Whenever you travel, whether it's to a new destination or to your favorite vacation spot, it's nice to have a guide to assist you with planning and setting expectations. The ODS LAYOUT statement became production in SAS^® 9.4. For those intrepid programmers who used ODS LAYOUT in an earlier release of SAS^®, this paper contains tons of information about changes you need to know about. Programmers new to SAS 9.4 (or new to ODS LAYOUT) need to understand the basics. This paper reviews some common issues customers have reported to SAS Technical Support when migrating to the LAYOUT destination in SAS 9.4 and explores the basics for those who are making their first foray into the adventure that is ODS LAYOUT. This paper discusses some tips and tricks to ensure that your trip through the ODS LAYOUT statement will be a fun and rewarding one.

This presentation is an open-ended discussion about techniques for transferring data and analytical results from SAS^® to Microsoft Excel. There are some introductory comments, but this presentation does not have any set content. Instead, the topics discussed are dictated by attendee questions. Come prepared to ask and get answers to your questions. To submit your questions or suggestions for discussion in advance, go to http://support.sas.com/surveys/askvince.html.

SAS^® provides a wealth of resources for creating useful, attractive metadata tables, including PROC CONTENTS listing output (to ODS destinations), the PROC CONTENTS OUT= SAS data set, and PROC CONTENTS ODS Output Objects. This paper and presentation explores some less well-known resources to create metadata such as %SYSFUNC, PROC DATASETS, and Dictionary Tables. All these options in conjunction with the use of the ExcelXP tagset (and, new in the second maintenance release for SAS^® 9.4, the Excel tagset) enable the creation of multi-tab metadata workbooks at the click of a mouse.

This presentation focuses on building a graph template in an easy-to-follow, step-by-step manner. The presentation begins with using Graph Template Language to re-create a simple series plot, and then moves on to include a secondary y-axis as well as multiple overlaid block plots to tell a more complex and complete story than would be possible using only the SGPLOT procedure.

In previous papers I have described how many standard SAS/GRAPH^® plots can be converted easily to ODS Graphics by using simple PROC SGPLOT or SGPANEL code. SAS/GRAPH Annotate code would appear, at first sight, to be much more difficult to convert to ODS Graphics, but by using its layering features, many Annotate plots can be replicated in a more flexible and repeatable way. This paper explains how to convert many of your Annotate plots, so they can be reproduced using Base SAS^®.

This presentation explains how to use Base SAS^®9 software to create multi-sheet Excel workbooks. You learn step-by-step techniques for quickly and easily creating attractive multi-sheet Excel workbooks that contain your SAS^® output using the ExcelXP Output Delivery System (ODS) tagset. The techniques can be used regardless of the platform on which SAS software is installed. You can even use them on a mainframe! Creating and delivering your workbooks on-demand and in real time using SAS server technology is discussed. Although the title is similar to previous presentations by this author, this presentation contains new and revised material not previously presented.

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Hysteresis loops occur because of a time lag between input and output. In the pharmaceutical industry, hysteresis plots are tools to visualize the time lag between drug concentration and drug effects. Before SAS^® 9.2, SAS annotations were used to generate such plots. One of the criticisms was that SAS programmers had to write complex macros to automate the process; code management and validation tasks were not easy. With SAS 9.2, SAS programmers are able to generate such plots with ease. This paper demonstrates the generation of such plots with both Base SAS and SAS/GRAPH^® software.

As SAS^® programmers and statisticians, we rarely write programs that are run only once and then set aside. Instead, we are often asked to develop programs very early in a project, on immature data, following specifications that may be little more than a guess as to what the data is supposed to look like. These programs will then be run repeatedly on periodically updated data through the duration of the project. This paper offers strategies for not only making those programs more flexible, so they can handle some of the more commonly encountered variations in that data, but also for setting traps to identify unexpected data points that require further investigation. We will also touch upon some good programming practices that can benefit both the original programmer and others who might have to touch the code. In this paper, we will provide explicit examples of defensive coding that will aid in kicking the tires, pumping the breaks, checking your blind spots, and merging ahead for quality programming from the beginning.

This paper puts forward an approach on how to create duplicate records from one Adverse Event (AE) datum based on study treatments. In order to fulfill this task, one flag was created to check if we need to produce duplicate records depending on an existing AE in different treatment periods. If yes, then we create these duplicate records and derive AE dates for these duplicate records based on treatment periods or discontinued dates.

