Course Description
The "Introduction to SQL Big Data & Analytics" course is designed to provide participants with foundational knowledge and skills in SQL for big data analysis. This comprehensive program covers essential SQL concepts and techniques used to manage and analyze large datasets, enabling participants to derive valuable insights from big data.
Key Features:
- Foundations of SQL: Learn the basics of SQL, including querying, filtering, and sorting data. Understand the role of SQL in big data analytics.
- Big Data Concepts: Gain an understanding of big data technologies and frameworks such as Hadoop and Spark. Learn how SQL integrates with these technologies.
- Data Storage and Retrieval: Explore how to store and retrieve large datasets efficiently using SQL. Learn about distributed databases and data warehouses.
- Data Manipulation: Develop skills in inserting, updating, and deleting data within big data environments. Understand how to maintain data integrity and quality.
- Advanced SQL Techniques: Master advanced SQL techniques, including subqueries, joins, and window functions, to analyze complex datasets.
- Performance Optimization: Learn techniques for optimizing SQL queries to handle large volumes of data efficiently. Understand indexing, partitioning, and query optimization strategies.
- Data Visualization: Discover how to visualize big data using SQL and integrate it with visualization tools like Tableau and Power BI for better insights.
- Real-World Applications: Apply SQL skills to real-world big data scenarios, such as trend analysis, customer segmentation, and predictive analytics.
- Hands-On Practice: Engage in practical exercises and projects to apply the concepts learned. Work with big data sets to gain hands-on experience.
- Data Security and Compliance: Understand the importance of data security and compliance in big data environments. Learn best practices for data protection and privacy.
- Certification: Upon completing the course, participants receive a certification, validating their skills in SQL for big data and analytics.
This course is ideal for data analysts, data scientists, database administrators, and anyone interested in leveraging SQL for big data analysis. By completing this program, participants will be equipped with the knowledge and skills to manage and analyze large datasets effectively, driving data-driven decision-making in their organizations.
Proudly Display Your Achievement
Upon completion of your training, you will receive a personalized certificate of completion to help validate your new skills.
Step-by-Step Courses List
Module 1: What are Big Data Clusters?
- 1.1 Introduction
- 1.2 Linux, PolyBase, and Active Directory
- 1.3 Scenarios
Module 2: Big Data Cluster Architecture
- 2.1 Introduction
- 2.2 Docker
- 2.3 Kubernetes
- 2.4 Hadoop and Spark
- 2.5 Components
- 2.6 Endpoints
Module 3: Deployment of Big Data Clusters
- 3.1 Introduction
- 3.2 Install Prerequisites
- 3.3 Deploy Kubernetes
- 3.4 Deploy BDC
- 3.5 Monitor and Verify Deployment
Module 4: Loading and Querying Data in Big Data Clusters
- 4.1 Introduction
- 4.2 HDFS with Curl
- 4.3 Loading Data with T-SQL
- 4.4 Virtualizing Data
- 4.5 Restoring a Database
Module 5: Working with Spark in Big Data Clusters
- 5.1 Introduction
- 5.2 What is Spark
- 5.3 Submitting Spark Jobs
- 5.4 Running Spark Jobs via Notebooks
- 5.5 Transforming CSV
- 5.6 Spark-SQL
- 5.7 Spark to SQL ETL
Module 6: Machine Learning on Big Data Clusters
- 6.1 Introduction
- 6.2 Machine Learning Services
- 6.3 Using MLeap
- 6.4 Using Python
- 6.5 Using R
Module 7: Create and Consume Big Data Cluster Apps
- 7.1 Introduction
- 7.2 Deploying, Running, Consuming, and Monitoring an App
- 7.3 Python Example - Deploy with azdata and Monitoring
- 7.4 R Example - Deploy with VS Code and Consume with Postman
- 7.5 MLeap Example - Create a yaml file
- 7.6 SSIS Example - Implement scheduled execution of a DB backup
Module 8: Maintenance of Big Data Clusters
- 8.1 Introduction
- 8.2 Monitoring
- 8.3 Managing and Automation
- 8.4 Course Wrap Up
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What is Included
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Professional Certification
Exam-focused prep and certification guidance aligned to your learning path.
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ATS-Optimized Resume
Build a resume that highlights your new skills for recruiters and hiring systems.
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Mock Interviews
Practice real interview scenarios with structured feedback from career coaches.
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LinkedIn Optimization
Polish your profile so employers discover your credentials and achievements.
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Job Placement Support
Career guidance and placement resources on eligible programs.
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Practical Labs
Hands-on labs and exercises to reinforce concepts from your courses.
Helped me understand SQL and database management deeply.
The course gave me hands-on skills in database design and analysis.
Helped me understand SQL and database management deeply.
Helped me understand SQL and database management deeply.