10月 202017
 

 

“The difference between style and fashion is quality.”

-Giorgio Armani

With an out-of-the-box SAS Enterprise Guide (EG) installation, when you build a report in SAS EG it is displayed in a nice-looking default style. If you like it, you can keep it, and continue reading. If you don’t quite like it, then stop, take a deep breath, and continue reading carefully – you are about to discover a wealth of styling options available in EG. In any case, you are not bound by the default style that is set during your SAS EG installation.

Changing your SAS EG report style on the fly

Let’s say we run the following SAS program in EG:

SAS code sample to run in SAS EG
When you run a SAS Program or a Process Flow that creates an output, it will open in the Results tab shown in a default style (HtmlBlue). For many it looks quite OK. However, SAS provides many other different styles you can choose from. To change your report style, just click on Properties of the workspace toolbar:
Results tab in SAS EG
This will open the Properties for SAS Report window where you can select any style in the Style drop-down list:

Properties for SAS Report
After you selected desired style, click OK; this will save your change and close the window. Your report will immediately be redrawn and displayed in your new style:

SAS report in new style

That new style will only apply to the Results element of the SAS Program or a Process Flow you ran. If you save the EG project and then re-open it in a new EG session and re-run, EG will still remember and use the style you previously selected for the Results element. All other elements will use the default style.

But how do you know what each style’s look and feel is before you select it? The following sections show how to browse different styles as well as how to change your default styles to new ones.

Browsing SAS EG styles

SAS Enterprise Guide interface provides a quick access to viewing different styles, whether built-in or external. Here is how to get an idea of different styles look and feel.

From the EG main menu click on Tools → Style Manager. In the opened Style Manager window you may browse through the Style List by clicking on each style listed in the left pane and also get a good idea of how each particular style looks by viewing it in the right Preview pane of the Style Manager window:

Style Manager window

From Style Manager window, you can also set up a default style by selecting a style you like from the Style List in the left pane and clicking Set as Default button. However, setting your default style using Style Manager will only affect SAS Report and HTML results formats. But what about other results formats? Not to worry, SAS EG interface has you covered.

Changing your default SAS EG report style

If you like a particular report style and don’t want to be stuck with a pre-set default style and necessity to change it every time you run a report, you may easily change your SAS EG default style for practically any results format.

From the EG main menu click on Tools → Options…, the Options window will open. I that window, under Results → Results General you may select (check) one or multiple Results Formats (SAS Report, HTML, PDF, RTF, Text Output, PowerPoint, and Excel) as well as choose your Default Result Format:

Options window to choose default report format

Let’s set up default styles for different results formats. First, let’s go to Results → SAS Report, you will see (under Appearance → Style) that your default style (set up during initial EG installation) is HtmlBlue. Click on the Style drop-down list to select a different style:

Select new report style

The same way you may set up default styles for other results formats (HTML, RTF, PDF, Excel, and PowerPoint). For Graph, you may select a Graph Format (ActiveX, Java, GIF, JPEG, etc.) When you are done, click OK button, the Options window will close and your selected styles become your new default. They are going to persist across EG sessions.

If you are a SAS Administrator, to ensure consistency across your organization, you may have all your SAS Enterprise Guide users set up the same Default styles for every Result format.

Server-side style templates

Server-side SAS style templates are created using the PROC TEMPLATE of the SAS Output Delivery System (ODS) and are stored in Template Stores within SAS libraries. By definition, a template store is an item store that stores items that were created by the TEMPLATE procedure. In particular, built-in server-side SAS style templates are stored in the SASHELP.TMPLMST item store.

Note, that you will not see these item stores / template stores in the EG Server→Library tree under the SASHELP library as it only shows data tables and views. While there is no access in EG to the Templates Window, you can access the Templates Window from SAS Display Manager.

In Enterprise Guide, in order to view a list of built-in server-side SAS styles in the SASHELP.TMPLMST item store, you may run the following code:

proc template;
   path sashelp.tmplmst;
   list styles;
run;

This will produce the following listing shown in the EG’s Results tab:

Report listing

If you want to view all the server-side styles including built-in and user-defined, you can do that in EG by running the following code:

proc template;
   list styles;
run;

Server-side templates are applied to ALL Results Formats.

CSS styles

Cascading Style Sheet (CSS) styles are available only for SAS Report and HTML result formats. The CSS stylesheet only styles the browser-rendered elements. It will not change a graph image style that is generated on the server.