Today, employers and universities alike must choose the most talented individuals from a large pool. However, it is difficult to determine whether a student's A+ in English means that he or she can write as proficiently as another student who writes as a hobby. As a result, there are now dozens of ways to compare individuals to one or another spectrum. For example, the ACT and SAT enable universities to view a student's performance on a test given to all applicants in order to help determine whether they will be successful. High schools use students' GPAs in order to compare them to one another for academic opportunities. The WorkKeys Exam enables employers to rate prospective employees on their abilities to perform day-to-day business activities. Rarely do standardized tests and in-class performance get compared to each other. We used SAS^® to analyze the GPAs and WorkKeys Exam results of 285 seniors who attend the Phillip O Berry Academy. The purpose was to compare class standing to what a student can prove he knows in a standardized environment. Emphasis is on the use of PROC SQL in SAS^® 9.3 rather than DATA step processing.

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Dynamic, interactive visual displays known as dashboards are most effective when they show essential graphs, tables, statistics, and other information where data is the star. The first rule for creating an effective dashboard is to keep it simple. Striking a balance between content and style, a dashboard should be devoid of excessive clutter so as not to distract from and obscure the information displayed. The second rule of effective dashboard design involves displaying data that meets one or more business or organizational objectives. To accomplish this, the elements in a dashboard should convey a format easily understood by its intended audience. Attendees learn how to create dynamic, interactive user- and data-driven dashboards, graphical and table-driven dashboards, statistical dashboards, and drill-down dashboards with a purpose.

Learning the Graph Template Language (GTL) might seem like a daunting task. However, creating customized graphics with SAS^® is quite easy using many of the tools offered with Base SAS^® software. The point-and-click interface of ODS Graphics Designer provides us with a tool that can be used to generate highly polished graphics and to store the GTL-based code that creates them. This opens the door for users who would like to create canned graphics that can be used on various data sources, variables, and variable types. In this hands-on training, we explore the use of ODS Graphics Designer to create sophisticated graphics and to save the template code. We then discuss modifications using basic SAS macros in order to create stored graphics code that is flexible enough to accommodate a wide variety of situations.

When ODS Graphics was introduced a few years ago, it gave SAS users an array of new ways to generate graphs. One of those ways is with Statistical Graphics procedures. Now, with just a few lines of simple code, you can create a wide variety of high-quality graphs. This paper shows how to produce single-celled graphs using PROC SGPLOT and paneled graphs using PROC SGPANEL. This paper also shows how to send your graphs to different ODS destinations, how to apply ODS styles to your graphs, and how to specify properties of graphs, such as format, name, height, and width.

Axis tables, polygon plot, text plot, and more features have been added to Statistical Graphics (SG) procedures and Graph Template Language (GTL) for SAS^® 9.4. These additions are a direct result of your feedback and are designed to make creating graphs easier. Axis tables let you add multiple tables of data to your graphs and to correctly align with the axis values with the right colors for group values in your data. Text plots can have rotated and aligned text anywhere in the graph. You can overlay jittered markers on box plots, use images and font glyphs as markers, specify group attributes without making style changes, and create entirely new custom graphs using the polygon plot. All this without using the annotation facility, which is now supported both for SG procedures and GTL. This paper guides you through these exciting new features now available in SG procedures and GTL.

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No matter what type of programming you do in a pharmaceutical environment, there will eventually be a need to combine your data with a lookup table. This lookup table could be a code list for adverse events, a list of names for visits, one of your own summary data sets containing totals that you will be using to calculate percentages, or you might have your favorite way to incorporate it. This paper describes and discusses the reasons for using five different simple ways to merge data sets with lookup tables, so that when you take over the maintenance of a new program, you will be ready for anything!

This presentation teaches the audience how to use ODS Graphics. Now part of Base SAS^®, ODS Graphics are a great way to easily create clear graphics that enable any user to tell their story well. SGPLOT and SGPANEL are two of the procedures that can be used to produce powerful graphics that used to require a lot of work. The core of the procedures is explained, as well as some of the many options available. Furthermore, we explore the ways to combine the individual statements to make more complex graphics that tell the story better. Any user of Base SAS on any platform will find great value in the SAS ODS Graphics procedures.

