Learn Data Analysis for Big Data. Master using SQL for data analysis on distributed big data systems

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Spécialisation Modern Big Data Analysis with SQLCloudera

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

Cloud StorageData AnalysisBig DataClouderaSQLDatabase (DBMS)Data WarehousingApache HiveApache ImpalaData ManagementDistributed File Systems

À propos de ce Spécialisation

11 199 consultations récentes

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.

Projet d'apprentissage appliqué

Each course in this Specialization includes a hands-on, peer-graded assignment. To earn the Specialization Certificate, you must successfully complete the hands-on, peer-graded assignment in each course. For this Specialization, there is not a separate Capstone Project like there is in some other Coursera Specializations.

Certificat partageable

Obtenez un Certificat lorsque vous terminez

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Planning flexible

Définissez et respectez des dates limites flexibles.

Niveau débutant

Aucune connaissance prérequise.

Approximativement 4 mois pour terminer

Rythme recommandé de 3 heures/semaine

Anglais

Sous-titres : Anglais, Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Espagnol

Certificat partageable

Obtenez un Certificat lorsque vous terminez

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Planning flexible

Définissez et respectez des dates limites flexibles.

Niveau débutant

Aucune connaissance prérequise.

Approximativement 4 mois pour terminer

Rythme recommandé de 3 heures/semaine

Anglais

Sous-titres : Anglais, Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Espagnol

Comment fonctionne la Spécialisation

Suivez les cours

Une Spécialisation Coursera est une série de cours axés sur la maîtrise d'une compétence. Pour commencer, inscrivez-vous directement à la Spécialisation ou passez en revue ses cours et choisissez celui par lequel vous souhaitez commencer. Lorsque vous vous abonnez à un cours faisant partie d'une Spécialisation, vous êtes automatiquement abonné(e) à la Spécialisation complète. Il est possible de terminer seulement un cours : vous pouvez suspendre votre formation ou résilier votre abonnement à tout moment. Rendez-vous sur votre tableau de bord d'étudiant pour suivre vos inscriptions aux cours et vos progrès.

Projet pratique

Chaque Spécialisation inclut un projet pratique. Vous devez réussir le(s) projet(s) pour terminer la Spécialisation et obtenir votre Certificat. Si la Spécialisation inclut un cours dédié au projet pratique, vous devrez terminer tous les autres cours avant de pouvoir le commencer.

Obtenir un Certificat

Lorsque vous aurez terminé tous les cours et le projet pratique, vous obtiendrez un Certificat que vous pourrez partager avec des employeurs éventuels et votre réseau professionnel.

Cette Spécialisation compte 3 cours

Cours1

Cours 1

Foundations for Big Data Analysis with SQL

4.8

étoiles

911 évaluations

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227 avis

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.

By the end of the course, you will be able to • 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; and • explore databases and tables in a big data platform. To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements: • 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)

Cours2

Cours 2

Analyzing Big Data with SQL

4.9

étoiles

436 évaluations

•

117 avis

In this course, you'll get an in-depth look at the SQL SELECT statement and its main clauses. The course focuses on big data SQL engines Apache Hive and Apache Impala, but most of the information is applicable to SQL with traditional RDBMs as well; the instructor explicitly addresses differences for MySQL and PostgreSQL.

By the end of the course, you will be able to • explore and navigate databases and tables using different tools; • understand the basics of SELECT statements; • understand how and why to filter results; • explore grouping and aggregation to answer analytic questions; • work with sorting and limiting results; and • combine multiple tables in different ways. To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements: • 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)

Cours3

Cours 3

Managing Big Data in Clusters and Cloud Storage

4.7

étoiles

239 évaluations

•

55 avis

In this course, you'll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need.

By the end of the course, you will be able to • use different tools to browse existing databases and tables in big data systems; • use different tools to explore files in distributed big data filesystems and cloud storage; • create and manage big data databases and tables using Apache Hive and Apache Impala; and • describe and choose among different data types and file formats for big data systems. To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements: • 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)

Enseignants

Glynn Durham

Ian Cook

Staff Curriculum Developer

Cloudera

21 704 étudiants

2 cours

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.