In the SAS code generated by EG, CSS style is specified in STYLESHEET= option of the ODS statement. It can point to any local or network accessible CSS file, for example:

STYLESHEET=(URL="file:///C:/Program%20Files/SASHome/SASEnterpriseGuide/7.1/Styles/HTMLBlue.css")

In addition, STYLESHEET= option can point to a .css file located on the Internet, for example:

STYLESHEET=(URL="https://www.sas.com/etc/designs/saswww/static.css")

Server-side styles vs. CSS styles

With SAS Enterprise Guide you create Projects, Process Flows, Programs, Tasks, Reports, etc. on your local Window machine. When you Run your Project (or any part of it), EG generates SAS code which gets sent to and executed on the SAS server, and then any visual results are sent back to EG and displayed there.

For every Result Format, a server-side style template is always applied when SAS output is generated on the SAS server.

When that SAS output is returned to SAS EG, for SAS Report and HTML result formats only, an additional optional styling is applied in a form of CSS styles that controls what your SAS Report or HTML output looks like. This CSS styling affects only HTML elements of the output and do not affect graph images that are always generated and styled on the server.

These two kinds of styles are reflected in the EG-generated SAS code that gets shipped to SAS server for execution. If you look at the Code Preview area (Program → Export → Export Program) or Log tab, you will always see ODS statement with STYLE= option that specifies the server-side style. If your selected Result Format is either SAS Report or HTML, then in addition to STYLE= option the ODS statement also contains STYLESHEET= option that specifies HTML CSS stylesheet (external file) accessible via the client.

If you select as default a built-in style (e.g. Harvest) EG will find both server version of it and CSS version of it; you will see this in the SAS log:

STYLE=Harvest
STYLESHEET=(URL="file:///C:/Program%20Files/SASHome/SASEnterpriseGuide/7.1/Styles/Harvest.css")

However, if you select as default some custom CSS or external CSS style (e.g. ABC) that does not have a match in the server template store, the server style will be set to the default server-side style HTMLBlue; you will see in the SAS log the following WARNING:

WARNING: Style ABC not found; Default style will be used instead.

This warning relates to the STYLE= option specifying the server-side style.

Adding your custom SAS EG report style

Even though SAS supplies dozens of styles for you to choose from (Built-in Styles), you can still modify existing styles and create your own custom styles for SAS Report and HTML output types only. You can do this via Style Manager.

Open Style Manager with either one of the following ways:

Tools → Style Manager

Tools → Options… → Results/SAS Reports → Manage Styles

Tools → Options… → Results/HTML → Manage Styles

Note, that style customization via Style Manager is only available for SAS Report and HTML output types.

In the left pane of the Style Manager there are 3 columns:

  1. Style representing style name;
  2. Location indicating whether it is Built-in Style (SAS-supplied CSS), My Style (your custom CSS), or External Style (any CSS - Cascading Style Sheet - on your local machine or on the Web; or a style template on a SAS server);
  3. URL showing the location of the CSS file.

Find a style in the left pane list you wish to modify. Notice that SAS-supplied built-in styles are not editable (Edit button is grayed out). First, make a copy of this style by pressing Create a Copy button. You can also make a copy of a style by right-clicking on it and selecting Create a Copy from the pop-up menu.  This will open Save Style As window where you can give it a name and select a Save in location.

Your new style appears in the Style List of the Style Manager. Click on the new style name and then press Edit button (alternatively, you may right-click on the new style name and select Edit from the pop-up menu):

Style Editor window

This will open the Style Editor window where you can modify text and border attributes, specify background and banner images, as well as assign any custom CSS property name / property value pairs.

Click OK button when you are done to return to the Style Manager. There you may even set your custom style as default, by selecting it first and then pressing the Set as Default button.

Besides editing your new style in Style Manager, you may also open your-new-style.css file in a Text Editor and edit CSS there.

Adding an external style to Enterprise Guide

You can add external styles to your Style List in the Style Manager. While in the Style Manager, click on Add button, this will open the Add New Style window:

Adding an external style

Make sure Add new external style radio box is selected. Type in a Style name for your external style and Style URL, which can be a folder/directory path name on your local machine or your network (e.g. C:\your_folder\your_css_file_name.css) or a location on the Web (e.g. http://www.some_domain.com/styles/your_special_style.css).

