Delivering SAS to Excel Jockeys

Delivering SAS to Excel Jockeys

Sy
Truong, Meta-Xceed, Inc., Milpitas, CA Jing Xu, Providian, Pleasanton CA

ABSTRACT

The ubiquity of Microsoft Excel and Word on desktop computers
has made it a default entry point for many users to view and edit their
information. Once Excel was included into the MS Office suite in 1993, it became
the killer app overtaking other spreadsheet heavy weights such as Lotus 1-2-3.
Although Excel has analysis capabilities, it does not have the powerful
statistical procedures and depth of SAS. When analyzing certain types of data,
such as financial information, Excel is the tool of choice. Its capabilities to
easily generate graphs along with the visual pivot table provide powerful
methods to view and analyze data. In certain cases, however, Excel is not
capable of performing particular tasks which SAS can provide. Some of the topics
that this paper will elaborate on include:

• Connecting SAS to Excel –
The use of TCP port communication allows Excel to connect directly with a SAS
session

• SAS Macro Management – Managing
SAS macros that can be delivered to Excel users

• Deliver SAS Data – SAS
Datasets can be delivered directly to Excel or Word in optimized smaller
blocks

• Pivot Table and Graph – SAS
data can be formulated and delivered to Excel users in the form of a Pivot
Table and/or Graph ( Excel Chart)

The union of SAS and Excel enables power users and decision
makers, who may not be SAS programmers, to fully explore their business data
with the full analytical power of the SAS system.

INTRODUCTION

The advent of the modern spreadsheet has revolutionized how
users analyze data such as financial data. It visually displays information in
cells similar to how a professor may describe the information on a chalk board.
The disadvantage of a chalk board is when a change or mistake is made. Rather
than having to erase each item on the board, the cells of a spreadsheet can be
updated through a formula. Programming languages have evolved to work with
spreadsheets so they can provide a very efficient method for financial analysts
to perform analysis interactively. There are many advantages to this approach
but there are also some limitations. Some of these limitations include:

• Change Control – The
changes to the spreadsheet are very interactive so the information stored
previous to updates are lost. This can lead to regulatory compliance issues or
limit the ability to easily roll back to an earlier version.

• Security – Spreadsheets
are designed for individuals to work on their own set of data. They cannot
easily handle multiple users with different perm issions. This combined with
the lack of change control makes it difficult to function as a secured system
for large sets of data in a large organization with many users.

• Cell Based Formula – Formulas
defined for a cell in Excel are defined for a particular cell. An example is
to sum up all the cells by their identified cell row and column name,
=SUM(A1:A3). In this example, the cells A1, A2 and A3 are summed to a
specified new cell such as A4. This is limited to cell A4 and is not easily
replicated in an array of multiple cells. There have been scripting languages
to enhance the capabilities of formulas but it is still limited since formulas
are designed as expressions and not designed for complex algorithms which
require a full featured programming language.

• Multiple Users – Spreadsheets
are designed for a single user. This creates limitations if multiple users
need to update the same data.

• Statistical Analysis – Formulas
are designed as an expression to derive at a numeric answer. There is some
statistical analysis that can be applied through a spreadsheet but this
approach is limited. It is not optimized for more complex statistical modeling
such as performing a multi-variate regression analysis.

The exploratory and visual aspects of spreadsheets make them
very suitable for certain types of financial calculations. However, some of the
limitations mentioned above can prevent power users from performing data mining
to truly model business conclusions that can be delivered by SAS. SAS has the
powerful programming language including a library of statistical procedures
which deliver to users functionality beyond the capabilities of spreadsheets.
The two tools can function together symbionically to form a complete solution.
This paper will explore the integration of SAS and Excel in ways that give SAS
programmers methods of delivering to Excel jockeys the power of SAS without
requiring them to program SAS.

CONNECTION SAS TO EXCEL

There are several ways to deliver data or connecting information
between SAS and Excel. Depending on the requirements, the following solutions can
provide the optimal methods of delivery.

