Figure 1: Select Preview in Mobile to generate the temporary files

With SAP BusinessObjects Dashboards 4.0 SP5 (Xcelsius 2011), you have the ability to preview and publish to an HTML5 version rather than Flash. I however am not interested in publishing to the platform for consumption on mobile devices as much as I am in retrieving the raw HTML5 files.

While poking around, I discovered that you can grab the previewed version of your dashboard in HTML5 format by searching your temporary files. The location of the dashboard preview is available in a randomized folder under:

C:\Users\<username>\AppData\Local\Temp\

Search your Temp directory and sub-directories for a file called dashboard.html. Open the directory of the file and you'll find the associated files as well. Save them off and test to your heart's delight.

Figure 2: Search for the dashboard.html file in your temporary directory to get the files for your HTML5 Dashboard

Note: You must be in preview mode in Dashboards for the files to be present. As soon as you exit the preview, the files are cleaned up.

Figure 3: Look Ma! A non-Flash Dashboard in Internet Explorer

Now you have all of the files, presumably, to test out an HTML5 version of your dashboard on the desktop and other devices without needing to publish to the platform for mobile devices.

Check out Timo's blog post on other topics regarding HTML5 Dashboards: Making A Mobile HTML5 Dashboard: Follow-Up Q&amp;A

Also, check out Tammy's blog post for a good overview of the capabilities and requirements too: Mobilizing Your Dashboards: ASUG Webcast

You can follow me on Twitter: @jwarbington

http://scn.sap.com/community/bi-dashboards/blog/2012/11/24/how-to-get-the-html5-version-of-your-dashboard-without-publishing-to-mobile?campaigncode=CRM-XM12-SOC-PROGCAMP-Twitter

Usage

• This tool can be used to compare DSO structures across different systems. e.g. Compare a DSOs structure in Dev v/s Prod/QA.
• Essential pre-check before staring any development.
• Prevent possible Go-live sync issues.
• Prod sync checks in parallel-dev environments.

User Interface

1. Compare DSO between Dev & Prod

Specify the DSO names along with RFC Connection. F4 help is available for choosing the RFC connection.

Login to the remote system:

• The output displays the list of Info objects and its presence/absence in DSO.
• The list also shows the position of the info object in the DSO structure.
• It also hows if the info object is a key field.

2. Compare two different DSOs in the same system.

Give the DSO name

Output:

Info objects missing in DSO 1:

Code

Copy paste this code in an executable program.

Text Elements

Selection Text

Text Elements

Pre-Requisites

• RFC connection must be available between systems.
• Check with your basis team for details regarding RFC connection

Acknowledgments

I would like to thank all my team mates and managers at Infosys for their constant support & encouragement.

As I wrote in my blog Analytics with SAP and R (Windows version) we can use RSAP to connect to our ERP system and play with the data.

This time I wanted of course, to keep exploring the capabilities of RSAP, but using something else. As everybody knows, I love micro-frameworks, so for R that not an exception...gladly, Rook came to the rescue...

Rook is a simple web server that will run locally and will allow us to do some really nice things...enough talk...let's go to the source code...

This is the result...

As you can see, we're getting the data from SAP to fill both SELECT's and then call out the query. We generate a PNG graphic showing the distance from the City From to the City To and then call it from our Web Page to show it on the screen.

As you can see, RSAP give us a lot of opportunities that we can take advantage by simply putting some effort and imagination. Hope this boots your R interest 

http://scn.sap.com/community/scripting-languages/blog/2012/07/06/rsap-rook-and-erp?utm_source=twitterfeed&utm_medium=twitter

As I mentioned in a recent blog about the In-memory Computing Conference 2012 (IMCC 2012) event,  I found thepresentation from Xiaoqun Clever (Corporate Officer, SAP AG Senior Vice President, TIP Design & New Applications, President of SAP Labs China) entitled “Extreme Applications – neuartige Lösungen mit der SAP In-memory Technologie“ interesting but didn’t go into details. In this blog, I wanted to describe what I found so interesting about the presentation.

The first slide that I found intriguing was the one that describes the various scenarios for HANA. You can visualize the evolution of Hana over time as moving from left to right: Accelerator -> Database -> Platform. The first thing that I noticed is that “Cloud” is not involved at all. Indeed, it is only mentioned in a single slide later in the presentation - it almost doesn’t appear to play a major role in such HANA-related endeavors.

