Book Image

Teradata Cookbook

By : Abhinav Khandelwal, Viswanath Kasi, Rajsekhar Bhamidipati
Book Image

Teradata Cookbook

By: Abhinav Khandelwal, Viswanath Kasi, Rajsekhar Bhamidipati

Overview of this book

Teradata is an enterprise software company that develops and sells its eponymous relational database management system (RDBMS), which is considered to be a leading data warehousing solutions and provides data management solutions for analytics. This book will help you get all the practical information you need for the creation and implementation of your data warehousing solution using Teradata. The book begins with recipes on quickly setting up a development environment so you can work with different types of data structuring and manipulation function. You will tackle all problems related to efficient querying, stored procedure searching, and navigation techniques. Additionally, you’ll master various administrative tasks such as user and security management, workload management, high availability, performance tuning, and monitoring. This book is designed to take you through the best practices of performing the real daily tasks of a Teradata DBA, and will help you tackle any problem you might encounter in the process.
Table of Contents (19 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Exploring ordered analytic functions


The Online Analytical Processing (OLAP) function, according to Wikipedia, is used to analyze multi-dimensional analytical queries quickly and efficiently. OLAP is part of the broader category of business intelligence, which also encompasses relational reporting and data mining. The typical applications of OLAP are business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, financial reporting, and similar areas.

The term OLAP was created as a slight modification of the traditional database term OLTP (Online Transaction Processing). Databases configured for OLAP use a multidimensional data model, allowing for complex analytical and ad hoc queries with a rapid execution time.

Like traditional aggregate functions, window aggregate functions operate on groups of rows and permit the qualification and filtering of the group result. Unlike aggregations, OLAP functions also return individual detail...