To make your custom styles available to all SAS EG users in your organization, you may create them as a SAS style template using PROC TEMPLATE and place on a SAS server (server-side style), see this SAS Code Sample.  In this case, you can add your custom style to the Style Manager by selecting This is a SAS server style only check box in the above Add New Style window. The Style URL field will become disabled, as it is only used to specify CSS stylesheet:

Checking This is a SAS server style only checkbox

You would select this checkbox if you only want to use server-side style (the STYLE= option is always present) and do not want to also provide and apply an optional CSS stylesheet (STYLESHEET=).

Conclusion

In this post I tried to present a comprehensive guide on using styles in SAS Enterprise Guide. Please use the Comments section below to share your experience with Enterprise Guide as it relates to reports styling.

Resources

Little SAS Enterprise Guide bookThe Little SAS Enterpriser Guide Book

Point-and-Click Style Editing in SAS® Enterprise Guide®

I Didn’t  Know SAS®  Enterprise Guide®  Could Do  That!

Creating reports in style with SAS Enterprise Guide was published on SAS Users.

10月 192017
 

The goal of this article is to describe the steps needed to configure the bridge that allows SAS Data Integration 4.902, based on SAS 9.4M4, to load data directly into CAS on SAS Viya 3.2.

Of course, SAS 9.4M5 simplifies this process, as a SAS/CONNECT communication will no longer be required, enabled by a direct function within SAS Data Integration to CAS - but for those of you who may not move immediately from SAS 9.4M4 to SAS 9.4M5, this could be helpful.

It is assumed here that SAS/CONNECT has been installed and configured on both environments, SAS 9.4M4 and SAS Viya 3.2.

Validate the connection from SAS 9.4M4 to SAS Viya 3.2

⇒     Check the status of the SAS/CONNECT Spawner on SAS Viya, on the machine where this service is installed.

SAS Viya 3.2 Bridge for SAS Data Integration Studio

⇒     Note the machine and the listening port of the SAS/CONNECT Spawner on SAS Viya.
⇒     Open SAS Studio on SAS 9.4M4 and sign-in.
⇒     Run the following SAS code with your machine details and a valid SAS Viya user account and check the results.

SAS Viya 3.2 Bridge for SAS Data Integration Studio

⇒     If successful, sign-off the SAS/CONNECT session and sign-out from SAS Studio SAS 9.4M4

Setup SAS9.4M4 metadata

⇒     Open SAS Management Console 9.4M4 as sasadm@saspw.
⇒     On the “Server Manager” plugin, add a “New Server…”

  • Server type: “SAS Application Server”
  • Name: “SASViya”
  • Select “Connect Server” as the sub-type of server you want to add to this SAS Application Server
  • Configure the “Connect Server” as shown below (you might have to create a new authentication domain for SAS Viya) and set the values accordingly (server where the SAS/CONNECT Spawner on SAS Viya is listening)

⇒     On the “Server Manager” plugin, add a “New Server…”

  • Server type: “SAS Cloud Analytic Services Server”
  • Name: “CAS Server”
  • Configure the “CAS Server” as shown below and set the values accordingly (CAS controller)

⇒     On the “User Manager” plugin, set a login for the SASViya application server, on a user or group that you will use in SAS Data Integration Studio

⇒     On the “Data Library Manager” plugin, add a “New Library…”

  • Library type: “SAS Cloud Analytic Services Library”
  • Name: CAS_DATA
  • Assign the library to the SASViya server

⇒     Configure the CAS library as shown below and set the values accordingly (the CASLIB must exist in the SAS Viya environment; here CASPATH is the name of an existing CASLIB).

⇒     Specify the server and connection information as shown below:

Build a SAS Data Integration Studio job to load data into CAS

⇒     Open SAS Data Integration Studio 4.902 as a user who holds, directly or not, a login for the ViyaAuth authentication domain.
⇒     Test the CAS_DATA library by “Register(ing) tables…”

  • In SAS Environment Manager on SAS Viya, some tables must have been loaded before into the CASLIB (the one that is pointed on by the CAS library, here CASPATH), so that you can display some tables in the “Register Tables…” wizard.
  • If you see some tables then it looks like you are all set.

⇒     If you want to go further and test the “Cloud Analytic Services Transfer” DI transformation, create the metadata for a target table in CAS with appropriate columns.