The use case with HANA as a Database and the involvement of NetWeaver components would also cover the current intentions regarding the NetWeaver Cloud offering where HANA will be present as one possible data source. In this area, I will be curious to see what sort of functionality overlap (user management, etc) will exist between the HANA Platform and the NetWeaver Cloud as well as how the two environments will integrate with one another.

A later slide describing the scenario “HANA als Platform” is actually titled “Native HANA Applikationen”. The applications listed on the slide are either OnPremise or OnDemand (usually associated with the HANA AppCloud) applications. I started to consider what the portrayal of these applications as being “native” meant for the relationship between HANA and the Cloud. To be truthful, I’m starting to get the impression that we are slowly seeing a merging of the OnPremise and OnDemand worlds in terms of HANA runtime environments. Native applications might be able to run in both worlds since the underlying platform is fundamentally the same. Thus, other considerations (costs involved, customer presence, etc) might be important in making decisions regarding where such applications are hosted.

If we take this assumption forward a few years, you might think that a HANA-Platform-based Business Suite running as a native HANA application (and thus, perhaps easily available in an OnDemand setting) might be an option but another slide in the same presentation shows that a HANA-based Business Suite would be distinct from native HANA Apps.

What I liked about the presentation is that it reinforced my understanding of the differences between scenarios involving NetWeaver functionality and those based on native HANA functionality. What I don’t fully understand is the potential use of native functionality in scenarios where NetWeaver functionality (for example, NetWeaver Cloud) is used. Is this possible? Planned?  As things evolve, I’ll waiting to see if the scenarios with HANA as a Database can hold their own against HANA as a Platform scenarios.

http://scn.sap.com/community/cloud-computing-and-on-demand-solutions/blog/2012/07/05/do-native-hana-applications-imply-a-future-without-a-cloud-onpremise-deployment-distinction?utm_source=twitterfeed&utm_medium=twitter

Hello Everybody

This is my first blog in SDN and I would like to put down some of the limitation faced when I tried to use WEB INTELLIGENCE reporting in BI4.0 with the new connectivity option of directly using a BEX query using BICS option. I have used the .UNV universe in 3.x environment and below are some of the limitation immediately became visible  with BICS approach.

Very Important ones.

1>     BEX  built using a sub query technique:  In this case the when the “Allow External Access to this Query” is checked the Report can’t even executed in Bex( or bex web), therefore can’t be used in BOBJ platform.

2>     Slice and Dice of the dimension in the report most of the time requires refreshing of  the Report:  This is due to the inherent nature of the Data base delegated Measure setting in the Virtual universe generated at the back end during run time, and setting can’t be changed because of that. We probably have to live with this even if we don’t want the calculation of Key Figure to be done by BW for every slice and dice in WEBI.

3>     The following Filtering technique which works for .UNV universe , doesn’t work for BICS

a.       Object Base Filter ( Filter comparing the same dimension)

b.      Sub Query

c.       Feeding the Output of One query to Another

4>     Combined Query Technique( Minus, Union etc) –  The Option for this also doesn’t seem to be enabled

5>     Drilling - while I absolutely love the way the Hierarchy perform with the new BICS option, the Good Old drilling doesn’t work with BICS and I think this is huge

Some Other:

6>     Display Attribute defined in BEX with change of description of the field, ordering etc, has no bearing in the WEBI report. All display attribute defined in the Back end info Object level are available, and can be confusing for the General Users. This doesn’t necessarily be a defect but confusing for the end users , depending upon the type of end users.

7>     Due to inherent nature of BICS approach, we can’t do the following.. but I see this as more as a different way of doing things instead of limitation etc.

a.       Can’t have predefined filters as .UNV

b.      Can’t group dimension in logical group

Since I see WEBI as the most important Self service and Report authoring tool by Business rather than IT, these can cause some problem and pain points for use of WEBI down the line with BEX/BICS.

There are others smaller one, line query Stripping etc… Let’s see if you faced similar issues and have a healthy discussion about these.

