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.
このコースはModern Big Data Analysis with SQL の専門講座に属します。
Foundations for Big Data Analysis with SQL
提供：
このコースについて
66,904 最近の表示
学習内容
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
習得するスキル
Database (DBMS)Data WarehousingData AnalysisBig DataSQL
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における3の1コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
初級レベル
約19時間で修了
推奨：10 hours/week
英語
字幕：英語
提供：
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.
シラバス - 本コースの学習内容
2時間で修了
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.
2時間で修了
11件のビデオ （合計50分）, 4 readings, 1 quiz
11件のビデオ
Welcome to the Course and Week 13 分
What Is Data?3 分
Why Organize Data?5 分
What Does a DBMS Do?5 分
Relational Databases and SQL6 分
The Success of RDBMSs and SQL4 分
Operational and Analytic Databases5 分
Comparing Operational and Analytic DBs: SELECT Statements2 分
Comparing Operational and Analytic DBs: DML Activity4 分
Operational and Analytic Databases: Further Comparisons1 分
4件の学習用教材
Hardware Requirements for the Exercise Environment10 分
Data Extraction from Digital Images10 分
Three Notes about SQL10 分
References10 分
1の練習問題
Data and Databases30 分
3時間で修了
Relational Databases and SQL
3時間で修了
15件のビデオ （合計80分）, 3 readings, 1 quiz
15件のビデオ
Introducing Table Schemas3 分
NULL Values3 分
Data Types3 分
Primary Keys5 分
Foreign Keys6 分
Two Strategies for Database Design3 分
Database Normalization8 分
Denormalization5 分
Differences6 分
Trade-offs4 分
Database Transactions6 分
ACID6 分
Enforcing Business Rules: Constraints and Triggers7 分
Business Rules and ACID for Analytics?6 分
3件の学習用教材
Let There Be Third Normal Form5 分
SELECT Statements in Transactions5 分
Database Indexes30 分
1の練習問題
Relational Databases30 分
2時間で修了
Big Data
2時間で修了
12件のビデオ （合計63分）, 1 reading, 1 quiz
12件のビデオ
How Big Is Big Data?3 分
Distributed Storage6 分
Distributed Processing9 分
Structured Data4 分
Unstructured Data4 分
Semi-Structured Data3 分
Strengths of Traditional RDBMSs4 分
Limitations of Traditional RDBMSs7 分
SQL and Structured Data5 分
SQL and Semi-structured Data4 分
SQL and Unstructured Data7 分
1件の学習用教材
What about Velocity?15 分
1の練習問題
Big Data30 分
2時間で修了
SQL Tools for Big Data Analysis
2時間で修了
12件のビデオ （合計53分）, 1 reading, 1 quiz
12件のビデオ
Big Data Analytic Databases (Data Warehouses)2 分
NoSQL: Operational, Unstructured and Semi-structured4 分
Non-transactional, Structured Systems2 分
Big Data ACID-Compliant RDBMSs1 分
Search Engines4 分
Challenges4 分
What We Keep3 分
What We Give Up5 分
What We Add8 分
Where to Store Big Data7 分
Coupling of Data and Metadata7 分
1件の学習用教材
Open Source and Apache15 分
1の練習問題
SQL Tools for Big Data Analysis30 分
レビュー
4.8
FOUNDATIONS FOR BIG DATA ANALYSIS WITH SQL からの人気レビュー
AGによりSep 27, 2019
The course is an excellent overview of database technologies and introduction into big data. Useful also for those who already worked with a few SQL engines. MIllion thanks to the creators! :)
AEにより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
AAにより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.
SYにより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!
Modern Big Data Analysis with SQL専門講座について
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.
よくある質問
いつ講座や課題にアクセスできるようになりますか？
修了証に登録すると、すべてのビデオ、テスト、およびプログラミング課題（該当する場合）にアクセスできます。ピアレビュー課題は、セッションが開始してからのみ、提出およびレビューできます。購入せずにコースを検討することを選択する場合、特定の課題にアクセスすることはできません。
この専門講座をサブスクライブすると何を行うことができるようになりますか？
コースに登録する際、専門講座のすべてのコースにアクセスできます。コースの完了時には修了証を取得できます。電子修了証が成果のページに追加され、そこから修了証を印刷したり、LinkedInのプロフィールに追加したりできます。コースの内容の閲覧のみを希望する場合は、無料でコースを聴講できます。
返金ポリシーについて教えてください。
学資援助はありますか？
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)
さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。