Communication Method	Description
Cut and Paste	Text output data can be cut and pasted into Excel through the clip board. If the source data contains the correct delimiter, the pasted values will be populated into a spreadsheet with proper column alignment.
DDE Dynamic Data Exchange	Data and instructions can be sent from SAS to Excel through Dynamic Data Exchange. This can deliver the most up to date data dynamically. It can also include some Excel functions so that the output can be placed onto a particular cell or worksheet.
TCP/IP Socket	Data and instructions can be sent from SAS to Excel through the same protocol that is used on most networks across the Internet.

There are advantages and limitations to each of the three
methods mentioned above. This paper will explore the third option of delivering
data and analytical computing power of SAS to Excel via TCP/IP socket
communication. This process will make it possible to have a SAS macro execute on
the server and the results delivered directly to Excel.

AUTHENTICATION AND SECURE ACCESS

There are multiple layers of security that can be applied to
ensure that the data being delivered from SAS to Excel is protected. Some or all
of the methods mentioned here can be implemented for optimal security. The
security measures include:

1. OS Privileges – The operating system in which the computer system
resides acts as the first line of defense. This will authenticate the user
who will be able to execute the SAS program and access Excel. This also acts
as a layer to prevent users from accessing certain datasets that contain
sensitive data.

2. Data Control – SAS datasets can contain password protection to
prevent unauthorized access. This can be set for read or read write
depending on the needs of the particular user.

3. Application Control – The application used in this example, MXI
Plugin™, also contains a layer of authentication, both on the server side
and client side. This will ensure that only specified members that have been
granted perm issions will have access.

The OS and dataset controls are well understood. The unique
approach that is discussed in this paper will demonstrate how the application
applies an extra layer to ensure optimal security. The following steps are
applied by the application.

STEP 1: SOCKET PORT – The application server is configured to
be available only on a specified port. This information is not published so it
is more difficult for unintentional users to access the data through this port.

STEP 2: ACCESS CONTROL LIST– The application server will have
the ability to create user accounts. This is needed to control the access and
limit access to specified data and SAS macro programs.

STEP 3: PRIVILEGE ASSIGNMENTS – All SAS datasets and SAS macro
programs will have user access assigned. This will be controlled at the level of
each user. For SAS datasets, the user will have the ability to assign read
perm issions. For SAS macro programs, the user can have either read or execute
privileges granted.

STEP 4: CLIENT AUTHENTIFICAITON – The client application in
this case is a plug-in application to MS Excel. A dialog box is presented to the
user with a way of authenticating to the server. This will authenticate the user
and includes the server and socket port number. This will prevent accidental
access on default port numbers which other applications use.

STEP 5: TRANSPORT ENCRYPTION – The data being sent from the
SAS server to the Excel client will be encrypted with a password. This will
prevent access to the contents of the data if the data packets are intercepted
during delivery.

The five steps demonstrate methods that ensure that the data
being delivered from the server to the client is secured. The multiple layers
create redundancy to prevent accidental or malicious intent to alter or capture
sensitive data.

SAS MACRO MANAGEMENT

SAS macro is a programming language that is an extension of the
SAS base programming language. It is a superset of the base language in that you
can apply all the same data steps and SAS procedures to fully utilize the power
of SAS. In addition, it provides a way of modularizing repetitive portions of
your SAS program. It is recommended that when a particular task or programming
code segment is repeated more than three times, it should be placed into a
macro. This way, it can be repeated in a consistent manner. This provides SAS
programmers with a method for automating algorithms while allowing other
programmers to apply the same logic without having to completely understand the
intricacies of that code segment.

There are a couple of ways in which SAS macros are delivered to
other users. The main method is by creating a macro library. In this approach,
each macro is placed into a program where the name of the program is the same as
the name of the macro, and then placed in specified folders. For example, if you
were to have code that calculates the age of an individual, the program can be
named calc_age.sas and the corresponding macro is named %calc_age. The macro can
therefore be accessible to any program if the path of the program cal_age.sas is
defined in the AUTOPATH as a SAS option. Similar to other programming languages,
an include statement can also be used to include the external program
calc_age.sas into your current program such as in: *** include the macro to
calculate age ***;

%include "c:\mypath\calc_age.sas";

There are therefore two steps in the process of delivering a SAS
macro. These include:

STEP 1: SETUP MACRO – Start out by creating a SAS library
through the AUTOPATH option and inform the users of this so that they can apply
the steps to enable access.

