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Managing Relational Databases
Akamai Customer Consulting and Support,
Students will learn about the structure and design of relational databases including primary and foreign key fields, one-to-many and one-to-one relationships. Students will learn about the Structured Query Language (SQL) and use SQL to examine the database structure. They will also learn to create and manage databases, tables, and records. The focus of the course is on data analysis. Students will start with basic SQL queries then learn to add conditional statements, and logical, comparison and arithmetic operators. Students will learn to query for a range of values, and to use pattern matching and regular expressions. Then they will progress to using multiple conditions, and complex criteria, adding functions to create calculated fields, retrieve unique records and aggregate data. Then students will learn to query multiple tables using joins, creating complex queries using subqueries, nested subqueries, and subqueries in the WHERE and FROM clauses. Students will use SQL to control the output of data including parsing text and numbers, grouping results and using ROLLUP. Students will perform labs that give practical experience and then they will complete a capstone project to demonstrate mastery of course objectives.
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Rating | Not enough ratings |
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Length | 5 weeks |
Effort | 4 weeks of study, 8hours/week |
Starts | Jul 3 (earlier today) |
Cost | $49 |
From | Akamai Technologies, Inc. via Coursera |
Instructor | Shadow Farrell |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science IT & Networking |
Tags | Data Science Data Analysis Information Technology Data Management |
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Rating | Not enough ratings |
---|---|
Length | 5 weeks |
Effort | 4 weeks of study, 8hours/week |
Starts | Jul 3 (earlier today) |
Cost | $49 |
From | Akamai Technologies, Inc. via Coursera |
Instructor | Shadow Farrell |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science IT & Networking |
Tags | Data Science Data Analysis Information Technology Data Management |
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