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.
Ce cours fait partie de la Spécialisation Modern Big Data Analysis with SQL
Foundations for Big Data Analysis with SQL
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À propos de ce cours
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Ce que vous allez apprendre
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
Compétences que vous acquerrez
Database (DBMS)Data WarehousingData AnalysisBig DataSQL
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Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 1 sur 3 dans le
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Niveau débutant
Approx. 19 heures pour terminer
Recommandé : 10 hours/week
Anglais
Sous-titres : Anglais
Programme du cours : ce que vous apprendrez dans ce cours
2 heures pour terminer
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 heures pour terminer
11 vidéos (Total 50 min), 4 lectures, 1 quiz
11 vidéos
Welcome to the Course and Week 13 min
What Is Data?3 min
Why Organize Data?5 min
What Does a DBMS Do?5 min
Relational Databases and SQL6 min
The Success of RDBMSs and SQL4 min
Operational and Analytic Databases5 min
Comparing Operational and Analytic DBs: SELECT Statements2 min
Comparing Operational and Analytic DBs: DML Activity4 min
Operational and Analytic Databases: Further Comparisons1 min
4 lectures
Hardware Requirements for the Exercise Environment10 min
Data Extraction from Digital Images10 min
Three Notes about SQL10 min
References10 min
1 exercice pour s'entraîner
Data and Databases30 min
3 heures pour terminer
Relational Databases and SQL
3 heures pour terminer
15 vidéos (Total 80 min), 3 lectures, 1 quiz
15 vidéos
Welcome to Week 21 min
Introducing Table Schemas3 min
NULL Values3 min
Data Types3 min
Primary Keys5 min
Foreign Keys6 min
Two Strategies for Database Design3 min
Database Normalization8 min
Denormalization5 min
Differences6 min
Trade-offs4 min
Database Transactions6 min
ACID6 min
Enforcing Business Rules: Constraints and Triggers7 min
Business Rules and ACID for Analytics?6 min
3 lectures
Let There Be Third Normal Form5 min
SELECT Statements in Transactions5 min
Database Indexes30 min
1 exercice pour s'entraîner
Relational Databases30 min
2 heures pour terminer
Big Data
2 heures pour terminer
12 vidéos (Total 63 min), 1 lecture, 1 quiz
12 vidéos
How Big Is Big Data?3 min
Distributed Storage6 min
Distributed Processing9 min
Structured Data4 min
Unstructured Data4 min
Semi-Structured Data3 min
Strengths of Traditional RDBMSs4 min
Limitations of Traditional RDBMSs7 min
SQL and Structured Data5 min
SQL and Semi-structured Data4 min
SQL and Unstructured Data7 min
1 lecture
What about Velocity?15 min
1 exercice pour s'entraîner
Big Data30 min
2 heures pour terminer
SQL Tools for Big Data Analysis
2 heures pour terminer
12 vidéos (Total 53 min), 1 lecture, 1 quiz
12 vidéos
Welcome to Week 41 min
Big Data Analytic Databases (Data Warehouses)2 min
NoSQL: Operational, Unstructured and Semi-structured4 min
Non-transactional, Structured Systems2 min
Big Data ACID-Compliant RDBMSs1 min
Search Engines4 min
Challenges4 min
What We Keep3 min
What We Give Up5 min
What We Add8 min
Where to Store Big Data7 min
Coupling of Data and Metadata7 min
1 lecture
Open Source and Apache15 min
1 exercice pour s'entraîner
SQL Tools for Big Data Analysis30 min
4.8
50 avisMeilleurs avis pour Foundations for Big Data Analysis with SQL
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! :)
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
Offert par
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.
À propos du Spécialisation Modern Big Data Analysis with SQL
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.
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
Quelle est la politique de remboursement ?
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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)
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.