just in theory, but in a practical way using real data. You will learn how to deal with typical errors when importing different data sources, how to clean up data using the PowerQuery Editor, and how to ensure certain aspects of data quality through formula and data checks, among other things. The analysis skills from Chapter 1 will also be put to use here. The limitations of the Excel tool will also be examined in more detail in this chapter. At the end of the chapter, you can look forward to another exciting final project in which you can consolidate all your newly acquired skills.
Learning environment
This online course offers a particularly practice-oriented learning concept with comprehensive self-study units and a team of mentors who are available throughout the course. With a time budget of 3–5 hours per week, you are sure to reach your goal in 8 weeks.
This is what you will learn in the course:
Data Lab:The course learning environment features videos, interactive graphics, text, and, above all, lots of practical exercises with comprehensive datasets. You can complete these directly in your browser or import them into Excel.
Mentor team: Learning coaches are available to answer any questions. These are experienced data analysts who are happy to help - via chat, audio or video call.
Webinars: Once a week, you have the opportunity to take part in webinars and immerse yourself in selected specialist data analysis topics.
Career coaching: What professional goals are you pursuing with further training and how can you achieve them? A team of mentors is on hand to help you achieve your career goals.
Certificate: Aftercompleting the final project, you will receive your official certificate of participation in this training course.
This online training is provided by our partner StackFuel GmbH. StackFuel specializes in training courses on data literacy, data science and AI.
Your benefit
You will learn in this course:
- Excel basics.
- Structure and prepare data in tables to create clear data bases.
- Summarize, analyze, and visualize data to gain insights.
- Use pivot tables and lookup functions to better understand your data.
- handling data correctly and improving data quality.
Recommended for
This beginner's course is aimed at anyone who makes data-based decisions or regularly works with data. The training is suitable for career changers. Basic computer skills and familiarity with Microsoft Office products are advantageous.
Further recommendations for "Data Quality in Practice – Focus on Excel"
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