The document provides an overview of the SAS system and its components. It describes the four main data-driven tasks of data access, data management, data analysis, and data presentation. It also outlines the structure of SAS programs and data sets, and how to run and submit SAS programs. Key concepts covered include DATA and PROC steps, the SAS log and output, browsing descriptor and data portions of SAS data sets, and SAS syntax rules.
This document provides an overview of SAS (Statistical Analysis Software). It describes how SAS can handle large datasets with millions or billions of records. It also lists some common SAS modules and provides examples of DATA and PROC steps to create and process SAS datasets. Finally, it discusses the SAS programming environment and how to submit and run SAS programs.
This document provides an introduction and outline for using SAS software. It covers basic SAS windows and rules, loading and viewing data, manipulating data by selecting subsets, adding or deleting variables, sorting, summarizing data with procedures, and creating plots and outputting results to Word. Examples are provided for common procedures like SORT, MEANS, UNIVARIATE, FREQ, CORR and PLOT. Practice exercises are included to try these skills on a sample dataset.
This document provides an overview of SAS programming concepts and techniques for working with data. It discusses reading raw data using DATA steps and PROC IMPORT, selecting and transforming data, merging datasets, handling missing values, and working with dates. Functions for character manipulation, arithmetic, ranking and summarizing data are also explained. Overall, the document serves as a helpful cheat sheet for common SAS programming tasks.
This document provides instructions for inputting and managing data in SAS. It discusses creating a SAS library to organize data files. Steps are provided to manually create a SAS data set within a library and input data. Importing data from an external file is also mentioned as an alternative to manual input. The document reviews key SAS concepts like librefs and permanent vs temporary libraries.
SAS is a programming language that can be learned quickly. New users can write simple SAS programs within hours. SAS programs involve DATA and PROC steps - DATA steps input and process data, while PROC steps perform operations and output. The example SAS program reads student data from cards, assigns the values to variables in a DATA step, and prints the output in a PROC PRINT step. Additional PROC SORT and formatting options are demonstrated. The log file provides feedback on program execution and errors.
This document provides an overview of using PROC SQL in SAS Enterprise Guide 4.3. It discusses the basics of SAS Enterprise Guide 4.3, the typical SQL statement structure including common clauses, best practices for order of operations and joins, and how to use macro variables with PROC SQL. The purpose is to provide guidance for both beginners and advanced users on effectively working with PROC SQL.
- PROC TABULATE creates customized tables that display descriptive statistics from SAS data. It allows users to classify and analyze variables to produce one, two, or three-dimensional tables.
- The procedure uses CLASS, VAR, and TABLE statements to specify how variables should be classified, analyzed, and presented in the table. Common statistics like frequency, mean, sum can be calculated and displayed.
- Two-way and multi-dimensional tables can be created to examine relationships between multiple variables. Formatting and summary options provide flexibility in customizing table output.
This document provides an overview of SAS (Statistical Analysis Software). It describes how SAS can handle large datasets with millions or billions of records. It also lists some common SAS modules and provides examples of DATA and PROC steps to create and process SAS datasets. Finally, it discusses the SAS programming environment and how to submit and run SAS programs.
This document provides an introduction and outline for using SAS software. It covers basic SAS windows and rules, loading and viewing data, manipulating data by selecting subsets, adding or deleting variables, sorting, summarizing data with procedures, and creating plots and outputting results to Word. Examples are provided for common procedures like SORT, MEANS, UNIVARIATE, FREQ, CORR and PLOT. Practice exercises are included to try these skills on a sample dataset.
This document provides an overview of SAS programming concepts and techniques for working with data. It discusses reading raw data using DATA steps and PROC IMPORT, selecting and transforming data, merging datasets, handling missing values, and working with dates. Functions for character manipulation, arithmetic, ranking and summarizing data are also explained. Overall, the document serves as a helpful cheat sheet for common SAS programming tasks.
This document provides instructions for inputting and managing data in SAS. It discusses creating a SAS library to organize data files. Steps are provided to manually create a SAS data set within a library and input data. Importing data from an external file is also mentioned as an alternative to manual input. The document reviews key SAS concepts like librefs and permanent vs temporary libraries.
