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Teradata: Improving Analysis and Storage

This course is part of Data Analytics with Teradata Specialization

Instructor: LearnQuest Network

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Single-Row and Multiple-Row subqueries in Teradata
Use of Aggregate Functions and JOINs in Teradata
Advanced SQL Techniques - Windowed Functions, Hierarchical Queries, and Indexes

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

14 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Data Analytics with Teradata Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

This is the second course in our Specialization in Teradata and Data Analysis. In the first course, we set up the concepts, principles, and practical basics to install software, load data, and design a logical and physical data model. In this second course, we'll improve our techniques for data analysis, with an eye on efficiency and storage for your real-world applications on the job.

In Module 1, we’ll grow your SQL Toolkit with multi-table, aggregate functions like SUM, AVG, MAX and COUNT. We’ll also expand your concept of primary and foreign keys, so you can make your first JOIN commands in SQL and define relationships between tables. Our second module is focused on SQL subqueries. We’ll start with single-row subqueries, comparing them to JOIN commands. Then we’ll examine multiple-row subqueries, which allow you to compare a value against multiple values returned from a subquery. In Module 3, we’ll examine SQL Techniques. We’ll recognize use cases and strategies to use windowed functions in SQL. We’ll define the structure of hierarchical queries in SQL. And we’ll identify for using indexes, so we can optimize our tables for data retrieval.

Module details

In this first module, we’ll look at effective requirements gathering, the use of aggregate functions, and the principles of normalization to refine our SQL querying skills. To make more valuable SQL queries, our first step is requirements gathering. Requirements Gathering involves detailed specifications about the data's format, quality, and sources. You’ll learn to prioritize data based on potential impact and engage stakeholders to help uncover essential, sometimes hidden, requirements. You will learn the most common aggregate functions available in Teradata: SUM, AVG, MAX, and COUNT. We’ll examine when we would typically use these functions, and how the output of these functions is different from traditional SQL queries. We’ll take a closer look at three levels of data normalization. Normalization reduces redundancy and ensures that each piece of data is stored precisely once, linked directly to a primary key. Finally, we’ll use SQL joins to link data across multiple tables. Using Inner Joins and left Joins which help us tailor our queries to meet specific analytical needs.

What's included

14 videos6 readings5 assignments1 discussion prompt2 plugins

14 videosTotal 54 minutes

Course Introduction5 minutes
Requirements Gathering3 minutes
Scenario: Requirements Gathering at NexaMart Coffee Bean3 minutes
Introduction to Aggregate Functions2 minutes
Normalization, Data Models, and Schema3 minutes
Aggregate functions in Teradata5 minutes
Scenario: Aggregate functions at NexaMart Coffee Bean3 minutes
Instructor Demonstration: Run queries with aggregate functions5 minutes
Table Relationships: Keys and JOINs2 minutes
JOINs in SQL3 minutes
Scenario: First Table Relationship at NexaMart Coffee Bean4 minutes
Instructor Demonstration: Run queries with JOINs8 minutes
Syntax in an Inner Join3 minutes
Growing your SQL Toolkit - Key Takeaways3 minutes

6 readingsTotal 60 minutes

Course Syllabus: Improving Analysis and Storage10 minutes
Aggregate Functions for the New User10 minutes
How to Write Aggregate functions10 minutes
Table Relationships for the New User10 minutes
Exercise Guide: How to Write Join Queries10 minutes
Key Takeaways: Growing your SQL Toolkit10 minutes

5 assignmentsTotal 110 minutes

Exam: Growing Your SQL Toolkit50 minutes
Quiz: Introduction to Aggregate Functions15 minutes
Quiz: SUM, AVG, MAX, and COUNT Functions15 minutes
Quiz: Understanding Table Relationships15 minutes
Growing Your SQL Toolkit: Knowledge Check15 minutes

1 discussion promptTotal 15 minutes

Growing your SQL Toolkit15 minutes

2 pluginsTotal 30 minutes

Software Simulation: Run queries with aggregate functions15 minutes
Queries with JOINs15 minutes

In this module, we will practice some practical applications of SQL subqueries, focusing on both single-row and multiple-row subqueries to enhance your data analysis skills. We'll start by exploring single-row subqueries, an advanced SQL technique perfect for conducting precise data checks within larger queries. You'll learn how to structure these subqueries to compare specific values against results returned by another query, which is crucial for tasks such as verifying if inventory levels meet demand or if a customer's purchase exceeds the average. Following that, we will examine multiple-row subqueries, which allow you to compare a value against multiple values returned from a subquery. This session will cover how to use SQL operators like IN, ANY, or ALL to filter and analyze data effectively. Through detailed examples and structured queries, this module will equip you with the knowledge to apply these techniques directly to real-world business intelligence scenarios, enhancing both the specificity and relevance of your data analysis.

What's included

6 videos4 readings4 assignments1 discussion prompt1 plugin

6 videosTotal 20 minutes

Single-Row Subqueries2 minutes
Scenario: Single-Row Subqueries at NexaMart Coffee Bean4 minutes
Instructor Demonstration: Run single-row subqueries4 minutes
Multiple-Row Subqueries4 minutes
Instructor Demonstration: Run a Multi-Row Subquery4 minutes
Subqueries in Teradata: Module Review2 minutes

4 readingsTotal 40 minutes

Write a Single-Row Subquery10 minutes
Single and Multi-Row Subqueries for the New User10 minutes
Exercise Guide: Multi-Row Subquery10 minutes
Subqueries in Teradata: Key Takeaways10 minutes

4 assignmentsTotal 90 minutes

Exam: Subqueries in Teradata50 minutes
Quiz: Single-Row Subqueries15 minutes
Quiz: Multiple-Row Subqueries15 minutes
Subqueries in Teradata Knowledge Check10 minutes

1 discussion promptTotal 10 minutes

Subqueries in Teradata10 minutes

1 pluginTotal 15 minutes

Software Simulation: Run single-row subqueries15 minutes

This module introduces key SQL concepts and techniques to enhance data analysis using Teradata. Window functions enable advanced data aggregation over specified ranges, allowing for dynamic time-based evaluations and facilitating calculations such as running totals, moving averages, and lagging or leading values. Hierarchical queries provide a framework for analyzing parent-child relationships within data, crucial for understanding complex structures like supply chains. This module covers the syntax and practical applications of these queries, highlighting their use in organizing and analyzing hierarchical data effectively. Finally, the module explains the importance of indexes in SQL for quicker data retrieval. Indexes prioritize frequently accessed columns, enhancing query performance and ensuring efficient data processing. These concepts collectively equip data analysts with robust tools for sophisticated data analysis and strategic decision-making.