Thanks

Arun

http://scn.sap.com/community/businessobjects-web-intelligence/blog/2012/06/14/some-limitation-in-web-intelligence-when-using-directly-with-bex-querybics-in-bi-40?utm_source=twitterfeed&utm_medium=twitter

Something that piqued my curiosity lately was the developments with SAP HANA and R (good overview here).  This is definitely a new and exciting direction for SAP, with creating a well structured, and organised 'Big Table' option for in memory computing, and then going the extra mile to embed a specialised Open Source Statistical Computing package (R) in it - making the fore front of the world of statistical analysis open to those that dare.

This is utterly brilliant, but the problem is that I can't access it as I don't have access to a SAP HANA instance (nor would most people).  It is also heavily geared to 'Big Data', when there is still an awful lot to be gained from small, and mid-range data analysis arenas (resisting the temptation about size and clichés).

This has definitely touched on my hackers itch, and in response to this I've created one more Scripting Language Connector for R - RSAP.

The idea of this is to enable RFC calls (using the SAP NW RFC SDK) where any table contents are returned asdata.frames (in R parlance).

Once you have this data in R, then the world is your oyster - it is up to your imagination as to what you do with it.  To give an overview of how it works, and what you can do, I'm going to step through the process of installing and using RSAP.

Obtaining and Installing

Firstly you need to install R.  I recommend using RStudio as it is a comfortable graphical user interface - you can get it from here.  

Under debian (read Ubuntu) flavoured Linux you can install R first before downloading/installing RStudio using:

sudo apt-get install r-base-core r-base-dev r-base-html r-recommended

SAP NW RFCSDK

The SDK is available from the SAP Service Market Place SWDC - this is a forum discussion on getting ithttp://scn.sap.com/thread/950318

If you have (like me) installed the NPL SAP Test Drive instance, then the SAP NW RFC libs exist in the /usr/sap/NPL/SYS/exe/run directory, the only problem being that it does not contain the C header files (really - SAP should make this available on SDN).

RSAP

Download or clone the RSAP project source from https://github.com/piersharding/RSAP

Building

Ensure that the R library prerequisites are installed.  To do this there is a helper script in the RSAP source code directory.  cd to the source directory (downloaded above) - in my case /home/piers/git/public/RSAP - and run the following:

R --no-save < install_dependencies.R

This will prompt to install the packages yaml, reshape, plotrix, and RUnit.

To build and install the RSAP package, cd to the source directory (downloaded above) - in my case /home/piers/git/public/RSAP - run the following:

R CMD INSTALL --build --preclean --clean --configure-args='--with-nwrfcsdk-include=/home/piers/code/sap/nwrfcsdk/include --with-nwrfcsdk-lib=/home/piers/code/sap/nwrfcsdk/lib' .

You must change the values for --with-nwrfcsdk-include and --with-nwrfcsdk-lib to point to the directory locations that you have downloaded the SAP NW RFC SDK to.

Under Linux, it is also likely that you need to add the lib directory to the LD cache or set the LD_LIBRARY_PATH variable.

Setting the LD Cache:

as root, edit /etc/ld.so.conf and add the lib path from above to it on it's own line.  Now regenrate the cache by executiong 'sudo ldconfig'.

Setting LD_LIBRARY_PATH

You must ensure that the following environment variable is set in all your shells:

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/nwrfcsdk/lib

The easiest way to do this is to add the above line to your $HOME/.bashrc file so that it happens automatically for all future shells.

Does it work?

Once the build and install of the RSAP package is complete, now you should test to make sure it's all working.

Change to the package source code directory (you are probably still there from the above activities), and launch either R or RStudio.

From the R command line try the following:

> library(RSAP)

Loading required package: yaml

>

You should get the above confirmation message that the dependent yaml package has been loaded.  Now we are ready to try some R wizardry.

How to work with RSAP

Lets work through the general process steps for interacting with SAP.

Connecting to SAP

Using RSAP we need to establish a connection to SAP.  For this you need an account that has the appropriate access for RFC calls, and functionality access.  Connections can be built in two ways - directly passing connection parameters:

>     conn <- RSAPConnect(ashost="nplhost", sysnr="42",

                          client="001", user="developer",

                          passwd="developer", lang="EN")

>

Or using a YAML encoded file that contains the connection details:

> conn <- RSAPConnect("sap.yml")

>

The sap.yml file is structured like:

ashost: nplhost

sysnr: "42"

client: "001"

user: developer

passwd: developer

lang: EN

trace: 1

The above activates the trace functionality in NW RFC SDK.  This will create trace files in the current working directory, and are invaluable for debugging connectivity problems.