SAS is a programming language that can be learned quickly. New users can write simple SAS programs within hours. SAS programs involve DATA and PROC steps - DATA steps input and process data, while PROC steps perform operations and output. The example SAS program reads student data from cards, assigns the values to variables in a DATA step, and prints the output in a PROC PRINT step. Additional PROC SORT and formatting options are demonstrated. The log file provides feedback on program execution and errors.
This document provides an overview of using PROC SQL in SAS Enterprise Guide 4.3. It discusses the basics of SAS Enterprise Guide 4.3, the typical SQL statement structure including common clauses, best practices for order of operations and joins, and how to use macro variables with PROC SQL. The purpose is to provide guidance for both beginners and advanced users on effectively working with PROC SQL.
- PROC TABULATE creates customized tables that display descriptive statistics from SAS data. It allows users to classify and analyze variables to produce one, two, or three-dimensional tables.
- The procedure uses CLASS, VAR, and TABLE statements to specify how variables should be classified, analyzed, and presented in the table. Common statistics like frequency, mean, sum can be calculated and displayed.
- Two-way and multi-dimensional tables can be created to examine relationships between multiple variables. Formatting and summary options provide flexibility in customizing table output.
The document provides an overview of SAS (Statistical Analysis System) software, including its applications, components, and tutorials. Key points include:
- SAS is an integrated suite of software used for data management, reporting, analytics, and more.
- It includes applications for executive information systems, data management, reporting, statistics, forecasting, and more.
- The document provides links to tutorials on base SAS, advanced SAS, macros, and certification preparation.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
This document provides an overview of the Statistical Analysis System (SAS) software. It discusses what SAS is used for, including data management, statistical analysis, reporting, and more. It also covers SAS components and their usage, how to install and use the SAS studio interface, basic SAS syntax like variables and data sets, and common statistical procedures in SAS like PROC MEANS, PROC FREQ, and PROC UNIVARIATE to produce measures, frequencies and graphs.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
The document provides answers to common questions asked in SAS interviews or for SAS certification. Key points:
- The OUTPUT statement overrides automatic output in DATA steps and writes observations only when executed.
- The STOP statement stops processing the current DATA step and resumes after.
- DROP= in the SET statement drops variables from processing, while DROP= in the DATA statement drops them from the output dataset.
- The END= option reads the last observation of a dataset to a new dataset.
Understanding SAS Data Step Processingguest2160992
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
This document provides an introduction and overview of the SAS statistical software system. It discusses that SAS was originally developed in the 1970s for agricultural research, but is now widely used statistical software. It also summarizes the main SAS product lines, resources for learning SAS including introductory books and online documentation, and provides a basic overview of the SAS programming language including data steps, procedure steps, and accessing SAS.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
The document discusses the components and structure of SAS programs and SAS data sets. It describes how SAS programs are made up of DATA and PROC steps that are executed one at a time. SAS data sets contain a descriptor portion and a data portion, with the data portion containing the observations and variables. The document also provides examples of running SAS programs and examining the output in the log and output windows.
Aan introduction to SAS, one of the more frequently used statistical packages in business. With hands-on exercises, explore SAS's many features and learn how to import and manage datasets and and run basic statistical analyses. This is an introductory workshop appropriate for those with little or no experience with SAS.
Complete workshop materials include demo SAS programs available at http://projects.iq.harvard.edu/rtc/sas-intro
This document provides an overview of SAS data sets and SAS programming. It discusses key concepts such as the two main parts of SAS programs (DATA and PROC steps), characteristics of SAS data sets such as variables and observations, and SAS libraries which are used to store SAS data sets. The document also provides examples of basic SAS code.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
This document provides a step-by-step guide to learning SAS. It begins with an introduction to SAS and its windowing environment. Next, it discusses SAS datasets and variables, including importing data into SAS and basic procedures and functions. The document then covers combining datasets in SAS before concluding with next steps. It assumes some basic database and analytics knowledge and provides disclaimers about its intended use as a high-level summary.