Examples include: how to join when your data is perfect, how to join when your data does not match and you have to manipulate it in order to join, how to create a subquery, how to use a subquery.

A forest plot is a common visualization for meta-analysis. Some popular versions that use subgroups with indented text and bold fonts can seem outright daunting to create. With SAS^® 9.4, the Graph Template Language (GTL) has introduced the AXISTABLE statement, specifically designed for including text data columns into a graph. In this paper, we demonstrate the simplicity of creating various forest plots using AXISTABLE statements. Come and see how to create forest plots as clear as day!

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SAS^® provides a number of tools for creating customized professional reports. While SAS provides point-and-click interfaces through products such as SAS^® Web Report Studio, SAS^® Visual Analytics or even SAS^® Enterprise Guide^®, unfortunately, many users do not have access to the high-end tools and require customization beyond the SAS Enterprise Guide point-and-click interface. Fortunately, base SAS procedures such as the REPORT procedure, combined with graphics procedures, macros, ODS, and Annotate can be used to create very customized professional reports. When toggling together different solutions such as SAS Statistical Graphics, the REPORT procedure, ODS, and SAS/GRAPH^®, different techniques need to be used to keep the same look and feel throughout the report package. This presentation looks at solutions that can be used to keep a consistent look and feel in a report package created with different SAS products.

This paper describes the main functions of the SAS^® SG procedures and their relations. It also offers a way to create data-colored maps using these procedures. Here are the basics of the SG procedures. For a few years, the SG procedures (PROC SGPLOT, PROC SGSCATTER, PROC SGPANEL, and so on) have been part of Base SAS^® and thus available for everybody. SG originated as Statistical Graphics , but nowadays the procedures are often referred to as SAS^® ODS Graphics. With the syntax in a 1000+ page document, it is quite a challenge to start using them. Also, SAS^® Enterprise Guide^® currently has no graphics tasks that generate code for the SG procedures (except those in the statistical arena). For a long time SAS/GRAPH^® has been the vehicle for producing presentation-ready graphs of your data. In particular, the SAS users that have experience with those SAS/GRAPH procedures will hesitate to change over. But the SG procedures continue to be enhanced with new features. And, because the appearance of many elements is governed by the ODS styles, they are very well suited to provide a consistent style across all your output, text and graphics. PROC SGPLOT - PROC SGPANEL - PROC SGSCATTER: The paper first describes the basic procedures that a user will start with; PROC SGPLOT is the first place. Then the more elaborate possibilities of PROC SGPANEL and PROC SGSCATTER are described. Both these procedures can create a matrix or panel of graphs. The different goals of these two procedures will be explained: comparing a group of variables versus comparing the levels of two variables. PROC SGPLOT can create many different graphs: histograms, time series, scatterplots, and so on. PROC SGPANEL has essentially the same possibilities. The nature of PROC SGSCATTER (and the name says it already) limits it to scatter-like graphs. But many statements and options are common to lots of types of graphs. This paper groups them logically , making clear what the procedures have in common and where they differ. Related to the SG procedures are also two utilities (the Graphics Editor and the Graphics Designer), which are delivered as SAS^® Foundation applications. The paper describes the relations between these utilities and the objects they produce, and the relevant SG procedures and related utilities. Creating a map for virtually all tasks that can be performed with the well known SAS/GRAPH procedures, the counterpart in the SG procedures is easily pointed out, often with more extensive features. This is not the case for the maps produced with PROC GMAP. This paper shows the mere few steps that are necessary to convert the data sets that contain your data and your map coordinates into data sets that enable you to use the power and features of PROC SGPLOT to create your map in any projection system and any coordinate window.

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You might be familiar with or experienced in writing or running reports using PROC REPORT, PROC TABULATE, or other methods of report generation. These reporting methods are often very flexible, but they can be limited in the statistics that are available as options for inclusion in the resulting output. SAS^® provides the capability to produce a variety of statistics through Base SAS^® and SAS/STAT^® procedures by using ODS OUTPUT. These procedures include statistics from PROC CORR, PROC FREQ, and PROC UNIVARIATE in Base SAS, as well as PROC GLM, PROC LIFETEST, PROC MIXED, PROC LOGISTIC, and PROC TTEST in SAS/STAT. A number of other procedures can also produce useful ODS OUTPUT objects. Commonly requested statistics for reports include p-values, confidence intervals, and test statistics. These values can be computed with the appropriate procedure, and then use ODS OUTPUT to output the desired information to a data set and include the new information with the other data used to produce the report. Examples that demonstrate how to easily generate the desired statistics or other information and include it to produce the requested final reports are provided and discussed.