Calling SAP

Now we have the connection object, we can get connection info with it:

info <- RSAPGetInfo(conn)

Query the system with:

res <- RSAPInvoke(conn, "<RFC Function Name", parms)

Or close the connection:

RSAPClose(conn)

RSAPInvoke() is what we are most interested in, and we need to pass the parameters as a series of nested named lists.  The classic example is RFC_READ_TABLE:

parms <- list('DELIMITER' = '|',

              'FIELDS' = list(FIELDNAME = list('CARRID', 'CONNID', 'PRICE',

                                               'SEATSMAX', 'SEATSOCC')),

              'OPTIONS' = list(TEXT = list("CARRID = 'AA' ", " AND CONNID = 0017 ")),

              'QUERY_TABLE' = 'SFLIGHTS2')

res <- RSAPInvoke(conn, "RFC_READ_TABLE", parms)

The names must correspond directly to the parameter and structure (for tables) names, and use numeric and character types as appropriate.

The other thing that is really important to get your head around is that R data structures are column oriented, which means we have to think differently about tables that we get from SAP.  Tables in SAP translate to lists of vectors where the outer list is a list of column names (a slightly loose analogy but it will do) and the vectors hang off these column names corresponding to all the values in that column down the rows.

Working through the examples in get_flights.R

In the source code package there is an example script - get_flights.R.  It uses the standard demonstration data for the Flight Data system contained in table SFLIGHT2.  Let's look at what this does.

Load libraries:

> library(RSAP)

Loading required package: yaml

> library(reshape)

Loading required package: plyr

  Attaching package: ‘reshape’

  The following object(s) are masked from ‘package:plyr’:

      rename, round_any

> library(plotrix)

>

We now have all the necessary libraries for the rest of the examples.

conn <- RSAPConnect("sap.yml")

parms <- list('DELIMITER' = ';',

              'QUERY_TABLE' = 'SFLIGHTS2')

res <- RSAPInvoke(conn, "RFC_READ_TABLE", parms)

RSAPClose(conn)

sflight = res$DATA

flds <- sub("\\s+$", "", res$FIELDS$FIELDNAME)

sflight <- data.frame(sflight, colsplit(sflight$WA, split = ";", names = flds))

This connects to SAP, calls RFC_READ_TABLE to get the contents of SFLIGHT2, and sets the column delimiter for that table as ';'.  We close the connection and copy the table data from the return parameter res$DATA (see RFC_READ_TABLE in transaction SE37) into sflight.  We also grab the field names returned in table FIELDS, and remove the whitespace at the end.  Next - this is where the importance of the ';' delimiter is - using the colsplit() function from the reshape package, we split return DATA into columns named by the FIELDS that RFC_READ_TABLE provided us.

Now we have a data.frame that looks a lot like the table SFLIGHT2 when viewed in transaction SE16.

sflight <- cbind(sflight, FLIGHTNO = paste(sub("\\s+$", "",

                                           sflight$CARRID),sflight$CONNID, sep=""))

sflight$SEGMENT <- paste(sflight$AIRPFROM, sflight$AIRPTO, sep=" - ")

sflight$CARRNAME <- sub("\\s+$", "", sflight$CARRNAME)

sflight$DISTANCE <- as.numeric(lapply(sflight$DISTANCE,

                                      FUN=function (x) {sub("\\*","", x)}))

sflight$DISTANCE <- as.numeric(lapply(sflight$DISTANCE,

                                      FUN=function (x) {if (x == 0) NA else x}))

sflight[sflight$CARRNAME == 'Qantas Airways','DISTANCE'] <- 10258

This next chunk created  new vectors (columns) FLIGHTNO combined from CARRID and CONNID, SEGMENT from AIRPFROM and AIRPTO, and cleaned vectors CARRNAME, and DISTANCE.

