Teradata SQL for Data Science and Data Analytics

Explore Teradata as a company and its core tools and utilities that integrate with the Teradata database, and understand the ecosystem for certification paths beyond SQL.

Explore Teradata Corporation, the creator of the Teradata database and an enterprise analytics platform provider. Learn how data warehousing enables analytics across software, hardware, and consulting services.

Discover Teradata Vantage, the integrated data warehouse that unifies SQL relational data with Python and R, simplifying cross-tool analytics across cloud or on-prem deployments.

Learn about Teradata query submitting tools, including Territory Studio, Territory Studio Express, SQL Assistant, and B.tech, and why Data Studio is the recommended tool for data science and analytics.

Explore Teradata load and unload utilities, including fast load, fast export, multi load, and TPT, to move data efficiently with high performance between files and Teradata tables.

Explore Teradata Viewpoint and administration tools, including Teradata Studio and data mover, to monitor CPU usage, queries, and user activity, and manage roles and workload definitions.

Learn how to install a Teradata database in an enterprise setup using Linux, VirtualBox, Vantage Express, and Studio Express, and connect via ODBC or JDBC with Territory Studio.

Install Teradata on Windows using VirtualBox and Vantage Express, then install Teradata Studio and connect to the database with Data Studio Express, verifying with a simple select date.

Install Teradata on mac by setting up VirtualBox, downloading Vantage Express and Teradata Studio for Mac, and connecting host and guest via Teradata Studio.

Navigate installation issues for Teradata SQL for data science and analytics by checking steps, using the Q&A section, and posting issues to receive help and grow a shared knowledge pool.

Discover the benefits and features of Teradata Studio and customize its interface to feel comfortable using it throughout the course and use it to its fullest capacity.

Discover how Mac users can follow Teradata studio tutorials alongside Windows, adapting command vs control shortcuts, preferences, and templates to keep the workflow consistent.

Start your virtual machine and Teradata Studio, create a Teradata connection with JDBC, specify the server address and authentication, set transaction mode to tera, then test the connection.

Overview of Teradata Studio modules, including data source explorer, project explorer, SQL editor, and result set viewer; learn to run queries with F5 and manage perspectives.

Learn to customize the Teradata SQL interface and result set viewer by adjusting fonts, colors, and window layouts; tailor row limits, headers, and alternate row colors, and restore defaults.

Explore how to customize the history view in Teradata SQL, restore the window, select history columns, view SQL statements, results, timestamps, elapsed time, and notes.

Explore the data source explorer in Teradata data tools, viewing DDL for objects such as databases and users. Customize what the explorer shows via window preferences, including indexes and macros.

Organize and save sql files using Teradata Studio’s project explorer, create or select projects, save changes, and export results or files to the desktop in csv or excel formats.

Explore Teradata Studio's features, including SQL code assist with database object suggestions, reusable templates via Ctrl+Space, customizable editor templates, and a GUI query builder for visual joins and SQL creation.

Trace the relational model and algebra, define data as tuples and relations, and learn primary keys, foreign keys, normalization and normal forms, plus sql origins and execution plans driving rdbms.

Discover how data from sales, employees, and customers becomes meaningful through intelligence—business intelligence, artificial intelligence, and data visualizations—driving information and guiding data engineering and data science roles.

Explore the main categories of SQL statements: data control language, data definition language, data manipulation language, data query language, and how they're used to create, modify, and query Teradata databases.

Explore the difference between OLTP and OLAP in Teradata Vantage, highlighting ultra-fast transactional queries and longer analytical workloads suited for data warehousing.

Learn how fact tables connect to dimension tables through star and snowflake schemas, with examples of customers, products, stores, and actions, and how normalization affects joins.

Learn to distinguish structured data from unstructured and semi-structured data, using predefined models, text files, and bank statements, and see how relational data fits as a structured subset.

Explore database objects such as tables, views, users, and databases, and learn ddl statements to create them, with a project to design a multi-table database for heavy analytics.

Explore Teradata database objects—from databases and users to indexes, macros, stored procedures, and UDFs—and learn their definitions saved in the data dictionary.

Practice creating database objects by provisioning a chess database with ten gigabytes of permanent space and as much spool and temporary space as possible, using Teradata Studio templates and syntax.

