SQL & BigQuery Mastery: Techniques & interview problems (Master Data Manipulation, Performance Tuning, and Cloud Integration)

SQL & BigQuery Mastery: Techniques & interview problems course is ideal for data analysts, businessmen, students, and IT specialists who wish to enhance their SQL and Google BigQuery capabilities. This course teaches everything from the basics of using SQL and Relational databases to intermediate queries to complicated queries and even system performance tuning. It presupposes that the learner has no acquaintance with SQL or databases so that the learner can begin at the starting point.

Across its modules, you work on applied analytical tasks and a business case or project. Some of these are BigQuery basics, data manipulation, query writing, BigQuery performance optimization, BigQuery data analysis, and BigQuery data modeling, among others. Moreover, the course also discusses BigQuery and its integration with Google Cloud services, cost optimization strategies, the employment of security considerations, and live data problems in presenting the candidate for job interview solutions.

This complete course, "SQL & BigQuery Mastery: Techniques & interview problems,” is overloaded with detailed instructions from professionals, so you will develop job-oriented skills that target practical approaches. You’ll get the backing of the community in your professional development process and access to materials that assist in tuning performance and decreasing costs. I completed the course from scratch, and it seemed to be very useful and comprehensive for me, as well as for those who need a brushing up to refresh their knowledge or gain confidence with crucial data analysis and interview practice.

SQL & BigQuery Mastery: Techniques & interview problems Table of Contents:

1. What is SQL - 22:19
2. Understanding Relational Databases - 03:45
3. Overview of Database Management Systems (DBMS) - 04:45
4. Introduction to Google BigQuery - 04:41
5. BigQuery Architecture and Advantages - 04:15
6. SQL Syntax overview - 03:54
7. BigQuery Data Types - 07:52
8. Understanding Tables and Datasets in BigQuery - 02:30
9. SELECT Statements - 04:30
10. WHERE Clause for Filtering - 03:33
11. Sorting Results using ORDER BY - 02:07
12. BigQuery Specific Functions - 01:40
13. Data Loading and Exporting Techniques in BigQuery - 16:20
14. INSERT INTO Statement (adding data) - 01:58
15. UPDATE Statement (Modifying Data) - 04:23
16. DELETE Statement (Removing Data) - 01:31
17. Using aggregate functions (COUNT, SUM, AVG) - 01:17
18. Grouping Data with GROUP BY - 02:51
19. Having Clause - 03:01
20. Working with Large Datasets - 01:39
21. Inner join - 04:23
22. RIGHT_JOIN - 06:37
23. LEFT_JOIN - 01:21
24. Designing simple tables - 02:30
25. Understanding Normalization - 02:47
26. Cost Optimization Techniques - 04:42
27. Customer with no orders - 03:35
28. Big countries - 02:16
29. Subqueries and Nested Queries - 09:36
30. CROSS_JOIN - 04:36
31. OUTER_JOIN - 05:03
32. Set Operations (UNION, INTERSECT, EXCEPT) - 03:05
33. Analyzing Large Datasets - 05:03
34. Date and Time Functions - 12:06
35. Working with Strings and Text Data - 05:08
36. Handling NULL Values - 07:07
37. BigQuery Geographic Information Systems (GIS) Functions - 03:27
38. Creating and Using Views - 06:50
39. Indexes and Their Importance - 04:04
40. Stored Procedures and Functions - 04:04
41. Using BigQuery ML for Machine Learning - 09:08
42. Advanced Normalization Techniques - 07:37
43. Entity-Relationship (ER) Modeling - 05:22
44. Implementing Constraints (Primary Key, Foreign Key) - 05:33
45. BigQuery Data Transfer Service - 02:40
46. ACID Properties - 01:31
47. Understanding Transactions - 05:26
48. Data Manipulation Language (DML) Best Practices - 03:36
49. Query Optimization Techniques - 02:57
50. Cost Management and Optimization - 02:13
51. Understanding and Analyzing Query Execution Plans - 02:16
52. Index Tuning - 03:02
53. Managers with 5 direct reports - 03:10
54. People with most friends - 08:39
55. Window Functions - 07:26
56. Recursive Queries - 17:59
57. Pivoting and Unpivoting Data - 06:48
58. BigQuery Specific Query Features - 08:37
59. Backup and Recovery Strategies - 07:29
60. User Management and Access Control - 03:36
61. Monitoring and Logging - 02:20
62. Security Best Practices in BigQuery - 02:30
63. Basics of Data Warehousing - 02:45
64. ETL Processes in BigQuery - 03:34
65. OLAP vs OLTP - 02:39
66. Overview of Google Cloud Platform (GCP) - 03:00
67. Interacting with Cloud Storage - 03:26
68. Data Integration with Pub_Sub and Dataflow - 03:05
69. BigQuery and Big Data (Hadoop, Spark) - 01:33
70. Integrating BigQuery with Other Languages (Python, R) - 03:34
71. SQL with Big Data (Hadoop, Spark) - 02:39
72. Overview of NoSQL - 03:00
73. Differences Between SQL and NoSQL - 03:26
74. Introduction to NewSQL - 01:53
75. Modern Database Technologies - 02:11
76. Best Practices in Database Management - 03:53
77. Future Directions and Innovations in BigQuery - 04:08
78. Find departments top salaries - 03:39

Who is this course for?

1. Aspiring Data Analysts: Good for entry-level data analysts and those willing to master SQL and Google BigQuery skills.
2. Business Professionals: Ideal for those who believe numbers empower and should be at the center of every business.
3. Students and Educators: This book is good for learners and teachers who wish to enhance their knowledge of databases and data manipulation specifically for academic usefulness.
4. Developers and IT Professionals: Intended for developers and IT specialists who wish to enhance their skills in using filtering capabilities, ML-based queries for BigQuery, and the integration capabilities between BigQuery and other Google Cloud solutions.

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