Enterprise Data Wrangling with SQL and Python

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Enterprise Data Wrangling with SQL and Python

位教师：Tareq Nasralah

包含在中

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4个模块

深入了解一个主题并学习基础知识。

8 小时完成

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

8 小时完成

灵活的计划

自行安排学习进度

要了解的详细信息

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该课程共有4个模块

Welcome to Enterprise Data Wrangling with SQL and Python. This course will cover data wrangling principles and techniques for business. Key topics include data extraction, profiling, cleansing, integration, transformation, and automating data processes for business purposes. In the course, you will apply principles and techniques using data transformation tools, programming languages, and data process automation tools. The course offers you an opportunity to learn how to embed appropriate communication mechanisms for collaboration to identify and resolve real-world data challenges revealed in datasets and business processes, creating business value in today’s disparate computing and dynamic business environment.

In this module, you will learn about the structure of relational databases and how to use SQL queries for information retrieval, focusing on single-row and group functions. In the next module, you will build upon this foundation by exploring data manipulation and data joining techniques.

涵盖的内容

6个视频17篇阅读材料1个作业

6个视频总计17分钟

Meet Your Faculty2分钟
Relational Database Data Structure3分钟
Unique Values 3分钟
Constraints5分钟
Working with Text Values2分钟
TIMESTAMP 3分钟

17篇阅读材料总计85分钟

Course Introduction2分钟
Syllabus - Enterprise Data Wrangling with SQL and Python10分钟
Academic Integrity1分钟
Data Wrangling Key Questions 2分钟
Data Wrangling Steps5分钟
Relational Databases2分钟
Key SQL Concepts10分钟
Overview of Predefined Functions2分钟
Single-Row vs. Group Functions10分钟
Overview of Single-Row Functions1分钟
Common Examples of Single-Row Functions5分钟
Uses of Single-Row Functions4分钟
Single-Row Function Example10分钟
Overview of Group Functions1分钟
Common Examples of Group Functions4分钟
Uses of Group Functions6分钟
Group Function Example10分钟

1个作业总计45分钟

Assess Your Learning: Introduction to Data Wrangling and Relational Databases45分钟

The module also highlights how effective data manipulation and joining contribute to the broader goals of data wrangling and preparation, ensuring that data is both well-organized and ready for analysis.

涵盖的内容

22篇阅读材料1个作业

22篇阅读材料总计146分钟

Data Manipulation Overview2分钟
DML Core Operations10分钟
INSERT5分钟
Update10分钟
Delete8分钟
TCL Core Operations1分钟
Commit3分钟
Rollback5分钟
Summary Table10分钟
Data Joining Overview2分钟
Summary Table with Notes10分钟
Data Joining Types Overview10分钟
Inner Join Overview4分钟
Inner Join Example10分钟
Join Overview4分钟
Left Join Example10分钟
Right Join Overview4分钟
Right Join Example10分钟
Full Outer Join Overview4分钟
Full Outer Join Example10分钟
Cross Join Overview4分钟
Cross Join Example10分钟

1个作业总计45分钟

Assess Your Learning: Managing and Retrieving Data with SQL45分钟

In this module, you will learn how to explore datasets using Python. You’ll practice techniques to inspect dataset structure (rows, columns, and data types), and detect missing, invalid, or inconsistent data. You will also learn how to generate descriptive statistics and distribution summaries, as well as interpret profiling results to guide data cleansing and improve overall data quality.

涵盖的内容

2个视频13篇阅读材料1个作业

2个视频总计6分钟

Data Profiling3分钟
Data Profiling Example3分钟

13篇阅读材料总计61分钟

Data Profiling Overview10分钟
Discovering Data Structure Overview2分钟
Rows and Columns7分钟
Data Type7分钟
Non-Null Entries7分钟
Discovering Data Content Overview3分钟
Summary Statistics4分钟
Descriptive Statistics4分钟
Frequency Distribution4分钟
Missing Values3分钟
Duplicate Data3分钟
Incorrect or Ambiguous Data4分钟
Data Profiling3分钟

1个作业总计15分钟

Assess Your Learning: Data Profiling and Discovery15分钟

By the end of this module, you will be able to apply practical data cleansing techniques to improve data quality and make your analysis more accurate and trustworthy.

涵盖的内容

2个视频11篇阅读材料1个作业

2个视频总计3分钟

Data Cleansing1分钟
Data Cleansing to Handle Outliers2分钟

11篇阅读材料总计29分钟

Data Cleansing Overview2分钟
Overview of Types of Data Issues2分钟
Missing Values3分钟
Duplicates3分钟
Inconsistent Formats3分钟
Outliers and Anomalies3分钟
Incorrect or Invalid Values3分钟
Data Types Conversions3分钟
Filtering3分钟
Data Cleansing Example2分钟
Congratulations! 2分钟

1个作业总计25分钟

Assess Your Learning: Data Cleansing25分钟

位教师

Tareq Nasralah

Northeastern University

1 门课程7 名学生

提供方

Northeastern University

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