Foundations for Big Data Analysis with SQL
- 4.8
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Course Summary
Learn the foundations of Big Data Analysis using SQL in this course. Gain skills in data manipulation, aggregation, and analysis using SQL and tools like Apache Spark.Key Learning Points
- Master SQL for Big Data Analysis
- Learn tools like Apache Spark for data manipulation and analysis
- Gain skills in data aggregation and analysis
Related Topics for further study
Learning Outcomes
- Master SQL for Big Data Analysis
- Gain skills in data manipulation and aggregation
- Learn to use tools like Apache Spark for data analysis
Prerequisites or good to have knowledge before taking this course
- Basic understanding of SQL
- Familiarity with data analysis concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Data Manipulation at Scale: Systems and Algorithms
- Data Analysis and Presentation Skills: the PwC Approach
Related Education Paths
Notable People in This Field
- Timothy Spann
- Doug Cutting
Related Books
Description
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.
Knowledge
- 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
Outline
- Data and Databases
- Welcome to the Specialization
- Welcome to the Course and Week 1
- 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
- Hardware Requirements for the Exercise Environment
- Data Extraction from Digital Images
- Three Notes about SQL
- References
- Data and Databases
- 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?
- Let There Be Third Normal Form
- SELECT Statements in Transactions
- Database Indexes
- Relational Databases
- 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
- What about Velocity?
- Big Data
- 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
- Open Source and Apache
- SQL Tools for Big Data Analysis
- 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
- Instructions for Downloading and Installing the Exercise Environment
- Troubleshooting the VM
- Preparation for the Quiz
- Cloudera Certified Associate Data Analyst Certification
Summary of User Reviews
Discover the foundations of big data analysis with SQL in this course from Coursera. Users have praised the course for its comprehensive coverage of SQL and its practical applications. However, some have noted that the course can be challenging for beginners.Key Aspect Users Liked About This Course
Comprehensive coverage of SQL and practical applicationsPros from User Reviews
- In-depth coverage of SQL
- Real-world examples and exercises
- Great for those seeking to expand their knowledge of big data analysis
- Well-structured and easy to follow
- Challenging and engaging
Cons from User Reviews
- Not suitable for beginners
- Requires a strong foundation in SQL
- Some users have reported technical issues with the platform
- Limited interaction with instructors
- Not enough focus on advanced data analysis techniques
Glynn Durham
4.8 Raiting
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