SAS^® data sets have PROC DATASETS, and SAS catalogs have PROC CATALOG. Find out what the little-known PROC CATALOG can do for you!

The task was to produce a figure legend that gave the quintile ranges of a continuous measure corresponding to each color on a five-color choropleth US map. Actually, we needed to produce the figures and associated legends for several dozen maps for several dozen different continuous measures and time periods, as well as create the associated alt text for compliance with Section 508. So, the process needed to be automated. A method was devised using PROC RANK to generate the quintiles, PROC SQL to get the data value ranges within each quintile, and PROC FORMAT (with the CNTLIN= option) to generate and store the legend labels. The resulting data files and format catalogs were used to generate both the maps (with legends) and associated alt text. Then, these processes were rolled into a macro to apply the method for the many different maps and their legends. Each part of the method is quite simple--even mundane--but together, these techniques enabled us to standardize and automate an otherwise very tedious process. The same basic strategy could be used whenever you need to dynamically generate data buckets and keep track of the bucket boundaries (for producing labels, map legends, or alt text or for benchmarking future data against the stored categories).

One of the fascinating features of SAS^® is that the software often provides multiple ways to accomplish the same task. A perfect example of this is the aggregation and summarization of data across multiple rows or BY groups of interest. These groupings can be study participants, time periods, geographical areas, or just about any type of discrete classification that you want. While many SAS programmers might be accustomed to accomplishing these aggregation tasks with PROC SUMMARY (or equivalently, PROC MEANS), PROC SQL can also do a bang-up job of aggregation--often with less code and fewer steps. This step-by-step paper explains how to use PROC SQL for a variety of summarization and aggregation tasks. It uses a series of concrete, task-oriented examples to do so. The presentation style issimilar to that used in the author's previous paper, PROC SQL for DATA Step Die-Hards.'

Do you have reports based on SAS/GRAPH^® procedures, customized with multiple GOPTIONS? Do you dream of those same graphs existing in a GOPTIONS and ANNOTATE-free world? Re-creating complex graphs using statistical graphics (SG) procedures is not only possible, but much easier than you think! Using before and after examples, I discuss how the graphs were created using the combination of Graph Template Language (GTL) and the SG procedures. This method produces graphs that are nearly indistinguishable from the original. This method simplifies the code required to make complex graphs, allows for maximum re-usability for graphics code, and enables changes to cascade to multiple reports simultaneously.

Many scientific and academic journals require that statistical tables be created in a specific format, with one of the most common formats being that of the American Psychological Association (APA). The APA publishes a substantial guide book to writing and formatting papers, including an extensive section on creating tables (Nichol 2010). However, the output generated by SAS^® procedures does not match this style. This paper discusses techniques to change the SAS procedure output to match the APA guidelines using SAS ODS (Output Delivery System).

A bubble map can be a useful tool for identifying trends and visualizing the geographic proximity and intensity of events. This session shows how to use PROC GEOCODE and PROC GMAP to turn a data set of addresses and events into a map of the United States with scaled bubbles depicting the location and intensity of the events.

As a part of regulatory compliance requirements, banks are required to submit reports based on Microsoft Excel, as per templates supplied by the regulators. This poses several challenges, including the high complexity of templates, the fact that implementation using ODS can be cumbersome, and the difficulty in keeping up with regulatory changes and supporting dynamic report content. At the same time, you need the flexibility to customize and schedule these reports as per your business requirements. This paper discusses an approach to building these reports using SAS^® XML Mapper and the Excel XML spreadsheet format. This approach provides an easy-to-use framework that can accommodate template changes from the regulators without needing to modify the code. It is implemented using SAS^® technologies, providing you the flexibility to customize to your needs. This approach also provides easy maintainability.

