Advanced SQL for Data Scientists

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Dan Sullivan

2:30:39

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01 - Advanced SQL techniques for data science.mp4

00:51

02 - What you should know.mp4

00:44

03 - Rules of normalization.mp4

06:19

04 - Denormalization.mp4

07:10

05 - Partitioning data.mp4

08:08

06 - Materialized views.mp4

08:16

07 - Read replicas.mp4

03:45

08 - Challenge - Design a data model for analytics.mp4

01:26

09 - Solution - Design a data model for analytics.mp4

02:28

10 - B-tree indexes.mp4

03:52

11 - Bitmap indexes.mp4

03:03

12 - Hash indexes.mp4

01:20

13 - GiST and SP-GiST indexes.mp4

01:53

14 - GIN and BRIN indexes.mp4

04:08

15 - Challenge - Choosing an optimal indexing strategy.mp4

00:37

16 - Solution - Choosing an optimal indexing strategy.mp4

01:28

17 - EXPLAIN and ANALYZE commands.mp4

07:41

18 - Generating data with generate sequence.mp4

04:16

19 - Generating time series data.mp4

06:35

20 - Analyzing a query with WHERE clauses and indexes.mp4

02:46

21 - Analyzing a query with a join.mp4

05:57

22 - Challenge - Optimize a query using an explain plan.mp4

00:34

23 - Solution - Optimize a query using an explain plan.mp4

01:39

24 - Extending SQL with user-defined functions.mp4

03:06

25 - SQL query functions.mp4

08:40

26 - Function overloading.mp4

05:41

27 - Function volatility.mp4

04:02

28 - PL Python functions.mp4

03:44

29 - Challenge - Write a user-defined function.mp4

00:34

30 - Solution - Write a user-defined function.mp4

01:35

31 - Federated queries.mp4

04:13

32 - Bloom filters.mp4

04:38

33 - Hstore for key-value pairs.mp4

06:23

34 - JSON for semi-structured data.mp4

08:34

35 - Hierarchical data and ltrees.mp4

11:59

36 - Challenge - Design a table to support unstructured data.mp4

00:33

37 - Solution - Design a table to support unstructured data.mp4

00:58

38 - Next steps.mp4

01:03

Ex Files Adv SQL Data.zip

Description

Many data scientists know how to work with SQL—the industry-standard language for data analysis. But as data sizes grow, you need to know how to do more than simply read and write from a database. This course provides a more sophisticated approach to designing data models and optimizing queries in SQL. Instructor Dan Sullivan begins with the logical and physical design of tables—with particular focus on very large databases—and then presents a deep dive review of indexes, including specialized indexes and when to use them. The next section introduces query optimization and shows how to optimize basic, multi-join, and more complex queries. The course also covers SQL extensions, including user-defined functions and specialized data types. The techniques taught here enable more efficient analysis of large data sets using SQL, statistics, and custom business logic.

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Data Science

SQL

Dan Sullivan

Instructor's Courses

Cloud and data architect with extensive experience in data architecture, data science, machine learning, stream processing, and cloud architecture. Capable of starting with vague initiatives and formulating precise objectives, strategies, and implementation plans. Regularly works with C-level and VP executives while also mentoring and coaching software engineers. Adapts well to unforeseen challenges. He is the author of the official Google Cloud study guides for the Professional Architect, Professional Data Engineer, and Associate Cloud Engineer.

Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.