Data set options allow features during dataset processing and control variables, observations, security, and attributes. They are specified in parentheses after a SAS data set name and include options like DROP, KEEP, RENAME, FIRSTOBS, and LABEL. Data set options apply to input datasets before programming statements and to output datasets after statements are processed.
The document discusses SAS training which includes:
1) Reading data from raw data files, formatting the data, and performing statistical analysis and data manipulation.
2) Combining and subsetting different data sets.
3) Processing data iteratively through loops and producing final reports.
Visualforce Remote Objects, Visual Workflow, and Developer Console received new features. Canvas Apps can now be added to page layouts and support SAML single sign-on. The Apex Flex Queue pilot allows submitting more batch jobs simultaneously. Push notifications can now be configured for Mobile SDK connected apps. Change Sets and deployment tools gained additional monitoring capabilities.
The document summarizes the three phases of the SAS data step process: compilation, execution, and output. During compilation, SAS checks syntax and identifies variable types. It creates an input buffer and program data vector (PDV). In execution, SAS reads each observation into the PDV and executes code. For output, it writes observations from the PDV to the output data set. The document provides examples to illustrate the processing and highlights what occurs in each phase.
This document summarizes information about SAS and how its legacy and computing structure compares to R. It discusses key aspects of SAS like its data structures, macro language, procedures, and output delivery system. It also provides examples of how common statistical analyses like descriptive statistics, class level processing, linear regression can be conducted in both SAS and R. The document recommends books for users to learn more about transitioning from SAS to R.
A Step-By-Step Introduction to SAS Report ProcedureYesAnalytics
The presentation of data is an essential part of every analytics project and there are number of tools within SAS that allows to create a large variety of charts, reports, and data summaries.
PROC REPORT is a particularly powerful and valuable procedure that can be used in this process. It can be used to both summarize and display data, and is highly customizable and highly flexible. It combines features of the PRINT, MEANS, and TABULATE procedures with features of the DATA step.
Here is a step by step introduction to Report Procedure which walks through the PROC REPORT statement and a few of its key options.
Sas Enterprise Guide A Revolutionary Toolsysseminar
The document describes SAS Enterprise Guide as a revolutionary tool that provides a point-and-click interface for SAS, allowing users to modify, analyze and report data without coding. It can increase efficiency, empower analysts without coding knowledge, and organize all SAS processes. The document highlights how SAS Enterprise Guide allows analysts to access and manipulate data, build queries, run analyses, and create reports and graphs through an intuitive graphical user interface without needing to learn SAS coding.
htttps://www.smartprogram.in/sas
Learn SAS programming, SAS slides, SAS tutorials, SAS certification, SAS Sample Code, SAS Macro examples,SAS video tutorials, SAS ebooks, SAS tutorials, SAS tips and Techniques, Base SAS and Advanced SAS certification, SAS interview Questions and answers, Proc SQL, SAS syntax, Advanced SAS
The document provides an overview of SAS (Statistical Analysis System) software, including its applications, components, and tutorials. Key points include:
- SAS is an integrated suite of software used for data management, reporting, analytics, and more.
- It includes applications for executive information systems, data management, reporting, statistics, forecasting, and more.
- The document provides links to tutorials on base SAS, advanced SAS, macros, and certification preparation.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
This document provides an overview of the Statistical Analysis System (SAS) software. It discusses what SAS is used for, including data management, statistical analysis, reporting, and more. It also covers SAS components and their usage, how to install and use the SAS studio interface, basic SAS syntax like variables and data sets, and common statistical procedures in SAS like PROC MEANS, PROC FREQ, and PROC UNIVARIATE to produce measures, frequencies and graphs.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
The document provides answers to common questions asked in SAS interviews or for SAS certification. Key points:
- The OUTPUT statement overrides automatic output in DATA steps and writes observations only when executed.
- The STOP statement stops processing the current DATA step and resumes after.
- DROP= in the SET statement drops variables from processing, while DROP= in the DATA statement drops them from the output dataset.
- The END= option reads the last observation of a dataset to a new dataset.
