Data Management Solutions Using SAS Hash Table Operations
Data Management Solutions Using SAS Hash Table Operations

Author: Paul Dorfman

Publisher:

Published: 2018-06

Total Pages: 400

ISBN-13: 9781629601434

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Hash tables can do a lot more than you might think! Data Management Solutions Using SAS® Hash Table Operations: A Business Intelligence Case Study concentrates on solving your challenging data management and analysis problems via the power of the SAS hash object, whose environment and tools make it possible to create complete dynamic solutions. To this end, this book provides an in-depth overview of the hash table as an in-memory database with the CRUD (Create, Retrieve, Update, Delete) cycle rendered by the hash object tools. By using this concept and focusing on real-world problems exemplified by sports data sets and statistics, this book seeks to help you take advantage of the hash object productively, in particular, but not limited to, the following tasks: select proper hash tools to perform hash table operations use proper hash table operations to support specific data management tasks use the dynamic, run-time nature of hash object programming understand the algorithmic principles behind hash table data look-up, retrieval, and aggregation learn how to perform data aggregation, for which the hash object is exceptionally well suited manage the hash table memory footprint, especially when processing big data use hash object techniques for other data processing tasks, such as filtering, combining, splitting, sorting, and unduplicating. Using this book, you will be able to answer your toughest questions quickly and in the most efficient way possible!

Data Management Solutions Using SAS Hash Table Operations
Data Management Solutions Using SAS Hash Table Operations

Author: Paul Dorfman

Publisher:

Published: 2019-08-16

Total Pages: 400

ISBN-13: 9781642953558

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Hash tables can do a lot more than you might think! Data Management Solutions Using SAS Hash Table Operations: A Business Intelligence Case Study concentrates on solving your challenging data management and analysis problems via the power of the SAS hash object, whose environment and tools make it possible to create complete dynamic solutions. To this end, this book provides an in-depth overview of the hash table as an in-memory database with the CRUD (Create, Retrieve, Update, Delete) cycle rendered by the hash object tools. By using this concept and focusing on real-world problems exemplified by sports data sets and statistics, this book seeks to help you take advantage of the hash object productively, in particular, but not limited to, the following tasks: select proper hash tools to perform hash table operations use proper hash table operations to support specific data management tasks use the dynamic, run-time nature of hash object programming understand the algorithmic principles behind hash table data look-up, retrieval, and aggregation learn how to perform data aggregation, for which the hash object is exceptionally well suited manage the hash table memory footprint, especially when processing big data use hash object techniques for other data processing tasks, such as filtering, combining, splitting, sorting, and unduplicating. Using this book, you will be able to answer your toughest questions quickly and in the most efficient way possible!

Data Management Solutions Using SAS Hash Table Operations
Data Management Solutions Using SAS Hash Table Operations

Author: Paul Dorfman

Publisher: SAS Institute

Published: 2018-07-09

Total Pages: 400

ISBN-13: 1635260590

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Hash tables can do a lot more than you might think! Data Management Solutions Using SAS Hash Table Operations: A Business Intelligence Case Study concentrates on solving your challenging data management and analysis problems via the power of the SAS hash object, whose environment and tools make it possible to create complete dynamic solutions. To this end, this book provides an in-depth overview of the hash table as an in-memory database with the CRUD (Create, Retrieve, Update, Delete) cycle rendered by the hash object tools. By using this concept and focusing on real-world problems exemplified by sports data sets and statistics, this book seeks to help you take advantage of the hash object productively, in particular, but not limited to, the following tasks: select proper hash tools to perform hash table operations use proper hash table operations to support specific data management tasks use the dynamic, run-time nature of hash object programming understand the algorithmic principles behind hash table data look-up, retrieval, and aggregation learn how to perform data aggregation, for which the hash object is exceptionally well suited manage the hash table memory footprint, especially when processing big data use hash object techniques for other data processing tasks, such as filtering, combining, splitting, sorting, and unduplicating. Using this book, you will be able to answer your toughest questions quickly and in the most efficient way possible!

SAS Data Integration Studio 3.4
SAS Data Integration Studio 3.4

Author: SAS Institute

Publisher: Sas Inst

Published: 2007

Total Pages: 393

ISBN-13: 9781599941981

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This manual is a task-oriented introduction to the main features of SAS Data Integration Studio. SAS Data Integration Studio is a visual design tool that enables you to consolidate and manage enterprise data from a variety of source systems, applications, and technologies. The audience for this manual is users who are responsible for data integration and who have a working knowledge of Base SAS software. This title is also available online.

