Creating an Analytical Dataset
About this Course
The Creating an Analytical Dataset course provides students with foundational knowledge to input, clean, blend, and format data in preparation for analysis. You will learn:
The common sources and types of data
To identify and correct common issues with data
To format data in useful ways for analysis
To blend data from multiple sources togetherThroughout this course you’ll also learn the techniques to apply your knowledge in a data analytics …
Creating an Analytical Dataset
About this Course
The Creating an Analytical Dataset course provides students with foundational knowledge to input, clean, blend, and format data in preparation for analysis. You will learn:
The common sources and types of data
To identify and correct common issues with data
To format data in useful ways for analysis
To blend data from multiple sources togetherThroughout this course you’ll also learn the techniques to apply your knowledge in a data analytics program called Alteryx. At the end of the course, you’ll complete a project based on the principles in the course..
This course is part of the Business Analyst Nanodegree.
Learn how to prepare data to ensure the efficacy of your analysis while improving fluency in Alteryx.
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Ever heard of the term garbage in, garbage out? This is as true in analytics as it is anywhere else. In this course, you’ll learn how to prepare data to ensure the efficacy of your analysis, a foundational skill for anyone using advanced analytics. You’ll learn this through improving your fluency in Alteryx, a data analytics tool that enables you prepare, blend, and analyze data quickly. This course is ideal for anyone who is interested in pursuing a career in business analysis, but lacks programming experience.
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lesson 1
Understanding Data
Learn to identify structured, unstructured, and semistructured data.
Get an introduction to the most common data types.
Learn about the most common sources of data.
lesson 2
Data Issues
Learn to clean dirty data.
Learn to how to adjust for missing data.
Be able to identify and correct outliers.
lesson 3
Data Formatting
Learn about the importance of data format for analysis.
Transpose, aggregate, and cross tabulate data.
Learn how to use parse data.
lesson 4
Data Blending
Learn how to merge data from multiple sources.
Learn to use common data blending techniques.
Explore fuzzy matching and spatial analysis