Understanding SAS Data Step Processingguest2160992
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
This document provides an introduction and overview of the SAS statistical software system. It discusses that SAS was originally developed in the 1970s for agricultural research, but is now widely used statistical software. It also summarizes the main SAS product lines, resources for learning SAS including introductory books and online documentation, and provides a basic overview of the SAS programming language including data steps, procedure steps, and accessing SAS.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
The document discusses the components and structure of SAS programs and SAS data sets. It describes how SAS programs are made up of DATA and PROC steps that are executed one at a time. SAS data sets contain a descriptor portion and a data portion, with the data portion containing the observations and variables. The document also provides examples of running SAS programs and examining the output in the log and output windows.
Aan introduction to SAS, one of the more frequently used statistical packages in business. With hands-on exercises, explore SAS's many features and learn how to import and manage datasets and and run basic statistical analyses. This is an introductory workshop appropriate for those with little or no experience with SAS.
Complete workshop materials include demo SAS programs available at http://projects.iq.harvard.edu/rtc/sas-intro
This document provides an overview of SAS data sets and SAS programming. It discusses key concepts such as the two main parts of SAS programs (DATA and PROC steps), characteristics of SAS data sets such as variables and observations, and SAS libraries which are used to store SAS data sets. The document also provides examples of basic SAS code.
Learning
Base SAS,
Advanced SAS,
Proc SQl,
ODS,
SAS in financial industry,
Clinical trials,
SAS Macros,
SAS BI,
SAS on Unix,
SAS on Mainframe,
SAS interview Questions and Answers,
SAS Tips and Techniques,
SAS Resources,
SAS Certification questions...
visit http://sastechies.blogspot.com
This document provides a step-by-step guide to learning SAS. It begins with an introduction to SAS and its windowing environment. Next, it discusses SAS datasets and variables, including importing data into SAS and basic procedures and functions. The document then covers combining datasets in SAS before concluding with next steps. It assumes some basic database and analytics knowledge and provides disclaimers about its intended use as a high-level summary.
Data set options allow features during dataset processing and control variables, observations, security, and attributes. They are specified in parentheses after a SAS data set name and include options like DROP, KEEP, RENAME, FIRSTOBS, and LABEL. Data set options apply to input datasets before programming statements and to output datasets after statements are processed.
The document discusses SAS training which includes:
1) Reading data from raw data files, formatting the data, and performing statistical analysis and data manipulation.
2) Combining and subsetting different data sets.
3) Processing data iteratively through loops and producing final reports.
Visualforce Remote Objects, Visual Workflow, and Developer Console received new features. Canvas Apps can now be added to page layouts and support SAML single sign-on. The Apex Flex Queue pilot allows submitting more batch jobs simultaneously. Push notifications can now be configured for Mobile SDK connected apps. Change Sets and deployment tools gained additional monitoring capabilities.
The document summarizes the three phases of the SAS data step process: compilation, execution, and output. During compilation, SAS checks syntax and identifies variable types. It creates an input buffer and program data vector (PDV). In execution, SAS reads each observation into the PDV and executes code. For output, it writes observations from the PDV to the output data set. The document provides examples to illustrate the processing and highlights what occurs in each phase.
This document summarizes information about SAS and how its legacy and computing structure compares to R. It discusses key aspects of SAS like its data structures, macro language, procedures, and output delivery system. It also provides examples of how common statistical analyses like descriptive statistics, class level processing, linear regression can be conducted in both SAS and R. The document recommends books for users to learn more about transitioning from SAS to R.
A Step-By-Step Introduction to SAS Report ProcedureYesAnalytics
The presentation of data is an essential part of every analytics project and there are number of tools within SAS that allows to create a large variety of charts, reports, and data summaries.
PROC REPORT is a particularly powerful and valuable procedure that can be used in this process. It can be used to both summarize and display data, and is highly customizable and highly flexible. It combines features of the PRINT, MEANS, and TABULATE procedures with features of the DATA step.
Here is a step by step introduction to Report Procedure which walks through the PROC REPORT statement and a few of its key options.
