课程信息

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初级
完成时间大约为12 小时
英语(English)
字幕:英语(English)

您将学到的内容有

  • Distinguish operational from analytic databases, and understand how these are applied in big data

  • Understand how database and table design provides structures for working with data

  • Appreciate how differences in volume and variety of data affects your choice of an appropriate database system

  • Recognize the features and benefits of SQL dialects designed to work with big data systems for storage and analysis

您将获得的技能

Database (DBMS)Data WarehousingData AnalysisBig DataSQL
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为12 小时
英语(English)
字幕:英语(English)

提供方

Cloudera 徽标

Cloudera

教学大纲 - 您将从这门课程中学到什么

内容评分Thumbs Up97%(1,585 个评分)Info
1

1

完成时间为 2 小时

Data and Databases

完成时间为 2 小时
11 个视频 (总计 50 分钟), 4 个阅读材料, 1 个测验
11 个视频
Welcome to the Course and Week 13分钟
What Is Data?3分钟
Why Organize Data?5分钟
What Does a DBMS Do?5分钟
Relational Databases and SQL6分钟
The Success of RDBMSs and SQL4分钟
Operational and Analytic Databases5分钟
Comparing Operational and Analytic DBs: SELECT Statements2分钟
Comparing Operational and Analytic DBs: DML Activity4分钟
Operational and Analytic Databases: Further Comparisons1分钟
4 个阅读材料
Hardware Requirements for the Exercise Environment10分钟
Data Extraction from Digital Images10分钟
Three Notes about SQL10分钟
References10分钟
1 个练习
Data and Databases30分钟
2

2

完成时间为 3 小时

Relational Databases and SQL

完成时间为 3 小时
15 个视频 (总计 80 分钟), 3 个阅读材料, 1 个测验
15 个视频
Introducing Table Schemas3分钟
NULL Values3分钟
Data Types3分钟
Primary Keys5分钟
Foreign Keys6分钟
Two Strategies for Database Design3分钟
Database Normalization8分钟
Denormalization5分钟
Differences6分钟
Trade-offs4分钟
Database Transactions6分钟
ACID6分钟
Enforcing Business Rules: Constraints and Triggers7分钟
Business Rules and ACID for Analytics?6分钟
3 个阅读材料
Let There Be Third Normal Form5分钟
SELECT Statements in Transactions5分钟
Database Indexes30分钟
1 个练习
Relational Databases30分钟
3

3

完成时间为 2 小时

Big Data

完成时间为 2 小时
12 个视频 (总计 63 分钟), 1 个阅读材料, 1 个测验
12 个视频
How Big Is Big Data?3分钟
Distributed Storage6分钟
Distributed Processing9分钟
Structured Data4分钟
Unstructured Data4分钟
Semi-Structured Data3分钟
Strengths of Traditional RDBMSs4分钟
Limitations of Traditional RDBMSs7分钟
SQL and Structured Data5分钟
SQL and Semi-structured Data4分钟
SQL and Unstructured Data7分钟
1 个阅读材料
What about Velocity?15分钟
1 个练习
Big Data30分钟
4

4

完成时间为 2 小时

SQL Tools for Big Data Analysis

完成时间为 2 小时
12 个视频 (总计 53 分钟), 1 个阅读材料, 1 个测验
12 个视频
Big Data Analytic Databases (Data Warehouses)2分钟
NoSQL: Operational, Unstructured and Semi-structured4分钟
Non-transactional, Structured Systems2分钟
Big Data ACID-Compliant RDBMSs1分钟
Search Engines4分钟
Challenges4分钟
What We Keep3分钟
What We Give Up5分钟
What We Add8分钟
Where to Store Big Data7分钟
Coupling of Data and Metadata7分钟
1 个阅读材料
Open Source and Apache15分钟
1 个练习
SQL Tools for Big Data Analysis30分钟

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关于 Modern Big Data Analysis with SQL 专项课程

This Specialization teaches the essential skills for working with large-scale data using SQL. Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you. Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that’s being generated is too big to be stored there, and it’s growing too quickly to be efficiently stored in commercial data warehouses. Instead, it’s increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable. To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines. This Specialization is designed to provide excellent preparation for the Cloudera Certified Associate (CCA) Data Analyst certification exam. You can earn this certification credential by taking a hands-on practical exam using the same SQL engines that this Specialization teaches—Hive and Impala....
Modern Big Data Analysis with SQL

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