Now create some aggregated views, to generate visualisations from:

airline_avgocc <- aggregate(data.frame(SEATSMAX=sflight$SEATSMAX,

                                       SEATSOCC=sflight$SEATSOCC,

                                       OCCUPANCY=sflight$SEATSOCC/sflight$SEATSMAX),

                            by=list(carrname=sflight$CARRNAME), FUN=mean, na.rm=TRUE)

airline_sumocc <- aggregate(data.frame(SEATSOCC=sflight$SEATSOCC),

                            by=list(carrname=sflight$CARRNAME), FUN=sum, na.rm=TRUE)

Show a pie chart  - sum of airline occupancy as a share of market:

x11()

lbls <- paste(airline_sumocc$carrname, "\n", sprintf("%.2f%%",         

        (airline_sumocc$SEATSOCC/sum(airline_sumocc$SEATSOCC))*100), sep="")

pie3D(airline_sumocc$SEATSOCC, labels=lbls,

      col=rainbow(length(airline_sumocc$carrname)),

      main="Occupancy sum share for Airlines", explode=0.1)

Create a Stacked Bar Plot with Colors and Legend showing a summary of occupancy by segment and carrier - to do this we need to generate a summary (aggregate), and fill in the missing combinations of the grid, and then switch the orientation of rows for columns to present to the plotting funcitons:

d <- aggregate(SEATSOCC ~ CARRNAME:SEGMENT, data=sflight, FUN=sum, na.rm=FALSE)

d2 <- with(d, expand.grid(CARRNAME = unique(d$CARRNAME), SEGMENT = unique(d$SEGMENT)))

airline_sumsegocc <- merge(d, d2, all.y = TRUE)

airline_sumsegocc$SEATSOCC[is.na(airline_sumsegocc$SEATSOCC)] <- 0

# switch orientation to segment * carrier

counts <- data.frame(unique(airline_sumsegocc$CARRNAME))

for (a in unique(airline_sumsegocc$SEGMENT)) 

    {counts <- cbind(counts,

     airline_sumsegocc$SEATSOCC[which(airline_sumsegocc$SEGMENT == a)]);}

counts[,1] <- NULL

colnames(counts) <- unique(airline_sumsegocc$SEGMENT);

rownames(counts) <- unique(airline_sumsegocc$CARRNAME);

x11()

barplot(as.matrix(counts), main="Total Occupancy by Segment and Carrier",

        ylab="Number of Seats",

        col=rainbow(dim(counts)[1]),

        ylim=c(0, 15000), legend = rownames(counts))

Lastly - we create a simple performance indicator using a time series comparison of different airlines:

# performance by airline over time - dollars per customer KM

sflight$FLDATEYYMM <- substr(sflight$FLDATE, start=1, stop=6)

d <- aggregate(data.frame(PAYMENTSUM=sflight$PAYMENTSUM,

                          SEATSOCC=sflight$SEATSOCC,

                          DISTANCE=sflight$DISTANCE,

                          PERFORMANCE=(sflight$PAYMENTSUM/(sflight$SEATSOCC *

                             sflight$DISTANCE))),

               by=list(carrname=sflight$CARRNAME,

                       fldateyymm=sflight$FLDATEYYMM),

               FUN=sum, na.rm=TRUE)

d2 <- with(d, expand.grid(carrname = unique(d$carrname),

                          fldateyymm = unique(d$fldateyymm)))

agg_perf <- merge(d, d2, all.y = TRUE)

agg_perf <- agg_perf[order(agg_perf$carrname, agg_perf$fldateyymm),]

agg_perf$PERFORMANCE[is.na(agg_perf$PERFORMANCE)] <- 0

# create time series and plot comparison

perf_series <- data.frame(1:length(unique(agg_perf$fldateyymm)))

for (a in unique(agg_perf$carrname))

    {perf_series <- cbind(perf_series,

       agg_perf$PERFORMANCE[which(agg_perf$carrname == a)]);}

perf_series[,1] <- NULL

colnames(perf_series) <- unique(agg_perf$carrname);

# convert all to time series

for (a in length(unique(agg_perf$carrname)))

    {perf_series[[a]] <- ts(perf_series[,a], start=c(2011,5), frequency=12)}

# plot the first and line the rest

x11()

ts.plot(ts(perf_series, start=c(2011,5), frequency=12),

           gpars=list(main="Performance: dollar per customer KM",

                      xlab="Months",

                      ylab="Dollars",

                      col=rainbow(dim(perf_series)[2]), xy.labels=TRUE))

legend(2012.05, 3.2, legend=colnames(perf_series),

                     col=rainbow(dim(perf_series)[2]), lty=1, seg.len=1)

Hopefully, I've shown that there is a lot that can be done with R - especially in the area of adHoc advanced business intelligence and data analysis.  I have not really even scratched the surface in terms of what R can offer for advanced statistical analysis and modelling - that is where the true wizards live.