Create the chess database under a parent DVC database, assign permanent size and optional temporary space, and review DDL definitions and disaster recovery options; no indexes or tables yet.

Learn to create tables in Teradata SQL using templates, copying from source tables or creating from queries, with data or with no data, and drop and delete operations.

Learn to create a Teradata table from scratch, define table and column attributes, and review disaster recovery and performance options like fallback, journals, and data block size.

Examine Teradata data types—from fixed and variable character strings to numeric, date and time, and large objects—then practice table creation, column attributes, and data insertion in a hands-on lab.

Explore Teradata column attributes such as not null, defaults, format, uppercase, case specific behavior, and compression, then understand primary and secondary indexes with hashing and unique vs non-unique keys.

Explore Teradata temporary tables: derived, volatile, and global types. Learn how session-local derived and volatile tables compare to globally defined temporary tables with on commit options and data dictionary behavior.

Create three tables—players, countries, and games—using consistent column names, no nulls, uppercase rules, default attributes, and primary indexes with defined data types for Teradata data science.

Create and define Teradata chess tables, including players and countries, with not null constraints, primary indexes, and proper handling of keyword title; save the project.

Explore data manipulation language basics with select statements for reading data, and inserts, updates, and deletes for writing data, as you populate the chess database through hands-on SQL practice.

Learn to insert, update, and delete data in Teradata SQL with practical table examples, including values, current timestamp and select-based inserts, and safe updating and deleting.

Practice inserting data into the chess database by populating the players, countries, and games tables using insert statements or fast load, with Excel tools.

Explore three data loading methods for your Teradata SQL project: fast load, insert statements, and loading from a csv file into the players, countries, and games tables.

Explore select statements in Teradata SQL for data science, covering select *, distinct, column aliases, order by (ascending and descending), and where filters with and/or operators.

Learn to filter data using logical expressions in teradata sql, including >, >=, !=, in, between, and null handling; master like patterns with ampersand and underscore and case sensitivity.

Learn pattern matching in Teradata SQL by using escape characters to treat percent and underscore as literals in queries against game and players tables.

Explore how to use sample and top in Teradata SQL to fetch limited rows, including sample randomized allocation and top N, top N percent, and with ties.

Explore how SQL joins combine data from multiple tables by matching common columns such as country code, using inner, outer, and cross joins to shape result sets.

Master aggregate operators like count, min, max, average, and sum, while nulls are ignored; group by creates per-country insights and clarifies where and having filters.

Learn ordered analytical functions like rank and row_number, using over partitions and qualify filters to rank players by rating across countries, plus guidance on where and having clauses.

Explore set operators that combine rows from multiple select statements, including union, union all, intersect, except, and minus. Learn duplicates handling and practical examples with the players and archived tables.

Explore Teradata SQL string functions, including type, concat, substring and substr, trim, upper and lower, index, length, translate, and replace, with practical data-shaping examples.

Learn conditional processing in SQL using valued and searched case expressions, plus coalesce and nullif as case family helpers, to map titles GM, IM, FM.

Learn to use cast for data type conversions in teradata sql, converting strings to integers, decimals, and dates, and handling date formats and current timestamp conversions.

Explore date functions in Teradata SQL, including casting strings to dates, using to_date and cast, formatting dates, applying interval arithmetic, and extracting year, month, and day from date fields.

Explore time functions in Teradata SQL, handling time data types (hour, minute, second) with timestamp six precision, converting to time, extracting components, and adding intervals across time zones.

Learn the timestamp data type and functions in Teradata SQL, including casting to timestamp six, viewing current timestamp with time zone, and extracting year, month, day, hour, minute, and second.

Teradata macros store pre-written sequel and accept inputs to run queries faster, covering creation, execution, replacement, and dropping, plus the single-statement constraint and DBC metadata checks.

Learn to create and use Teradata SQL macros, search for tables and columns with patterns, manage macros in the data dictionary, and define macro inputs and syntax.

Develop a final project query to compute chess standings by event id, listing players' first names, last names, country, and total score, with tied rankings and half point from draws.

Compute total scores by summing white and black game results with case expressions and unions, then join players to show event id, first name, last name, and country in rankings.

Apply your Teradata SQL skills to personal finance by building financial tables, uploading bank statements, and gaining insights into spending categories and Amazon shopping.