Cloudera - Foundations for Big Data Analysis with SQL
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Foundations for Big Data Analysis with SQL at Coursera Overview
Duration | 19 hours |
Start from | Start Now |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Go to Website  |
Credential | Certificate |
Foundations for Big Data Analysis with SQL at Coursera Highlights
- Requires effort of 10 hours per week
- Offered by Cloudera
- Earn a certificate upon successful completion
- Learn in-depth knowledge from senior instructor of Cloudera
Foundations for Big Data Analysis with SQL at Coursera Course details
- 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
- 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.
Foundations for Big Data Analysis with SQL at Coursera Curriculum
Week 1: Data and Databases
Welcome to the Specialization
Welcome to the Course and Week
What Is Data?
Why Organize Data?
What Does a DBMS Do?
Relational Databases and SQL
The Success of RDBMSs and SQL
Operational and Analytic Databases
Comparing Operational and Analytic DBs: SELECT Statements
Comparing Operational and Analytic DBs: DML Activity
Operational and Analytic Databases: Further Comparisons
Week 2: Relational Databases and SQL
Welcome to Week 2
Introducing Table Schemas
NULL Values
Data Types
Primary Keys
Foreign Keys
Two Strategies for Database Design
Database Normalization
Denormalization
Differences
Trade-offs
Database Transactions
ACID
Enforcing Business Rules: Constraints and Triggers
Business Rules and ACID for Analytics?
Week 3: Big Data
Welcome to Week 3 and the Three Vs of Big Data
How Big Is Big Data?
Distributed Storage
Distributed Processing
Structured Data
Unstructured Data
Semi-Structured Data
Strengths of Traditional RDBMSs
Limitations of Traditional RDBMSs
SQL and Structured Data
SQL and Semi-structured Data
SQL and Unstructured Data
Week 4: SQL Tools for Big Data Analysis
Welcome to Week 4
Big Data Analytic Databases (Data Warehouses)
NoSQL: Operational, Unstructured and Semi-structured
Non-transactional, Structured Systems
Big Data ACID-Compliant RDBMSs
Search Engines
Challenges
What We Keep
What We Give Up
What We Add
Where to Store Big Data
Coupling of Data and Metadata
Week 5: Introduction to the Hands-On Environment
Welcome to Week 5
Apache Hive
Apache Impala
Exploring Structured Data in Hue
Welcome to the Honors Track
Honors Track Conclusion
Foundations for Big Data Analysis with SQL at Coursera Entry Requirements
- 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)
- Not mentioned
Foundations for Big Data Analysis with SQL at Coursera Admission Process
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