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Eric Grose

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.

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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.

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Syllabus

Growing Your SQL Toolkit
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.
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Subqueries in Teradata
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.
SQL Techniques
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.

Good to know

Know what's good
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, and possible dealbreakers
Teaches how to gather requirements, a foundational aspect of data analysis
Builds on the skills and knowledge developed in the first course in the Specialization in Teradata and Data Analysis
Develops aggregate functions, normalization, and joins, which are core skills for data analysts
Builds a strong foundation for advanced data analysis techniques covered in subsequent courses
Provides hands-on practice through exercises and examples, reinforcing the concepts taught
Requires familiarity with SQL and basic data analysis concepts, making it suitable for intermediate learners

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Teradata: Improving Analysis and Storage with these activities:
Review Intro to SQL
Refresh your understanding of SQL fundamentals, including data types, operators, and basic syntax, to lay a solid foundation for this course.
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  • Read through your lecture notes or textbook chapters on SQL basics.
  • Complete practice problems or online quizzes to test your comprehension.
Refresh SQL
This activity will help you refresh your knowledge of basic SQL commands and concepts, which will be essential for success in this course.
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  • Review the SQL syntax for creating and querying tables.
  • Practice writing basic SQL queries to select, insert, update, and delete data.
Organize your notes, assignments, and quizzes from the course
This activity will help you stay organized and prepared for upcoming assessments.
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  • Create a system for organizing your notes, assignments, and quizzes.
  • Regularly review your materials to reinforce your learning.
Six other activities
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Join a study group or online forum for Teradata and data analysis
This activity will provide you with opportunities to collaborate with other learners and get help with your questions.
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  • Find a study group or online forum that is relevant to your interests.
  • Participate in discussions and ask questions.
Follow tutorials on data analysis with Teradata
This activity will help you gain hands-on experience with Teradata and data analysis techniques.
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  • Find tutorials on data analysis with Teradata.
  • Follow the steps in the tutorials to perform data analysis tasks.
Practice SQL queries on sample data
This activity will help you improve your SQL skills and gain confidence in writing queries.
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  • Find sample data sets that are relevant to your interests.
  • Write SQL queries to perform data analysis tasks on the sample data.
Mentor Junior Learners
Enhance your understanding of SQL concepts by explaining them to others. Find opportunities to mentor junior learners, answer questions in forums, or participate in study sessions.
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  • Identify opportunities to mentor junior learners in SQL.
  • Prepare materials and resources to support your mentoring sessions.
  • Facilitate discussions, answer questions, and provide guidance to mentees.
Mentor another student who is struggling with Teradata or data analysis
This activity will help you solidify your understanding of the material by explaining it to someone else.
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  • Find a student who is struggling with Teradata or data analysis.
  • Offer to help them with their work.
Create a data analysis project using Teradata
This activity will allow you to apply your skills to a real-world data analysis project.
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  • Define the scope of your project and the specific data analysis tasks you want to perform.
  • Gather data and load it into Teradata.
  • Write SQL queries to perform data analysis tasks on the data.
  • Create visualizations and reports to communicate your findings.

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