Big Data Analysis Using SQL
Big Data Analysis Using SQL
Big Data has now become an irreplaceable factor in today’s life. The rising demand for integrating Data Science and Big Data into business has made a significant mark in the global job market resulting in organizations looking out for skilled professionals to take up challenging job roles. The Data Science and Big Data Analytics course in Dubai offers fundamental training to enable professionals to leverage their knowledge of Big Data and Analytics.
Course Outcome
Successful completion of the Data Science and Big Data Analytics course will help you to:
- Gain a deep understanding of Data Science and Data Analytics concepts
- Understand basic and advanced analytic methods
- Apply appropriate analytic techniques and tools to analyze big data
- Create statistical models, and identify insights
- Manage a data analytics project through the entire lifecycle
Target Audience
- The eager novice, seeking to grasp the fundamentals of SQL for big data analysis in Dubai.
- The seasoned data analyst, honing SQL skills to master big data complexities in Dubai's corporate landscape.
- The ambitious entrepreneur, leveraging SQL expertise for data-driven decision-making in Dubai's competitive market.
- The diligent student, immersing themselves in SQL techniques for big data analytics amidst Dubai's technological boom.
Course Content
5 modules · 55 topics01Data and databases12 topics
- Welcome to the Specialization
- Welcome to the Specialization
- 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
- Exercises
02Relational databases and SQL13 topics
- Introducing Table Schemas
- NULL Values
- NULL Values
- Primary Keys
- Foreign Keys
- Two Strategies for Database Design
- Database Normalization
- Differences
- Trade-offs
- Database Transactions
- ACID
- Business Rules and ACID for Analytics?
- Exercises
03Big data12 topics
- 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
- Exercises
04SQL tools for big data analysis9 topics
- Database schema
- Big Data Analytic Databases (Data Warehouses)
- NoSQL: Operational, Unstructured and Semi-structured
- Non-transactional, Structured Systems
- Big Data ACID-Compliant RDBMSs
- Search Engines
- Where to Store Big Data
- Coupling of Data and Metadata
- Exercises
05Introduction to the Hands-on environment9 topics
- 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
- Exercises
- Review course objectives and suggestions
Schedule Dates
4 upcoming batches| Batch Dates | Duration | Batch Options | Language | Action |
|---|---|---|---|---|
| 12 October 2026 - 16 October 2026 | 5 Days | 4 hours & 8 hours | English/ Arabic | |
| 18 January 2027 - 22 January 2027 | 5 Days | 4 hours & 8 hours | English/ Arabic | |
| 19 April 2027 - 23 April 2027 | 5 Days | 4 hours & 8 hours | English/ Arabic | |
| 19 July 2027 - 23 July 2027 | 5 Days | 4 hours & 8 hours | English/ Arabic |
Can’t find a suitable date? Request a schedule that fits your team.
Request More InformationFAQs
What is Big Data Analysis, and why is it important?
Big Data Analysis refers to the process of examining large and varied datasets to uncover hidden patterns, correlations, and insights. It’s crucial because it helps businesses make informed decisions, improve operations, and gain a competitive edge by harnessing the power of data.
Why should I choose SQL for Big Data Analysis?
SQL (Structured Query Language) is a powerful and widely used language for managing and querying relational databases, which are often the backbone of big data systems. Learning SQL enables you to manipulate and extract valuable insights from large datasets efficiently.
What will I learn in this course?
This course covers essential SQL concepts and techniques tailored for big data analysis, including data manipulation, querying large datasets, optimizing queries for performance, and understanding advanced SQL features relevant to big data environments.
Do I need any prior experience in SQL or programming to enroll in this course?
No prior experience in SQL or programming is required. This course is designed for beginners and assumes no prior knowledge. However, basic computer literacy and familiarity with data concepts would be beneficial.
Is this course suitable for experienced SQL users?
While beginners will find this course beneficial, it also caters to experienced SQL users looking to enhance their skills specifically for big data analysis. Advanced topics and techniques relevant to big data environments are covered to provide value to all skill levels.