⇒     Build a job that loads a source table to this target table using the “Cloud Analytic Services Transfer” (“Access” folder) as shown below:

⇒     The “Cloud Analytic Services Transfer” is basically a “Data Transfer” transformation that fits with CAS; it enables you to provide some CAS options such as COPIES; by default the table is PROMOTED.

⇒     Run it and check if it ran successfully and if the table is available from the SAS Viya world.

SAS/CONNECT on SAS Viya configuration directory

⇒     The SAS/CONNECT on SAS Viya configuration is located by default here /opt/sas/viya/config/etc/connectserver/default

⇒     You might want to customize/clean some of the files here.

  • Check the CASHOST option in autoexec files, sometimes the value is not appropriate.

Normally, options here are sourced from the CONNECTSERVER_CONFIGURATION in vars.yml during the deployment of SAS Viya.

SAS Viya 3.2 Bridge for SAS Data Integration Studio 4.902 (on SAS 9.4M4) configuration steps was published on SAS Users.

10月 182017
 

In a previous article, I discussed the lines plot for multiple comparisons of means. Another graph that is frequently used for multiple comparisons is the diffogram, which indicates whether the pairwise differences between means of groups are statistically significant. This article discusses how to interpret a diffogram. Two related plots are also discussed.

How to create a diffogram in SAS

The diffogram (also called a mean-mean scatter diagram) is automatically created when you use the PDIFF=ALL option on the LSMEANS statement in several SAS/STAT regression procedures such as PROC GLM and PROC GLMMIX, assuming that you have enabled ODS graphics. The documentation for PROC GLM contains an example that uses data about the chemical composition of shards of pottery from four archaeological sites in Great Britain. Researchers want to determine which sites have shards that are chemically similar. The data are contained in the pottery data set. The following call to PROC GLM performs an ANOVA of the calcium oxide in the pottery at the sites. The PDIFF=ALL option requests an analysis of all pairwise comparisons between the LS-means of calcium oxide for the different sites. The ADJUST=TUKEY option is one way to adjust the confidence intervals for multiple comparisons.

ods graphics on;
proc glm data=pottery plots(only)=( diffplot(center)          /* diffogram */
                                    meanplot(cl ascending) ); /* plot of means and CIs */
   label Ca = "Calcium Oxide (%)";
   class Site;
   model Ca = Site;
   lsmeans Site / pdiff=all cl adjust=tukey;  /* all pairwise comparisons of means w/ adjusted CL */
   ods output LSMeanDiffCL=MeanDiff;          /* optional: save mean differences and CIs */
quit;

Two graphs are requested: the diffogram (or "diffplot") and a "mean plot" that shows the group means and 95% confidence intervals. The ODS OUTPUT statement creates a data set from a table that contains the mean differences between pairs of groups, along with 95% confidence intervals for the differences. You can use that information to construct a plot of the mean differences, as shown later in this article.

How to interpret a diffogram

Diffogram in SAS showing multiple comparisons of means

The diffogram, which is shown to the right (click to enlarge), is my favorite graph for multiple comparisons of means. Every diffogram displays a diagonal reference line that has unit slope. Horizontal and vertical reference lines are placed along the axes at the location of the means of the groups. For these data, there are four vertical and four horizontal reference lines. At the intersection of most reference lines there is a small colored line segment. These segments indicate which of the 4(4-1)/2 = 6 pairwise comparisons of means are significant.

Let's start at the top of the diffogram. The mean for the Caldecot site is about 0.3, as shown by a horizontal reference line near Y=0.3. On the reference line for Caldecot are three line segments that are centered at the mean values for the other groups, which are (from left to right) IslandThorns, AshleyRails, and Llanederyn. The first two line segments (in blue) do not intersect the dashed diagonal reference line, which indicates that the means for the (IslandThorns, Caldecot) and (AshleyRails, Caldecot) pairs are significantly different. The third line segment (in red) intersects the diagonal reference line, which indicates that the (Llanederyn, Caldecot) comparison is not significant.

Similarly, the mean for the Llanederyn site is about 0.2, as shown by a horizontal reference line near Y=0.2. On the reference line for Llanederyn are two line segments, which represent the (IslandThorns, Llanederyn) and (AshleyRails, Llanederyn) comparisons. Neither line segment intersects the diagonal reference line, which indicates that the means for those pairs are significantly different.