Sas Enterprise Guide A Revolutionary Toolsysseminar
The document describes SAS Enterprise Guide as a revolutionary tool that provides a point-and-click interface for SAS, allowing users to modify, analyze and report data without coding. It can increase efficiency, empower analysts without coding knowledge, and organize all SAS processes. The document highlights how SAS Enterprise Guide allows analysts to access and manipulate data, build queries, run analyses, and create reports and graphs through an intuitive graphical user interface without needing to learn SAS coding.
htttps://www.smartprogram.in/sas
Learn SAS programming, SAS slides, SAS tutorials, SAS certification, SAS Sample Code, SAS Macro examples,SAS video tutorials, SAS ebooks, SAS tutorials, SAS tips and Techniques, Base SAS and Advanced SAS certification, SAS interview Questions and answers, Proc SQL, SAS syntax, Advanced SAS
Draft sas and r and sas (may, 2018 asa meeting)Barry DeCicco
This document discusses using SAS and R together. It describes how to call R from SAS using SAS/IML, and how to call SAS from R using knitr and Markdown. Key steps include setting up SAS to use R, exporting/importing datasets between the programs, and submitting R code from SAS. Limitations include running each chunk as a separate SAS job and needing permanent files to pass data between chunks.
This presentation is about -
Overview of SAS 9 Business Intelligence Platform,
SAS Data Integration,
Study Business Intelligence,
overview Business Intelligence Information Consumers ,navigating in SAS Data Integration Studio,
For more details Visit :-
http://vibranttechnologies.co.in/sas-classes-in-mumbai.html
SQL Performance Tuning and New Features in Oracle 19cRachelBarker26
What's new in Oracle 19c (and CMiC R12) and the reporting software Jaspersoft Studios. If you are not interested in Jasper go ahead and skip to page 26. Explains how to read an execution plan and what to look for in an optimized execution plan.
SQL Server 2000 Research Series - Transact SQLJerry Yang
The document discusses key concepts in Transact-SQL including stored procedures, data types, variables, flow control statements, and functions. It covers topics such as stored procedure design, data type categories, local and global variables, conditional and looping statements, and built-in versus user-defined functions. The summary provides an overview of the document's content for technical integration and SQL training purposes.
8323 Stats - Lesson 1 - 03 Introduction To Sas 2008untellectualism
This document provides an introduction to SAS, a statistical software used for business intelligence. It discusses the main programming windows in SAS including the editor, log, and output windows. It also describes how to access and manage SAS datasets by assigning libraries, and how SAS programs are made up of data and proc steps to import data, create and analyze SAS datasets, and produce outputs.
Get up to Speed (Quick Guide to data.table in R and Pentaho PDI)Serban Tanasa
1) The document provides a quick guide to using data.table in R and Pentaho Data Integration (PDI) for fast data loading and manipulation. It discusses benchmarks showing data.table is 2-20x faster than traditional methods for reading, ordering, and transforming large data.
2) The outline discusses how to use basic data.table functions for speed gains and to overcome R's scaling limitations. It also provides a very brief overview of PDI's capabilities for Extract/Transform/Load (ETL) workflows without writing code.
3) The benchmarks section shows data.table is up to 500% faster than traditional R methods for reading large CSV files and orders of magnitude faster for sorting and aggregating
SAS Online Training Institute in Hyderabad - C-Pointcpointss
C-Point Software Solutions is a Leading Training Institute in Hyderabad. We Provide Training on SAP, SAS, Oracle E Business Suite, Informatica, OBIEE, SQL DBA, Hadoop, Cloud Computing, .Net, Testing Tools, Java, Web Designing, PHP.
MySQL is a relational database management system that is open-source and can be installed from binary packages. It is commonly used for small to medium web applications and can be managed through command line tools or graphical interfaces. SQL queries are used to manage the database structure and data.
Sas classes in mumbai
best Sas classes in mumbai with job assistance.
our features are:
expert guidance by it industry professionals
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This document discusses automating SQL Server management tasks using tools like maintenance plans, scripts, and scheduling. It recommends automating redundant tasks, backups, index maintenance, and other processes. Common automation methods include maintenance plans, T-SQL scripts, PowerShell, and scheduling tasks with SQL Agent or Windows. Notifications of issues or successes can be sent by email, alerts, or other tools. Automation simplifies management and creates repeatable, reliable processes.
