课程

Cleaning Data in SQL Server Databases

中级技能水平

更新时间 2022年4月

Develop the skills you need to clean raw data and transform it into accurate insights.

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SQLData Preparation4 小时13 视频48 练习3,750 经验值11,603成就声明

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课程描述

Did you know that data scientists and data analysts spend a large amount of time cleaning data before they can analyze it? This is because real-world data is messy. To help you navigate messy data this course teaches you how to clean data stored in an SQL Server database. You’ll learn how to solve common problems such as how to clean messy strings, deal with empty values, compare the similarity between strings, and much more. You’ll get hands-on with all these tasks using a wide range of interesting and messy datasets, including monthly airline flights by airport, TV series and paper shop sales. Are you ready to get your hands messy?

先决条件

Intermediate SQL Server

1

Starting with Cleaning Data

To begin the course, you will learn why cleaning data is important. You will solve simple problems such as leading and trailing spaces in strings, unifying formats for flight registrations, combining strings and more.

Introduction to Cleaning Data

50 经验值

Unifying flight formats I

100 经验值

Unifying flight formats II

100 经验值

Cleaning messy strings

50 经验值

Trimming strings I

100 经验值

Trimming strings II

100 经验值

Unifying strings

100 经验值

Comparing the similarity between strings

50 经验值

SOUNDEX() and DIFFERENCE()

50 经验值

Comparing names with SOUNDEX()

100 经验值

Comparing names with DIFFERENCE()

100 经验值

2

Dealing with missing data, duplicate data, and different date formats

In this chapter, you will deepen your data cleaning knowledge. You will learn how to deal with missing data, avoid duplicate data in your datasets, and work with different formats of dates.

Dealing with missing data

50 经验值

Removing missing values

100 经验值

Removing blank spaces

100 经验值

Filling missing values using ISNULL()

100 经验值

Filling missing values using COALESCE()

100 经验值

Avoiding duplicate data

50 经验值

Diagnosing duplicates

50 经验值

Treating duplicates

100 经验值

Dealing with different date formats

50 经验值

Using CONVERT()

100 经验值

Using FORMAT()

100 经验值

CONVERT() vs FORMAT()

50 经验值

3

Dealing with out of range values, different data types, and pattern matching

In this chapter, you will deal with out of range values and inaccurate data. You will also practice converting data with different types. Finally, you will work on matching patterns to your data to find outliers.

Out of range values and inaccurate data

50 经验值

Out of range values or inaccurate data?

50 经验值

Detecting out of range values

100 经验值

Excluding out of range values

100 经验值

Detecting and excluding inaccurate data

100 经验值

Converting data with different types

50 经验值

Using CAST() and CONVERT()

100 经验值

The series with most episodes

50 经验值

Pattern matching

50 经验值

Characters to specify a patterns

50 经验值

Matching urls

100 经验值

Checking phone numbers

100 经验值

4

Combining, splitting, and transforming data

In this final chapter, you will learn how to combine and aggregate data of some columns into one, split data of one column into more columns, and transform rows into columns and vice versa.

Combining data of some columns into one column

50 经验值

Combining cities and states using +

100 经验值

Concatenating cities and states

100 经验值

Working with DATEFROMPARTS()

100 经验值

Splitting data of one column into more columns

50 经验值

Using SUBSTRING() and CHARINDEX()

100 经验值

Using RIGHT() , LEFT() and REVERSE()

100 经验值

SUBSTRING() or CHARINDEX()?

50 经验值

Transforming rows into columns and vice versa

50 经验值

PIVOT or UNPIVOT?

50 经验值

Turning rows into columns

100 经验值

Turning columns into rows

100 经验值

Congratulations!

50 经验值

Cleaning Data in SQL Server Databases

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