Foire Aux Questions

Quelle est la politique de remboursement ?
Si vous vous abonnez, vous bénéficiez d'une période d'essai gratuite de 7 jours, durant laquelle vous pouvez annuler votre abonnement sans pénalité. Ensuite, nous n'accordons plus de remboursements, mais vous pouvez annuler votre abonnement à tout instant. Consultez notre politique de remboursement complète.
Puis-je m'inscrire à un seul cours ?
Oui ! Pour commencer, cliquez sur la carte du cours qui vous intéresse et inscrivez-vous. Vous pouvez vous inscrire et terminer le cours pour obtenir un Certificat partageable, ou vous pouvez accéder au cours en auditeur libre afin d'en visualiser gratuitement le contenu. Si vous vous abonnez à un cours faisant partie d'une Spécialisation, vous êtes automatiquement abonné(e) à la Spécialisation complète. Visitez votre tableau de bord d'étudiant(e) pour suivre vos progrès.
Une aide financière est-elle possible ?
Oui, Coursera offre une Aide Financière aux étudiants qui n'ont pas les moyens d'acquitter les frais. Demandez-la en cliquant sur le lien Aide Financière sous le bouton S'inscrire situé à gauche. Vous devrez remplir un formulaire de demande et vous serez averti(e) si elle est acceptée. Vous devrez répéter cette procédure pour chaque cours de la Spécialisation, y compris pour le Projet Final. En savoir plus.
Puis-je suivre le cours gratuitement ?
Si vous vous inscrivez au cours, vous pouvez accéder à tous les cours de la Spécialisation et obtenir un Certificat lorsque vous terminez le travail. Si vous souhaitez seulement lire et examiner le contenu du cours, vous pouvez accéder gratuitement au cours en auditeur libre. Si vous n'avez pas les moyens d'acquitter les frais, vous pouvez faire une demande d'Aide Financière.
Ce cours est-il vraiment accessible en ligne à 100 % ? Dois-je assister à certaines activités en personne ?
Ce cours est entièrement en ligne : vous n'avez donc pas besoin de vous présenter physiquement dans une salle de classe. Vous pouvez accéder à vos vidéos de cours, lectures et devoirs en tout temps et en tout lieu, par l'intermédiaire du Web ou de votre appareil mobile.
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
Cette Spécialisation n'est pas associée à des crédits universitaires, mais certaines universités peuvent décider d'accepter des Certificats de Spécialisation pour des crédits. Vérifiez-le auprès de votre établissement pour en savoir plus.
Should I take the courses in a specific order?
Yes, the courses in this Specialization are intended to be taken in order:
Foundations for Big Data Analysis with SQL
Analyzing Big Data with SQL
Managing Big Data in Clusters and Cloud Storage
Is there a fourth course in this Specialization?
A fourth course entitled Advanced SQL for Big Data Analysis is currently under development. When it is completed, it will be added to this Specialization.
What are the hardware and software requirements for the exercise environment?
To use the hands-on environment for the courses in this Specialization, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements: • 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)
Will I earn the Cloudera Certified Associate (CCA) Data Analyst credential for completing this Specialization?
Successfully completing this Specialization confers a Coursera Specialization Certificate. This is different from the Cloudera Certified Associate (CCA) Data Analyst credential. You can earn the CCA Data Analyst credential by passing a 120-minute performance-based exam. For pricing and other details, see CCA Data Analyst. If you complete this Specialization, including the honors lessons, then you should be well prepared to take the certification exam, but we cannot guarantee that you will pass it and earn the certification credential.
What is the hands-on Capstone Project for this Specialization?
Each course in this Specialization includes a hands-on, peer-graded assignment. To earn the Specialization Certificate, you must earn the Course Certificate for each course in this Specialization. This requires that you successfully complete the hands-on, peer-graded assignment in each course. For this Specialization, there is not a separate Capstone Project like there is in some other Coursera Specializations.
I want to purchase this Specialization for my employees! How can I do that?
Please go to https://www.coursera.org/enterprise for more information, to contact Coursera, and to pick a plan. For each plan, you decide the number of courses each person can take and hand-pick the collection of courses they can choose from.

D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.