Proc SQL can be used as an alternative to traditional SAS approaches like Proc Summary and data step merges for summarizing, joining, and selecting data. It allows sorting, using functions, and selecting values into macro variables in a single step. Proc SQL also supports creating indexes to improve efficiency of joins and performing many-to-many joins not possible with other methods.
The document provides an overview of SAS 9.3 and the SAS environment. It discusses what SAS is, who uses it, and its evolution. It then outlines the SAS user interface and describes the main windows, including the editor window, explorer window, log window, output window, and results window. The remainder of the document focuses on SAS programs, data sets, libraries, and procedures for working with data like PROC PRINT, PROC PLOT, PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC SQL.
This document provides 20 tips and techniques for SAS programming. It begins with tips for creating pivot tables from SAS data in Excel and using Visual Basic scripts. It then provides tips on debugging complex macros, adding operators to the macro language, and using progress bars in SAS. The document continues sharing many other tips for optimizing SAS code, such as using views to improve efficiency, finding secret SAS options, using pipes to process large files, and formatting tables to visually indicate high and low values.
The integration of SAS and Tableau can have significant business benefits. SAS and Tableau are ‘best of breed’ in their own areas: SAS in the area of Analytics and ‘Analytical Data Preparation’; Tableau in the area of data discovery, visualization and intuitive, interactive dashboarding. Consequently, it makes sense to find ways to combine these technologies to deliver an Integrated Information Framework which leverages the strengths of both solutions.
This document provides an overview and introduction to the SAS statistical software system. It discusses the origins and development of SAS, describes some of the main SAS products and their uses, and provides resources for further learning including introductory books and online materials. The document also outlines the basic structure of SAS programs including data steps, procedure steps, and accessing SAS on UNIX systems. It provides explanations of key concepts such as the structure of the data step and using the INPUT statement.
SAS is a software suite for advanced analytics. It was developed in the 1960s and includes components for statistical analysis, graphics, predictive modeling, and more. The main components of SAS are the data step for data manipulation and procedure steps for analysis. Common procedures include PROC PRINT, PROC MEANS, PROC FREQ and PROC REG. SAS programs are written in the SAS code editor and results are displayed in the SAS results window.
SecZone 2011 - Cali, Colombia
(29th Nov. 2011)
SAP (in)security:
Scrubbing SAP clean with SOAP
------
Note
------
This is a slightly updated version of my Hashdays 2011 talk.
----------
Abstract:
----------
At the heart of any large enterprise, lies a platform misunderstood and feared by all but the bravest systems administrators. Home to a wealth of information, and key to infinite wisdom. This platform is SAP. For years this system has been amongst the many "red pen" items on penetration tests and audits alike... but no more! We will no longer accept the cries of "Business critical, out-of-scope". The time for SAP has come, the cross-hairs of attackers are firmly focused on the soft underbelly that is ERM, and it's our duty to follow suit. Join me as we take the first steps into exploring SAP, extracting information and popping shells. Leave your Nessus license at the door! It's time to scrub this SAP system clean with SOAP!
----------
1. The document describes the prerequisites for setting up output in Excel using PL/SQL with XML, including designing an Excel layout, defining a stored procedure and concurrent program, and setting up required profiles.
2. It provides steps to create a PL/SQL package to generate the XML code for the Excel output, including functions to print the header, data rows, and footer.
