Data Analytics with Teradata

Overview

Syllabus

Courses

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  15 hours 17 minutes

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  This course will equip learners with a comprehensive understanding of Teradata Vantage's core concepts, architecture, and data management capabilities. Instruction focuses on foundational knowledge crucial for database administrators, IT managers, and data architects. Upon completion, learners will be able to: install and configure a Teradata database, load data appropriately, perform queries using SQL commands, and use data modeling to prepare data for more advanced query operations. “Getting Started with Teradata” is the first course in our Teradata specialization, which will give you the foundational understanding and experience to begin, pivot, or advance your career in database administration, IT management, or data architecture.
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  12 hours 41 minutes

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  Building Analytics Systems is a course for professionals interested in Data Analytics with Teradata. Data Analysts taking on the Teradata tool, new students of Data Analytics, and business professionals pivoting to this field will all benefit. If you've taken "Getting Started with Teradata" and "Improving Analysis and Storage," you're ready to run with this third course in my Teradata Specialization. This course uses animated lectures, scenarios, instructor demonstrations and software simulations to strengthen your skills with Teradata as well as your understanding of how to integrate and use the growing variety of data sources. In this course, you will recognize how to connect to additional data sources; define how APIs and JSON are the pillars of enterprise data warehousing; identify how Teradata handles the common challenges of connecting with data sources; identify which columns are eligible for categorical summaries and how to interpret the output; define the importance of summary statistics for your data tables; recognize techniques on how to clean up missing, null, or incomplete data; identify how the in-database analytics provided by Teradata create data visualizations; define the process of Exploratory Data Analysis (EDA) in exploring data and testing hypotheses; Define event attribution and how it can be applied to business processes; recognize how to search for patterns within data using the nPath function; identify the process to match a session window time frame to an analysis goal; recognize how to apply aggregate functions to a sessionized dataset for advanced analytics; identify strategies to manipulate text data for analysis; practice creating grams, bigrams, and trigrams using the nGrams function; recognize the use of sentiment analysis to better understand customer needs, and define the use of the Sentiment Extractor function to analyze meaning from text data.
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  9 hours 28 minutes

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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.

Taught by

Eric Grose