Lastly, the mean for the AshleyRails site is about 0.05, as shown by a horizontal reference line near Y=0.05. The line segment on that reference line represents the (IslandThorns, AshleyRails) comparison. It intersects the diagonal reference line, which indicates that those means are not significantly different.

The colors for the significant/insignificant pairs depends on the ODS style, but it is easy to remember the simple rule: if a line segment intersects the diagonal reference line, then the corresponding group means are not significantly different. A mnemonic is "Intersect? Insignificant!"

The mean plot with confidence interval: Use wisely!

Mean plot and 95% confidence intervals, created with SAS

The previous section shows how to use the diffogram to visually determine which pairs of means are significantly different. This section reminds you that you should not try to use the mean plot (shown at the right) for making those inferences.

I have seen presentations in which the speaker erroneously claims that "the means of these groups are significantly different because their 95% confidence intervals do not overlap." That is not a correct inference. In general, the overlap (or lack thereof) between two (1 – α)100% confidence intervals does not give sufficient information about whether the difference between the means is significant at the α level. In particular, you can construct examples where

  • Two confidence intervals overlap, but the difference of means is significant. (See Figure 2 in High (2014).)
  • Two confidence intervals do not overlap, but the difference of means is not significant.

The reason is twofold. First, the confidence intervals in the plot are constructed by using the sample sizes and standard deviations for each group, whereas tests for the difference between the means are constructed by using pooled standard deviations and sample sizes. Second, if you are making multiple comparisons, you need to adjust the widths of the intervals to accommodate the multiple (simultaneous) inferences.

"But Rick," you might say, "in the mean plot for these data, the Llanederyn and Caldecot confidence intervals overlap. The intervals for IslandThorns and AshleyRails also overlap. And these are exactly the two pairs that are not significantly different, as shown by the diffogram!" Yes, that is true for these data, but it is not true in general. Use the diffogram, not the means plot, to visualize multiple comparisons of means.

Plot the pairwise difference of means and confidence intervals

In addition to the diffogram, you can visualize comparisons of means by plotting the confidence intervals for the pairwise mean differences. Those intervals that contain 0 represent insignificant differences. Recall that the call to PROC GLM included an ODS output statement that created a data set (MeanDiff) that contains the mean differences. The following DATA step constructs labels for each pair and computes whether each pairwise difference is significant:

data Intervals;
length Pair $28.;
length S $16.;
set MeanDiff;
/* The next line is data dependent. For class variable 'C', concatenate C and _C variables */
Pair = catx(' - ', Site, _Site);           
Significant = (0 < LowerCL | UpperCL < 0); /* is 0 in interior of interval? */
S = ifc(Significant, "Significant", "Not significant");
run;
 
title "Pairwise Difference of LSMeans (Tukey Adjustment)";
title2 "95% Confidence Intervals of Mean Difference";
footnote J=L "Pairs Whose Intervals Contain 0 Are Not Significantly Different";
proc sgplot data=Intervals;
   scatter y=Pair x=Difference / group=S name="CIs"
           xerrorlower=LowerCL xerrorupper=UpperCL;
   refline 0 / axis=x;
   yaxis reverse colorbands=odd display=(nolabel) 
                 offsetmin=0.06 offsetmax=0.06;
   keylegend "CIs" / sortorder=ascending;
run;
Plot of mean differences and confidence intervals, created with SAS

The resulting graph is shown to the right. For each pair of groups, the graph shows an estimate for the difference of means and the Tukey-adjusted 95% confidence intervals for the difference. Intervals that contain 0 indicate that the difference of means is not significant. Intervals that do not contain 0 indicate significant differences.

Although the diffogram and the difference-of-means plot provide the same information, I prefer the diffogram because it shows the values for the means rather than for the mean differences. Furthermore, the height of the difference-of-means plot needs to be increased as more groups are added (there are k(k-1)/2 rows for k groups), whereas the diffogram can accommodate a moderate number of groups without being rescaled. On the other hand, it can be difficult to read the reference lines in the diffogram when there are many groups, especially if some of the groups have similar means.

For more about multiple comparisons tests and how to visualize the differences between means, see the following references:

The post The diffogram and other graphs for multiple comparisons of means appeared first on The DO Loop.

10月 182017
 

In growing areas such as the Research Triangle Park, there is always the tough decision between developing land for business, or keeping it natural for parks and recreation. SAS is fortunate to have the great hiking trails at Umstead Park just across the road to the north - it's the [...]