SAS^® formats can be used in so many different ways! Even the most basic SAS format use (modifying the way a SAS data value is displayed without changing the underlying data value) holds a variety of nifty tricks, such as nesting formats, formats that affect various style attributes, and conditional formatting. Add in picture formats, multi-label formats, using formats for data cleaning, and formats for joins and table look-ups, and we have quite a bag of tricks for the humble SAS format and PROC FORMAT, which are used to generate them. This paper describes a few very useful programming techniques that employ SAS formats. While this paper will be appropriate for the newest SAS user, it will also focus on some of the lesser-known features of formats and PROC FORMAT and so should be useful for even quite experienced users of SAS.

Can you create hundreds of great looking Microsoft Excel tables all within SAS^® and make them all Section 508 compliant at the same time? This paper examines how to use the ODS TAGSETS.EXCELXP statement and other Base SAS^® features to create fantastic looking Excel worksheet tables that are all Section 508 compliant. This paper demonstrates that there is no need for any outside intervention or pre- or post-meddling with the Excel files to make them Section 508 compliant. We do it all with simple Base SAS code.

Customer expectations are set high when Microsoft Excel and Microsoft PowerPoint are used to design reports. Using SAS^® for reporting has benefits because it generates plots directly from prepared data sets, automates the plotting process, minimizes labor-intensive manual construction using Microsoft products, and does not compromise the presentation value. SAS^® Enterprise Guide^® 5.1 has a powerful point-and-click method that is quick and easy to use. However, it is limited in its ability to customize the output to mimic manually created Microsoft graphics. This paper demonstrates why SAS Enterprise Guide is the perfect starting point for creating initial code for plots using SAS/GRAPH^® point-and-click features and how the code can be enhanced using established PROC GPLOT, ANNOTATE, and ODS options to re-create the look and feel of plots generated by Excel and PowerPoint. Examples show the generation of plots and tables using PROC TABULATE to embed the plot data into the graphical output. Also included are tips for overcoming the ODS limitation of SAS^® 9.3, which is used by SAS Enterprise Guide 5.1, to transfer the SAS graphical output to PowerPoint files. These SAS^® 9.3 tips are contrasted with the new SAS^® 9.4 ODS POWERPOINT statement that enables direct PowerPoint file creation from a SAS program.

Six Sigma is a business management strategy that seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimizing variability in manufacturing and business processes. Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified financial targets. All Six Sigma project methodologies include an extensive analysis phase in which SAS^® software can be applied. JMP^® software is widely used for Six Sigma projects. However, this paper demonstrates how Base SAS^® (and a bit of SAS/GRAPH^® and SAS/STAT^® software) can be used to address a wide variety of Six Sigma analysis tasks. The reader is assumed to have a basic knowledge of Six Sigma methodology. Therefore, the focus of the paper is the use of SAS code to produce outputs for analysis.

The report looks simple enough--a bar chart and a table, like something created with GCHART and REPORT procedures. But, there are some twists to the reporting requirements that make those procedures not quite flexible enough. The solution was to mix 'old' and 'new' DATA step-based techniques to solve the problem. Annotate datasets are used to create the bar chart and the Report Writing Interface (RWI) to create the table. Without a whole lot of additional code, an extreme amount of flexibility is gained.

Technology is always changing. To succeed in this ever-evolving landscape, organizations must embrace the change and look for ways to use it to their advantage. Even standard business tasks such as creating reports are affected by the rapid pace of technology. Reports are key to organizations and their customers. Therefore, it is imperative that organizations employ current technology to provide data in customized and meaningful reports across a variety of media. The SAS^® Output Delivery System (ODS) gives you that edge by providing tools that enable you to package, present, and deliver report data in more meaningful ways, across the most popular desktop and mobile devices. To begin, the paper illustrates how to modify styles in your reports using the ODS CSS style engine, which incorporates the use of cascading style sheets (CSS) and the ODS document object model (DOM). You also learn how you can use SAS ODS to customize and generate reports in the body of e-mail messages. Then the paper discusses methods for enhancing reports and rendering them in desktop and mobile browsers by using the HTML and HTML5 ODS destinations. To conclude, the paper demonstrates the use of selected SAS ODS destinations and features in practical, real-world applications.