STEP 2: USING MACRO – The user would then set up the macro
auto path in their autoexec.sas or through applying the include statement to
gain access. The user would then call the macro through the name such as in the
call: *** Apply the calculation of age ***;

data mydata;

set sourcelib.data;

%calc_age;

run;

The above traditional steps for managing the SAS macros are
designed for SAS programmers. This requires the user to understand the concepts
of the macro language and know how to access the macros programmatically through
proper syntax. This is appropriate for SAS programmers but can be prohibitive if
delivered to non SAS programmers such as Excel jockeys. An alternative and more
suitable method is described in the following steps.

STEP 1: MACRO LIBRARY MANAGEMENT – A graphical user interface
is provided for the macro developer to manage and organize the macros in
preparation for delivery.

The concept of a library is similar to the SAS auto path macro
library in that a series of macros can be placed into this directory for
delivery. In addition to having the path associated, a user friendly library
name can be assigned such as "Sample Library". This approach can
provide more flexibility since programs from different directory paths can be
associated to one library. The method for adding macros to a library in this
approach is applied through a graphical user interface. This makes the process
more user friendly. However, since this step is generally applied by SAS
developers, an additional batch approach is also available. For experienced
users, the batch method can be more efficient if many macros are applied at
once. In this example, a macro can be added to a macro library through a macro.

/*----------------------------------------------------*

* Program: maclib.sas

* Path: C:\Program Files\SAS\SAS 9.1

* Description: Manage macro libraries for MXI Plugin

* By: Sy Truong, %maclib, 02/18/2007, 12:06:03 pm

*-----------------------------------------------------*/

%maclib(macro = ,

library = Old Name,

action = delete);

%maclib(macro = ,

library = Sample Library,

action = add);

CONVERTING MACRO PARAMETERS

Macro parameter is the main method for modularizing your SAS
logic. This allows for you to parameterize and change specific values such as
input data or variable names within your SAS logic in order for it to perform
many different tasks. For example, a macro can be named "getparam"
which stands for "get parameters" as shown below: %getparam(macro =
C:\saspgm\pivottab.sas,

desc = ,

param = datname var type,

require = ,

type = text text radio buttons,

vallist = none none SAMPDATA.AE.DOMAIN,

defval = mydata|id 6 of maps.afghanis|AE);

In this example, the macro %getparam macro contains parameters
such as MACRO, DESC and PARAM. The values associated with each parameter are
then fed into the associated macro code to perform tasks specified by the user
request. This fundamental construct of the macro language acts as an interface
between the user and the macro itself.

The same parameters can be delivered to users in the form of
selection lists and radio buttons that Excel users are more accustomed to. MXI
Plugin can set this up so that the user experience is completely within Excel
providing the familiar user interface, while delivering powerful analysis on the
SAS server.

PIVOT TABLE AND GRAPH

Pivot tables and graphs or charts are powerful tools to explore
and display information. This can be demonstrated in an example where credit
score information, recorded as a FICO score, is collected for customers. The
financial institution commonly asks the question if the latest average FICO
score is high or low. This information is summarized across all customers by
year. An example result of performing this analysis is shown here:

The pivot table is shown on the left two columns of the
spreadsheet. The user can pull down the account open date "OPENDT2"
column and select specific years. The graph to the right will then show the
selected pivot table data points in a graph. The pivot table adds flexibility in
selecting the data segment of interest. The accompanying graph provides a visual
presentation of the same information to enable users to spot trends. The above
information can be prepared by the following steps.

STEP 1: DELIVER THE DATA – The data can be delivered from SAS
directly into Excel. This is accomplished through the MXI Plugin menu within
Excel or through the Excel toolbar. The data selection is then presented through Excel or through the Excel toolbar. The data selection is then presented through
the data libraries that are established on the server.