The post RDU airport -vs- surrounding parks and nature appeared first on SAS Learning Post.

10月 182017
 

In growing areas such as the Research Triangle Park, there is always the tough decision between developing land for business, or keeping it natural for parks and recreation. SAS is fortunate to have the great hiking trails at Umstead Park just across the road to the north - it's the [...]

The post RDU airport -vs- surrounding parks and nature appeared first on SAS Learning Post.

10月 182017
 

You know the value of your SAS Certification; does the rest of the world? A recent MONEY and Payscale.com study named SAS Analytics skills as the most valuable skills to have in today’s job market and certification is the best way to demonstrate those skills. Recognition like this helps solidify [...]

The post Share your SAS Certification experience and maximize value appeared first on SAS Learning Post.

10月 172017
 

moving content between SAS Viya environmentsIn a SAS Viya 3.2 environment two types of content can be created: SAS Visual Analytics Reports and Data Plans. For administrators, who may want to manage that content within a folder structure, there are some things to keep in mind. In the current release, both types of content can be moved around in folders, but the objects cannot be copied. In addition, SAS Viya 3.2 supports the promotion of SAS Visual Analytics Reports, but doesn’t support the promotion of Data Plans (support for Plans is coming in SAS Viya 3.3). So, what if I want to copy a report between, say my personal folders, to a production folder?

If you want copy a Report or Data Plan within an environment there is an easy way. When the object is open in edit mode you can do a Save As to save a copy to a different location in the folder structure.

Between environments, Reports can be exported and imported using the SAS Visual Analytics, when you are editing your content (Report or Data Plan) you can access a “diagnostics” window. The diagnostics window will show you the json (or xml) used to render the Report or Plan. To enter the diagnostics window use the keystrokes:

  • ctl+alt+d for SAS Visual Data Builder.
  • ctl+alt+b for SAS Visual Analytics.

In the steps below I will use the diagnostics window to save a Data Plan so that it can be loaded to a different SAS Viya Environment. The steps for a SAS Visual Analytics report are very similar.

In SAS Visual Data Builder when editing your Data Plan select ctl-alt-d to open the SAS Visual Data Builder Diagnostics window. The source tab of the window shows the json that will render the data plan.

Click Save to save the json to a text file and close the dialog. The json file will be saved in the browsers default downloads folder.

Copy the saved text file to a location accessible to the SAS Viya environment where you want to import the plan. In that environment, open Data Builder and click New to open a new Data Plan.

Click ctl-alt-d on the empty data plan and cut and paste the json from your text file replacing the json in the diagnostics window.

Click Parse to check the json.A message should be displayed indicating that the  “plan text was parsed successfully.”  Once you have parsed the text, click Run and the plan is loaded into SAS Visual Data Builder.

In SAS Visual Data Builder, select Save As and save the plan to any location in the folder structure.

The assumption with this approach is that the data is available in the same location in both environments.

You can do much the same with SAS Visual Analytics reports. The key-stroke is ctl-alt-b to open the SAS Visual Analytics Diagnostics window.  You can see the report xml or json on the BIRD tab.

To copy a single report between environments, you can select json and then save the json to a file. In the target environment open a new report, paste the json in the BIRD tab, parse and load and then save the report to a folder. This can be a useful approach if you want to relocate a report to a different location in your target environment. The transfer service currently will only import reports to the same folder location in the target that they are located in the source environment.

I hope you found this tip useful.

A tip for moving content between SAS Viya environments was published on SAS Users.

10月 172017
 

Would you like to format your macro variables in SAS? Good news. It's easy!  Just use the %FORMAT function, like this: %let x=1111; Log %put %format(&amp;x,dollar11.); $1,111 %put %format(&amp;x,roman.); MCXI %put %format(&amp;x,worddate.); January 16, 1963   %let today=%sysfunc(today()); %put %format(&amp;today,worddate.); October 13, 2017   %put %format(Macro,$3.); Mac What?!  You never [...]

The post How to format a macro variable appeared first on SAS Learning Post.

10月 172017
 

Professionals with deep analytical knowledge, particularly using SAS, are in high demand. But to build a successful career, you first have to acquire the necessary analytical skills. Recently, I interviewed Andrea Baroni, a graduate from Lancaster University, and asked him to share his experience learning SAS and how it has helped advance his professional career. Your background Mayra [...]

The post How SAS can help your career appeared first on SAS Analytics U Blog.