3. Running the package main procedure will execute a cursor to fetch data and write it to the XML output, which can then be viewed in Excel when selecting that option.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
4. Components of the SAS System Base SAS Reporting and Graphics Analytical Visualization and Discovery Data Access and Management Business Solutions User Interfaces Application Development Web Enablement
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7. Turning Data into Information DATA Step SAS Data Sets Data PROC Steps Information
8. Design of the SAS System PC Workstation Servers / Midrange Mainframe Super Computer 90% independent 10% dependent MultiVendor Architecture
9. Design of the SAS System MultiEngine Architecture ™ DATA INGRES SYBASE INFORMIX ORACLE dBase Rdb DB2
15. SAS Programs DATA steps are typically used to create SAS data sets. PROC steps are typically used to process SAS data sets (that is, generate reports and graphs, edit data, and sort data). A SAS program is a sequence of steps that the user submits for execution. Raw Data DATA Step Report SAS Data Set SAS Data Set PROC Step
16. SAS Programs data work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff; run; proc means data=work.staff; class JobTitle; var Salary; run; DATA Step PROC Steps
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18. data work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff; proc means data=work.staff; class JobTitle; var Salary; run; Step Boundaries
21. OS/390 (MVS) Batch Execution Place the JCL appropriate for your location before your SAS statements. //jobname JOB accounting info,name … // EXEC SAS //SYSIN DD * data work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff; run; proc means data=work.staff; class JobTitle; var Salary; run;
25. Submitting a SAS Program When you execute a SAS program, the output generated by SAS is divided into two major parts: SAS log contains information about the processing of the SAS program, including any warning and error messages. SAS output contains reports generated by SAS procedures and DATA steps.
26. SAS Log 1 data work.staff; 2 infile ' raw-data-file '; 3 input LastName $ 1-20 FirstName $ 21-30 4 JobTitle $ 36-43 Salary 54-59; 5 run; NOTE: The infile ' raw-data-file ' is: File Name= ' raw-data-file ', RECFM=V,LRECL=256 NOTE: 18 records were read from the infile ' raw-data-file '. The minimum record length was 59. The maximum record length was 59. NOTE: The data set WORK.STAFF has 18 observations and 4 variables. 6 proc print data=work.staff; 7 run; NOTE: There were 18 observations read from the dataset WORK.STAFF. 8 proc means data=work.staff; 9 class JobTitle; 10 var Salary; 11 run; NOTE: There were 18 observations read from the dataset WORK.STAFF.
27. PROC PRINT Output The SAS System First Obs LastName Name JobTitle Salary 1 TORRES JAN Pilot 50000 2 LANGKAMM SARAH Mechanic 80000 3 SMITH MICHAEL Mechanic 40000 4 LEISTNER COLIN Mechanic 36000 5 WADE KIRSTEN Pilot 85000 6 TOMAS HARALD Pilot 105000 7 WAUGH TIM Pilot 70000 8 LEHMANN DAGMAR Mechanic 64000 9 TRETTHAHN MICHAEL Pilot 100000 10 TIETZ OTTO Pilot 45000 11 O'DONOGHUE ART Mechanic 52000 12 WALKER THOMAS Pilot 95000 13 NOROVIITA JOACHIM Mechanic 78000 14 OESTERBERG ANJA Mechanic 80000 15 LAUFFER CRAIG Mechanic 40000 16 TORR JUGDISH Pilot 45000 17 WAGSCHAL NADJA Pilot 77500 18 TOERMOEN JOCHEN Pilot 65000
28. PROC MEANS Output The SAS System The MEANS Procedure Analysis Variable : Salary N JobTitle Obs N Mean Std Dev Minimum ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Mechanic 8 8 58750.00 19151.65 36000.00 Pilot 10 10 73750.00 22523.14 45000.00 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Analysis Variable : Salary N JobTitle Obs Maximum ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ Mechanic 8 80000.00 Pilot 10 105000.00 ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
33. SAS Data Sets Data Entry External File Conversion Process SAS Data Set Descriptor Portion Data Portion Other Software Files
34. SAS Data Sets SAS data sets have a descriptor portion and a data portion. General data set information * data set name * data set label * date/time created * storage information * number of observations Information for each variable * Name * Type * Length * Position * Format * Informat * Label Descriptor Portion Data Portion
