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Databases, knowledge and data warehousing. Big data, DBMS and SQL and noSQL

All lectures: All lectures at the Academy of Intelligence on the discipline: databases, knowledge and data warehousing. big data, dbms and sql and nosql. These fascinating lectures provide us with the opportunity to explore the deep principles and phenomena underlying our knowledge and our desire to understand the world.
1. Database and knowledge. types of databases. relational and non relational
2. Relational DB. types of normal data. Database normalization
3. Distributed and parallel database systems
4. Graph database NEO4J create, insert, delete, edit.Cypher
5. Explaining how SQL JOIN works using the Venn diagrams as an example
6. Relationships and associations between database tables: one-to-one, one-to-many, many-to-many
7. Explaining SQL UNION using the Venn Diagrams as an Example
8. Sets, relationships, fact table in relational databases
9. Basic concepts of the relational data model
10. 4. Relational algebra - operations of union, intersection, difference, Cartesian product, selection, projection, join
11. 5. Elements of the SQL language
12. 6. Normal forms of relationships. Database Design, Types of Normal Forms
13. 7. Normal forms of higher orders
14. 8. Elements of the model "entity-relationship" ER-diagrams in databases
15. 9. Transactions and database integrity
16. 10. Transactions and concurrency
17. 11. Transactions and data recovery
18. ORM object-relational mapping,
19. MySQL InnoDB and MyISAM locks
20. Blocking (DBMS) Pessimistic Optimistic Joint Exclusive Lowercase Granular
21. questions and answers for the MYSQL interview in English
22. 1. The concept of a database
23. 2. Database structure
24. 3. Relational databases
25. 4. Conceptual database model
26. 5. Transformation of model into relational
27. A few words about database design.
28. Briefly about relational databases
29. Infologic DB design. Entities, objects, properties, relations
30. Data models Early approaches to data organization
31. Database Design
32. Storage Structures and Access Methods
33. Types of subqueries (subqueries) in SQL
34. Connections and set-theoretic relations on relations
35. Requests using connections
36. Theory of Data Synchronization in Computer Science
37. Transaction isolation level
38. index types Oracle, MySQL, PostgreSQL, MS SQL
39. Organization of client-server data synchronization for a mobile application
40. Multidimensional database technology
41. Big Data Part 1: Principles of working with big data, the MapReduce paradigm
42. Big Data Part 2: Hadoop
43. Big data. Part 3: Techniques and strategies for developing MapReduce applications
44. Big data. Part 3: Techniques and strategies for developing MapReduce applications
45. Big Data from Part 4: Hbase
46. Approaches to processing big data (Using only a detailed fact table, the method of chain interaction of documents, the relationship of tables through triggers)
47. big data
48. Big Data. Part 5.1: Hive - SQL engine over MapReduce
49. Big Data Part 5.2: Advanced hive features
50. The main functions of ETL-systems
51. Statistical analysis in PostgreSQL using PL / R
52. PostgreSQL - database overview, basics
53. Multi-user database processing systems
54. The concept and architecture of the distribution of databases. Homogeneous and heterogeneous raBD. Data Distribution Strategies in DBA
55. Distributed DBMS (RDBMS). Twelve rules of K. Data. Advantages and disadvantages of RDBMS
56. Types of data access interface (D) base
57. The concept of data storage (DS). Differences between data warehouses and databases
58. B. Inmon data warehousing classification
59. Data Warehouse Technology Solutions . Key Data Warehouse Architecture Approaches
60. Database users. Multi-user database problems. Database Administrator Functions
61. Relevance of database protection. The causes of its destruction. Legal protection of databases
62. Database recovery (using database backup, using transaction log, recovery via rollback, roll forward)
63. Database Optimization
64. Extract, transform, load (ETL)
65. Persistent data structures
66. Denormalization as a means of increasing productivity. Denormalization implementation
67. In-memory database (IMDB)
68. MVCC (multiversion concurrency control) — managing concurrent access through multiversioning
69. Problems with slow ALTER TABLE in MySQL and possible solutions
70. NoSQL (not only SQL)
71. MySQL — a database overview: basics, purpose, and capabilities
72. Ten myths about database performance
73. Multi-Range Read (MRR) optimization in MySQL
74. Codd's 12+1 rules for relational DBMS
75. ACID (Atomicity, Consistency, Isolation, Durability) — requirements for a transactional system, and BASE
76. Design and comparison of SQL and NoSQL databases
77. Parametric and zone indexes
78. Variants, capabilities, and specifics of sorting in MySQL
79. WITH queries — Common Table Expressions (CTE), hierarchical and recursive queries in SQL
80. The N + 1 selection problem in object-relational mapping (ORM)
81. Kappa architecture: subtleties and meaning
82. The need for and use of NULL in relational databases
83. Common mistakes in writing SQL queries
84. The CAP theorem and BASE architecture
85. The object-relational gap and impedance mismatch
86. SQL Antipatterns
87. The entity-relationship modeling method
88. The dimensional modeling method
89. Temporal data modeling methods
90. The Data Vault modeling method
91. Relational data warehouses: concept, construction schemas, advantages and disadvantages
92. Business Intelligence systems and data warehouses
93. The physical model of a data warehouse
94. Metadata in data warehouses
95. The physical model of a data warehouse: accounting for the impact of transactions, table denormalization
96. Designing data warehouse performance — indexing
97. Aggregation and summarization in data warehouses
98. Tuning the performance of data warehouse queries
99. Designing data cubes
100. Analytical data processing in data warehouses (analytic, statistical, ranking, window, and reporting functions)
101. Building a data warehouse model based on the corporate data model
102. Designing and developing the ETL process
103. Window functions in SQL
104. Architectures of remote databases
105. Methods and types of database optimization: denormalization, indexes, buffer tables, replication, sharding, partitioning, lazy loading, MapReduce
106. Algorithmic complexity (Big O) in SQL SELECT queries and with JOINs
107. Full-text search and the full-text index
108. Digital obsolescence
109. Data types and their indexes in DBMS (MySQL, PostgreSQL, Microsoft SQL Server, Oracle Database)
110. Ways of storing data inside relational databases
111. Streaming data: collection, storage, processing, and examples
112. Vector database — essence and examples
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