LearnQuest
Teradata: Improving Analysis and Storage
LearnQuest

Teradata: Improving Analysis and Storage

Eric Grose

Instructor: Eric Grose

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

9 hours to complete
3 weeks at 3 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

Details to know

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Recently updated!

July 2024

Assessments

11 assignments

Taught in English

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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.
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There are 3 modules in this course

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 videos4 readings4 assignments1 discussion prompt2 plugins

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 videos3 readings3 assignments1 discussion prompt1 plugin

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.

What's included

11 videos2 readings4 assignments1 discussion prompt

Instructor

Eric Grose
LearnQuest
3 Courses106 learners

Offered by

LearnQuest

Recommended if you're interested in Data Analysis

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