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37. Partial PROC CONTENTS Output The SAS System The CONTENTS Procedure Data Set Name: WORK.STAFF Observations: 18 Member Type: DATA Variables: 4 Engine: V8 Indexes: 0 Created: 18:09 Sunday, Observation Length: 48 July 22, 2001 Last Modified: 18:09 Sunday, Deleted Observations: 0 July 22, 2001 Protection: Compressed: NO Data Set Type: Sorted: NO Label: -----Alphabetic List of Variables and Attributes----- # Variable Type Len Pos ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 2 FirstName Char 10 28 3 JobTitle Char 8 38 1 LastName Char 20 8 4 Salary Num 8 0
38. SAS Data Sets: Data Portion Numeric values Variable names Variable values LastName FirstName JobTitle Salary TORRES JAN Pilot 50000 LANGKAMM SARAH Mechanic 80000 SMITH MICHAEL Mechanic 40000 WAGSCHAL NADJA Pilot 77500 TOERMOEN JOCHEN Pilot 65000 The data portion of a SAS data set is a rectangular table of character and/or numeric data values. Character values
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44. Missing Data Values LastName FirstName JobTitle Salary TORRES JAN Pilot 50000 LANGKAMM SARAH Mechanic 80000 SMITH MICHAEL Mechanic . WAGSCHAL NADJA Pilot 77500 TOERMOEN JOCHEN 65000 A value must exist for every variable for each observation. Missing values are valid values. A numeric missing value is displayed as a period. A character missing value is displayed as a blank.
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47. PROC PRINT Output The SAS System First Obs LastName Name JobTitle Salary 1 TORRES JAN Pilot 50000 2 LANGKAMM SARAH Mechanic 80000 3 SMITH MICHAEL Mechanic 40000 4 LEISTNER COLIN Mechanic 36000 5 WADE KIRSTEN Pilot 85000 6 TOMAS HARALD Pilot 105000 7 WAUGH TIM Pilot 70000 8 LEHMANN DAGMAR Mechanic 64000 9 TRETTHAHN MICHAEL Pilot 100000 10 TIETZ OTTO Pilot 45000 11 O'DONOGHUE ART Mechanic 52000 12 WALKER THOMAS Pilot 95000 13 NOROVIITA JOACHIM Mechanic 78000 14 OESTERBERG ANJA Mechanic 80000 15 LAUFFER CRAIG Mechanic 40000 16 TORR JUGDISH Pilot 45000 17 WAGSCHAL NADJA Pilot 77500 18 TOERMOEN JOCHEN Pilot 65000
48. SAS Data Set Terminology SAS documentation and text in the SAS windowing environment use the following terms interchangeably: SAS Data Set SAS Table Variable Column Observation Row
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56. Good spacing makes the program easier to read. Conventional Spacing data work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTaitle $ 36-43 Salary 54-59; run; proc print data=work.staff; run; proc means data=work.staff; class JobTitle; var Salary; run; SAS Syntax Rules
63. Recall a Submitted Program daat work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff run; proc means data=work.staff average max; class JobTitle; var Salary; run; data work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff; run; proc means data=work.staff mean max; class Jobtitle; var Salary; run; Program statements accumulate in a recall buffer each time you issue a SUBMIT command. Submit Number 1 Submit Number 2
64. Recall a Submitted Program Submit Number 1 Submit Number 2 Issue RECALL once. Submit number 2 statements are recalled. Issue the RECALL command once to recall the most recently submitted program. data work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff; run; proc means data=work.staff mean max; class JobTitle; var Salary; run;
65. Recall a Submitted Program Submit Number 1 Submit Number 2 daat work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff run; proc means data=work.staff average max; class JobTitle; var Salary; run; data work.staff; infile ' raw-data-file '; input LastName $ 1-20 FirstName $ 21-30 JobTitle $ 36-43 Salary 54-59; run; proc print data=work.staff; run; proc means data=work.staff mean max; class JobTitle; var Salary; run; Issue RECALL again. Issue the RECALL command again to recall submit number 1 statements.
66. Review: Save Your Program Use the FILE command with the appropriate file naming convention for your operating environment. OS/390: UNIX: Windows: FILE ' userid.prog1 .sascode( myprog )' FILE '/users/prog1/ myprog .sas' FILE 'c:orkshopinsasrog1myprog .sas'