Combining and Modifying SAS Data Sets
Combining and Modifying SAS Data Sets

Author: Michele M. Burlew

Publisher:

Published: 2019-08-16

Total Pages: 332

ISBN-13: 9781642953077

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Building on the popularity of the first edition, Michele Burlew has revised this popular examples book to include expanded content and new features of SAS software. Completely updated for SAS 9.2, Combining and Modifying SAS Data Sets: Examples, Second Edition, presents examples that show solutions to common programming tasks that involve combining, modifying, and reshaping data sets. Expanded examples demonstrate how to combine data sets vertically and horizontally; retrieve data from lookup tables; modify and update data sets; combine summary and detail data sets; reshape and transpose observations in a data set; and manipulate data in a data set with utilities and functions. The tools used to combine and modify data sets include the SET, MERGE, MODIFY, and UPDATE statements in the DATA step; joins and set operators in PROC SQL; BY-group processing; indexes; hash objects in the DATA step; the use of PROC FORMAT and hash tables as table lookups; and generation data sets. Unique features of this book include the following: Examples are grouped by task, not by code, so you can easily find a solution to a particular task; alternative solutions are presented in addition to the main examples; most examples that combine and modify data sets include both a DATA step and a PROC SQL solution; many examples include a "Closer Look" section that describes in-depth how the example helps you complete the task; and each example stands on its own so you do not need to read the book from beginning to end. Designed for SAS programmers at all levels, this examples book will help simplify the challenging task of combining and modifying data sets.

Data Management with SAS
Data Management with SAS

Author:

Publisher:

Published: 2019-06-21

Total Pages: 88

ISBN-13: 9781642954814

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Data may be the most valuable resource that your organization owns. None of the promise of AI is possible without the ability to access, integrate, and transform data. SAS is intent on fundamentally changing the way our customers perform data management because changes in consumer expectations, and technology that drive them, continue to evolve at an incredible rate. SAS offers many different data management solutions to handle and protect your data. The papers included in this special collection demonstrates the latest tools and techniques that can benefit your data analysis. Also available free as a PDF from sas.com/books.

A Handbook of Statistical Graphics Using SAS ODS
A Handbook of Statistical Graphics Using SAS ODS

Author: Geoff Der

Publisher: CRC Press

Published: 2014-08-15

Total Pages: 250

ISBN-13: 1466599030

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Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains how to implement the methods using SAS 9.4. The handbook shows how to use SAS to create many types of statistical graphics for exploring data and diagnosing fitted models. It uses SAS’s newer ODS graphics throughout as this system offers a number of advantages, including ease of use, high quality of results, consistent appearance, and convenient semiautomatic graphs from the statistical procedures. Each chapter deals graphically with several sets of example data from a wide variety of areas, such as epidemiology, medicine, and psychology. These examples illustrate the use of graphic displays to give an overview of data, to suggest possible hypotheses for testing new data, and to interpret fitted statistical models. The SAS programs and data sets are available online.

Readings in Database Systems
Readings in Database Systems

Author: Joseph M. Hellerstein

Publisher: MIT Press

Published: 2005

Total Pages: 884

ISBN-13: 9780262693141

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The latest edition of a popular text and reference on database research, with substantial new material and revision; covers classical literature and recent hot topics. Lessons from database research have been applied in academic fields ranging from bioinformatics to next-generation Internet architecture and in industrial uses including Web-based e-commerce and search engines. The core ideas in the field have become increasingly influential. This text provides both students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area--the basic material for any DBMS professional. This fourth edition has been substantially updated and revised, with 21 of the 48 papers new to the edition, four of them published for the first time. Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system. The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems.

SAS and Open-Source Model Management
SAS and Open-Source Model Management

Author:

Publisher:

Published: 2020-07

Total Pages: 148

ISBN-13: 9781970170818

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Turn analytical models into business value and smarter decisions with this special collection of papers about SAS Model Management. Without a structured and standardized process to integrate and coordinate all the different pieces of the model life cycle, a business can experience increased costs and missed opportunities. SAS Model Management solutions enable organizations to register, test, deploy, monitor, and retrain analytical models, leveraging any available technology - including open-source models in Python, R, and TensorFlow -into a competitive advantage.