It is well-known in the world of SAS^® programming that the REPORT procedure is one of the best procedures for creating dynamic reports. However, you might not realize that the compute block is where all of the action takes place! Its flexibility enables you to customize your output. This paper is a primer for using a compute block. With a compute block, you can easily change values in your output with the proper assignment statement and add text with the LINE statement. With the CALL DEFINE statement, you can adjust style attributes such as color and formatting. Through examples, you learn how to apply these techniques for use with any style of output. Understanding how to use the compute-block functionality empowers you to move from creating a simple report to creating one that is more complex and informative, yet still easy to use.

The Work library is at the core of most SAS^® programs, but programmers tend to ignore it unless something breaks. This paper first discusses the USER= system option for saving the Work files in a directory. Then, we cover a similar macro-controlled method for saving the files in your Work library, and the interaction of this method with OPTIONS NOREPLACE and the syntax check options. A number of SAS system options that help you to manage Work libraries are discussed: WORK=, WORKINIT, WORKTERM; these options might be restricted by SAS Administrators. Additional considerations in managing Work libraries are discussed: handling large files, file compression, programming style, and macro-controlled deletion of redundant files in SAS^® Enterprise Guide^®.

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The SAS^® macro processor is a powerful ally, but it requires respect. There are a myriad of macro functions available, most of which emulate DATA step functions, but some of which require special consideration to fully use their capabilities. Questions to be answered include the following: When should you protect the macro variable? During macro compilation, during macro execution? (What do those phrases even mean?) How do you know when to use which macro function? %BQUOTE(), %NBRQUOTE(), %UNQUOTE(),%SUPERQ(), and so on? What's with the %Q prefix of some macro functions? And more: %SYSFUNC(), %SYSCALL, and so on. Macro developers will no longer by daunted by the complexity of choices. With a little clarification, the power of these macro functions will open up new possibilities.

Using PROC TRANSPOSE to make wide files wider requires running separate PROC TRANSPOSE steps for each variable that you want transposed, as well as a DATA step using a MERGE statement to combine all of the transposed files. In addition, if you want the variables in a specific order, an extra DATA step is needed to rearrange the variable ordering. This paper presents a method that accomplishes the task in a simpler manner using less code and requiring fewer steps, and which runs n times faster than PROC TRANSPOSE (where n=the number of variables to be transposed).

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There have been many SAS^® Global Forum papers written about getting your data into SAS^® from Microsoft Excel and getting your data back out to Excel after using SAS to manipulate it. But sometimes you have to update Excel files with special formatting and formulas that would be too hard to replicate with Dynamic Data Exchange (DDE) or that change too often to make DDE worthwhile. But we can still use the output prowess of SAS and a sprinkling of Visual Basic for Applications (VBA) to maintain the existing formatting and formulas in your Excel file! This paper focuses on the possibilities you have in updating Excel files by reading in the data, using SAS to modify it as needed, and then using DDE and a simple Excel VBA macro to output back to Excel and use a formula while maintaining the existing formatting that is present in your source Excel file.

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Many papers have been written over the years that describe how to use Dynamic Data Exchange (DDE) to pass data from SAS^® to Excel. This presentation aims to show you how to do the same exchange with the SAS Output Delivery System (ODS) and the TEMPLATE Procedure.

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If you have not had a chance to explore SAS^® Studio yet, or if you're anxious to see what's new, this paper gives you an introduction to this new browser-based interface for SAS^® programmers and a peek at what's coming. With SAS Studio, you can access your data files, libraries, and existing programs, and you can write new programs while using SAS software behind the scenes. SAS Studio connects to a SAS server in order to process SAS programs. The SAS server can be a hosted server in a cloud environment, a server in your local environment, or a copy of SAS on your local machine. It's a comfortable environment for those used to the traditional SAS windowing environment (SAS^® Display Manager) but new features like a query window, process flow diagrams, and tasks have been added to appeal to traditional SAS^® Enterprise Guide^® users.

Managing and organizing external files and directories play an important part in our data analysis and business analytics work. A good file management system can streamline project management and file organizations and significantly improve work efficiency . Therefore, under many circumstances, it is necessary to automate and standardize the file management processes through SAS^® programming. Compared with managing SAS files via PROC DATASETS, managing external files is a much more challenging task, which requires advanced programming skills. This paper presents and discusses various methods and approaches to managing external files with SAS programming. The illustrated methods and skills can have important applications in a wide variety of analytic work fields.