COURSE MODULE

Data Cleaning and Preparation

Prepare raw datasets for accurate analysis.

9 Lessons

3 Module

LEARNING PATH

Module Lessons

Explore the learning materials and work through the lessons in this module.

9 Lessons

Available

LESSON 1

Understanding Dirty Data

Understanding Dirty Data Data cleaning and preparation is one of the most important stages of the data analysis process. Before...

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LESSON 2

Missing Values

Missing Values Missing values are one of the most common data-quality problems encountered by data analysts. A missing value occurs...

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LESSON 3

Duplicate Records

Duplicate Records Duplicate records are one of the most common problems encountered during data cleaning. A duplicate occurs when the...

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LESSON 4

Incorrect Formats

Lesson 4: Incorrect Formats Data format problems occur when information is stored in a form that is inconsistent, inappropriate or...

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LESSON 5

Data Consistency

Lesson 5: Data Consistency Data consistency is the practice of ensuring that the same type of information is represented in...

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LESSON 6

Outlier Identification

Outlier Identification An outlier is an observation that is unusually far away from the general pattern of the other observations...

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LESSON 7

Data Transformation

Data Transformation Data transformation is the process of converting data from its original form into a more useful, consistent, standardized,...

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LESSON 8

Data Validation

Data Validation Data validation is the process of checking data to determine whether it is accurate, complete, consistent, reasonable, and...

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LESSON 9

Preparing Analysis-Ready Datasets

Preparing Analysis-Ready Datasets An analysis-ready dataset is a dataset that has been carefully structured, cleaned, transformed, validated, documented, and prepared...

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