Once the user has been properly authenticated, the data can be
delivered to users as SAS datasets, pivot tables or graphs. If

the user decides to select the SAS datasets, the raw data will
be delivered to Excel as a spreadsheet. In this case, the user would continue to
the next step to establish the pivot table.

STEP 2: SETUP PIVOT TABLE – If the user selects the source
data from the list of SAS datasets, the data will be presented as a spreadsheet.
In this case, the user can then use Excel to set up the pivot table.

The Excel Layout tool allows the user to select the row such as
the open date in this example. The column of the pivot table can also be
assigned as seen in this example where the average FICO score is selected. This
does require a little work within Excel for the user to then establish the pivot
table. Alternatively, you can set up the same pivot table and have it delivered
directly to Excel by using the MXI Plugin server pivot table setup tool.

In this case, the open date and FICO score variables can be
selected in a similar manner. The difference is that this is being established
beforehand so that the user can select the pivot table directly as a sample data
source. This setup occurs on the SAS server, but once delivered to the client,
it will appear as a native Excel pivot table.

STEP 3: SETUP GRAPH/CHART – The last step in this analysis is
to create a graph or chart from the selected pivot table. The user has the
choice of selecting data from the raw source or from the pivot table. This
information is then used to create the graph within Excel. An alternative method
is to have this process set up on the server. This adds greater flexibility
since the graphs can be preprocessed on the server and delivered directly into
Excel as an Excel native chart, or it can be generated on the client Excel Excel as an Excel native chart, or it can be generated on the client Excel
spreadsheet.

In this example, the source to the graph can be either the
source data or a pivot table. You would then choose the column and row
variables. The titles and types of graphs can be selected in a similar way that
the wizard in Excel provides. The difference is that you are preparing to have
this delivered completely on the server prior to its delivery to the user on
Excel. The above steps show how you can deliver SAS data to Excel either as a Excel. The above steps show how you can deliver SAS data to Excel either as a
spreadsheet, pivot table or graph. You can leave it up to the user to then
create their own pivot table and graph within Excel, or have this prepared ahead
of time so that the user can have the most updated data on the server delivered
in the form of a pivot table or graph. This empowers Excel users to access SAS
data with visual display formats which are native to Excel.

CONCLUSION

MS Excel has become the default standard for data analysis on
desktop client computers. SAS has established itself as a powerful analytical
data mining tool on servers. This paper presents a unique approach using MXI
Plugin which marries the two tools enabling SAS data sets to be delivered
directly to Excel. The delivery method uses the standard TCP/IP as the underling
protocol for communication. There are multiple layers of security that are put
into place to prevent accidental or intentional data corruption. The powerful
analytical logic of SAS is delivered to Excel in multiple ways including: SAS
macro, SAS data, pivot table and graph. This information is delivered in a user
friendly manner since users can select parameters of a macro in a form of pull
down lists or check boxes. The SAS data is presented as spreadsheets and pivot
tables and graphs can be delivered in Excel formatted pivot tables and charts.
This empowers Excel users with many options to access the power of SAS without
having to program SAS. This approach provides Excel jockeys with an interface
that is familiar to Excel users while delivering the full power of the SAS
system.

REFERENCES

SAS and all other SAS Institute Inc. product or service names
are registered trademarks or trademarks of SAS Institute Inc. in the USA and
other countries. ® indicates USA registration.

MXI Plutin™ and other MXI (Meta-Xceed, Inc.) product names are
registered trademarks of Meta-Xceed, Inc. in the USA.

Other brand and product names are registered trademarks or
trademarks of their respective companies.

ABOUT THE AUTHOR

Sy Truong is President of MXI (Meta-Xceed, Inc.) They may be
contacted at:

Sy Truong Meta-Xceed, Inc. (MXI) 1751 McCarthy Blvd.
Milpitas, CA 95035 (408) 955-9333 sy.truong@meta-x.com

Jing Xu Washington Mutual Card Services Pleasanton, CA
4940 Johnson DR Pleasanton, CA 94588 (925) 738-5430 jing.xu@wamu.net

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