Informações sobre o curso

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Prazos flexíveis
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Nível iniciante
Aprox. 20 horas para completar
Inglês
Legendas: Inglês

O que você vai aprender

  • 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

  • Describe and choose among different data types and file formats for big data systems

Habilidades que você terá

Data ManagementDistributed File SystemsCloud StorageBig DataSQL
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível iniciante
Aprox. 20 horas para completar
Inglês
Legendas: Inglês

oferecido por

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Cloudera

Programa - O que você aprenderá com este curso

Semana
1

Semana 1

3 horas para concluir

Orientation to Data in Clusters and Cloud Storage

3 horas para concluir
7 vídeos (Total 56 mín.), 3 leituras, 1 teste
7 videos
Browsing Tables with Hue7min
Browsing Tables with SQL Utility Statements6min
Browsing HDFS with the Hue File Browser13min
Browsing HDFS from the Command Line9min
Understanding S3 and Other Cloud Storage Platforms6min
Browsing S3 Buckets from the Command Line8min
3 leituras
Review and Preparation30min
Instructions for Downloading and Installing the Exercise Environment30min
Troubleshooting the VM5min
1 exercício prático
Week 1 Graded Quiz30min
Semana
2

Semana 2

5 horas para concluir

Defining Databases, Tables, and Columns

5 horas para concluir
7 vídeos (Total 33 mín.), 12 leituras, 2 testes
7 videos
Introduction to the CREATE TABLE Statement5min
Using Different Schemas on the Same Data12min
Specifying TBLPROPERTIES2min
Examining, Modifying, and Removing Tables1min
Hive and Impala Interoperability2min
Impala Metadata Refresh3min
12 leituras
Creating Databases and Tables with Hue30min
Creating Databases and Tables with SQL15min
Permissions to Create Databases and Tables5min
The ROW FORMAT Clause25min
The STORED AS Clause15min
The LOCATION Clause20min
CREATE TABLE Shortcuts10min
Using Hive SerDes15min
Working with Unstructured and Semi-Structured Data15min
Examining Table Structure10min
Dropping Databases and Tables5min
Modifying Existing Tables35min
2 exercícios práticos
Week 2 Practice Quiz20min
Week 2 Graded Quiz30min
Semana
3

Semana 3

3 horas para concluir

Data Types and File Types

3 horas para concluir
5 vídeos (Total 14 mín.), 12 leituras, 2 testes
5 videos
Overview of Data Types1min
Choosing the Right Data Types4min
Overview of File Types3min
Choosing the Right File Types3min
12 leituras
Integer Data Types5min
Decimal Data Types10min
Character String Data Types10min
Other Data Types5min
Examining Data Types10min
Out-of-Range Values5min
Text Files5min
Avro Files5min
Parquet Files5min
ORC Files5min
Other File Types5min
Creating Tables with Avro and Parquet Files20min
2 exercícios práticos
Week 3 Practice Quiz20min
Week 3 Graded Quiz30min
Semana
4

Semana 4

5 horas para concluir

Managing Datasets in Clusters and Cloud Storage

5 horas para concluir
8 vídeos (Total 48 mín.), 13 leituras, 3 testes
8 videos
Refresh Impala's Metadata Cache after Loading Data2min
Loading Files into HDFS with Hue's Table Browser10min
Loading Files into HDFS with Hue's File Browser6min
Loading Files into HDFS from the Command Line8min
Loading Files into S3 from the Command Line10min
Using Hive and Impala to Load Data into Tables3min
Conclusion2min
13 leituras
More about HDFS Shell Commands10min
Chaining and Scripting with HDFS Commands5min
HDFS Permissions5min
Other Ways to Load Files into S35min
S3 Permissions10min
Missing Values15min
Character Sets5min
Using Sqoop to Import Data15min
More Sqoop Import Options5min
Using Sqoop to Export Data5min
SQL LOAD DATA Statements10min
SQL INSERT Statements10min
SQL INSERT ... SELECT and CTAS Statements15min
2 exercícios práticos
Week 4 Practice Quiz20min
Week 4 Graded Quiz30min

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Sobre Programa de cursos integrados 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....
Modern Big Data Analysis with SQL

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