In this course, you'll get a big-picture view of using SQL for big data, starting with an overview of data, database systems, and the common querying language (SQL). Then you'll learn the characteristics of big data and SQL tools for working on big data platforms. You'll also install an exercise environment (virtual machine) to be used through the specialization courses, and you'll have an opportunity to do some initial exploration of databases and tables in that environment.
本課程是 Modern Big Data Analysis with SQL 專項課程 專項課程的一部分
Foundations for Big Data Analysis with SQL
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課程信息
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您將學到的內容有
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
您將獲得的技能
Database (DBMS)Data WarehousingData AnalysisBig DataSQL
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第 1 門課程（共 3 門）
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初級
完成時間大約為20 小時
英語（English）
字幕：英語（English）
提供方
Cloudera
At Cloudera, we believe that data can make what is impossible today, possible tomorrow. We empower people to transform complex data into clear and actionable insights. Cloudera delivers an enterprise data cloud for any data, anywhere, from the Edge to AI. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 2 小時
Data and Databases
In this week, you'll get an overview of this Specialization and of Course 1. Then you'll learn about database systems and the distinction between operational and analytic databases.
完成時間為 2 小時
11 個視頻 （總計 50 分鐘）, 4 個閱讀材料, 1 個測驗
11 個視頻
Welcome to the Course and Week 13分鐘
What Is Data?3分鐘
Why Organize Data?5分鐘
What Does a DBMS Do?5分鐘
Relational Databases and SQL6分鐘
The Success of RDBMSs and SQL4分鐘
Operational and Analytic Databases5分鐘
Comparing Operational and Analytic DBs: SELECT Statements2分鐘
Comparing Operational and Analytic DBs: DML Activity4分鐘
Operational and Analytic Databases: Further Comparisons1分鐘
4 個閱讀材料
Hardware Requirements for the Exercise Environment10分鐘
Data Extraction from Digital Images10分鐘
Three Notes about SQL10分鐘
References10分鐘
1 個練習
Data and Databases30分鐘
完成時間為 3 小時
Relational Databases and SQL
完成時間為 3 小時
15 個視頻 （總計 80 分鐘）, 3 個閱讀材料, 1 個測驗
15 個視頻
Introducing Table Schemas3分鐘
NULL Values3分鐘
Data Types3分鐘
Primary Keys5分鐘
Foreign Keys6分鐘
Two Strategies for Database Design3分鐘
Database Normalization8分鐘
Denormalization5分鐘
Differences6分鐘
Trade-offs4分鐘
Database Transactions6分鐘
ACID6分鐘
Enforcing Business Rules: Constraints and Triggers7分鐘
Business Rules and ACID for Analytics?6分鐘
3 個閱讀材料
Let There Be Third Normal Form5分鐘
SELECT Statements in Transactions5分鐘
Database Indexes30分鐘
1 個練習
Relational Databases30分鐘
完成時間為 2 小時
Big Data
完成時間為 2 小時
12 個視頻 （總計 63 分鐘）, 1 個閱讀材料, 1 個測驗
12 個視頻
How Big Is Big Data?3分鐘
Distributed Storage6分鐘
Distributed Processing9分鐘
Structured Data4分鐘
Unstructured Data4分鐘
Semi-Structured Data3分鐘
Strengths of Traditional RDBMSs4分鐘
Limitations of Traditional RDBMSs7分鐘
SQL and Structured Data5分鐘
SQL and Semi-structured Data4分鐘
SQL and Unstructured Data7分鐘
1 個閱讀材料
What about Velocity?15分鐘
1 個練習
Big Data30分鐘
完成時間為 2 小時
SQL Tools for Big Data Analysis
完成時間為 2 小時
12 個視頻 （總計 53 分鐘）, 1 個閱讀材料, 1 個測驗
12 個視頻
Big Data Analytic Databases (Data Warehouses)2分鐘
NoSQL: Operational, Unstructured and Semi-structured4分鐘
Non-transactional, Structured Systems2分鐘
Big Data ACID-Compliant RDBMSs1分鐘
Search Engines4分鐘
Challenges4分鐘
What We Keep3分鐘
What We Give Up5分鐘
What We Add8分鐘
Where to Store Big Data7分鐘
Coupling of Data and Metadata7分鐘
1 個閱讀材料
Open Source and Apache15分鐘
1 個練習
SQL Tools for Big Data Analysis30分鐘
審閱
4.8
來自FOUNDATIONS FOR BIG DATA ANALYSIS WITH SQL的熱門評論
由 AE 提供Sep 9, 2019
Awesome foundation to build on skills of query and analysis of big data and to use big data technologies like Hive and Impala\n\nI Really enjoyed the course and the instructor is perfect
由 AA 提供Aug 14, 2019
If you don't have any background about SQL and you don't know where to start, I think this is the best course to start. It simplifies the concepts into easy ideas to be understandable.
由 SY 提供Mar 3, 2020
Thank you for bringing such a Awesome and High quality course - Cloudera. Course instructors are just exceptional in presenting the course material in a clear, concise manner!
由 AK 提供Jul 25, 2019
Amazing course, full of useful information, the quiz are good way to test your knowledge and the instructor is an expert in this field and has very good presentation skills.
由 PK 提供Jul 26, 2019
Big data is the one of the most emerging technologies in the world and this cloudera course will definitely help us to understand the hive and impala with practical.
由 MO 提供Feb 25, 2020
Excellent course for beginners, that want to get started with big data. This course also help me appreciate traditional RDMS systems while clearing confusions.
由 RP 提供Dec 2, 2019
Useful concepts for starting to understand and learn how world of big data works. Would have enjoyed to be a bit more practical at last assignment.
由 JG 提供Jan 28, 2020
Great foundational course for somebody who has some experience using SQL but no formal training -- it really fills in the gaps.
由 NH 提供Apr 1, 2020
Good start of specialization. Great instructor and nicely elaborated difference between RDBMS and Big Data Analytics.
由 MD 提供Dec 8, 2019
Amazing course! :) Very well introduction to Big Data ecosystem and gold-standard information about SQL.
由 ER 提供Oct 19, 2019
informative background info of Big Data that's good to know about. not too simple or too challenging.
由 HA 提供Oct 19, 2019
Good course to understand the foundations of big data using good examples and real life problems.
由 GT 提供Nov 4, 2019
I learned so much. I intended to continual review the entire material in this course. Thanks All.
由 VD 提供Jan 12, 2020
Very well designed course for beginners and also a review for the intermediate and advanced.
由 LR 提供Mar 28, 2020
Excellent course for big data analysis and concepts. I highly recommend this course.
由 AU 提供Aug 9, 2019
Best course for learning the basic concept about big data and SQL.
由 TM 提供Mar 4, 2020
A great course to build the basis for dealing with Big Data!
由 FD 提供Nov 3, 2019
Excellent class, earned a lot from the lecturer. Thank you.
由 DM 提供Nov 22, 2019
Good videos and background info for database uses.
關於 Modern Big Data Analysis with SQL 專項課程
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.
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What are the hardware and software requirements for the exercise environment?
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work) • 64-bit operating system (32-bit operating systems will not work) • 8 GB RAM or more • 25GB free disk space or more • Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled; on Windows and Linux computers, you might need to enable it in the BIOS) • For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)
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