I would love to hear back from anyone who tries RSAP out - issues and user experiences alike.

Edit:

I should note that Alvaro has been here before me with OData/JSON/and R -http://scn.sap.com/community/netweaver-gateway/blog/2012/04/06/when-r-met-sap-gateway

References:

• Post on SAP HANA and R from Alvaro

Basic R Tutorials

• Quick R
• The R Cookbook
• The R Statistics Blog
• Producing simple Graphs with R
• The CRAN project Documentation

Secure Sockets Layer (SSL) with HANA and BI4 Feature Pack 3 requires configuration on the HANA server and BI4 server.  The following steps will show how to configure SSL using OpenSSL and a certificate obtained by from a Certificate Authority (CA).

OpenSSL Configuration

This blog will cover the OpenSSL Crypto Library, however HANA can also be configured using the SAP Crypto Library.

Confirm that OpenSSL is installed

shell> rpm -qa | grep -i openssl

openssl-0.9.8h-30.34.1

libopenssl0_9_8-32bit-0.9.8h-30.34.1

openssl-certs-0.9.8h-27.1.30

libopenssl0_9_8-0.9.8h-30.34.1

Confirm that OpenSSL is 64-bit

shell> file /usr/bin/openssl

openssl: ELF 64-bit LSB executable, x86-64, version 1 (SYSV), for GNU/Linux 2.6.4, dynamically linked (uses shared libs), stripped

Confirm there is a symlink to the libssl.so file

If not, create one as the root user

shell> ln -s /usr/lib64/libssl.so.0.9.8 /usr/lib64/libssl.so

SSL Certificates

This blog won’t go into details of how SSL works, but in generic terms you’ll need to create a Certificate Singing Request (CSR) from the HANA server and send that to a CA.  In return, the CA will give you a Signed Certificate and a copy of their Root CA Certificate.  These, then need to be setup with HANA and the BI4 JDBC and ODBC drivers.

Creating the Certificate Signing Request

shell> openssl req -new -nodes -newkey rsa:2048 -keyout Server_Key.key -out Server_Req.csr -days 365

Fill out the requested information according to your company:

-----
You are about to be asked to enter information that will be incorporated
into your certificate request.
What you are about to enter is what is called a Distinguished Name or a DN.
There are quite a few fields but you can leave some blank
For some fields there will be a default value,
If you enter '.', the field will be left blank.
-----
Country Name (2 letter code) [AU]:
State or Province Name (full name) [Some-State]:
Locality Name (eg, city) []:
Organization Name (eg, company) [Internet Widgits Pty Ltd]:
Organizational Unit Name (eg, section) []:
Common Name (eg, YOUR name) []:
Email Address []:

Please enter the following 'extra' attributes
to be sent with your certificate request
A challenge password []:
An optional company name []:

This will create two files

• Key: Server_Key.key
• CSR: Server_Req.csr

The CSR needs to be sent to the CA, which in turn will give you a signed certificate and their Root CA Certificate.

Convert the Root CA Certificate to PEM

The Root CA Certificate may come in the DER format (.cer extension), HANA requires the cert in PEM format.  Therefore, we will need to convert it using the command

shell> openssl x509 -inform der -in CA_Cert.cer -out CA_Cert.pem

HANA SSL Configuration

Copy both the Signed Cerficiate and Root CA Certificate to the HANA server.  For HANA SSL to work, we need to create two files:

• key.pem
• trust.pem

The key.pem key store file contains the certificate chain, which includes your servers key (Server_Key.key), the CA’s Signed Certificate and the Root CA Certificate.  Whereas the trust.pem trust store file contains the Root CA Certificate.

Create the key.pem and trust.pem trust stores

key.pem

shell> cat Server_Cert.pem Server_Key.key CA_Cert.pem > key.pem

trust.pem

shell> cp CA_Cert.pem trust.pem

Copy the files to the user's home directory

In the user's home directory create a .ssl directory and place both the key.pem and trust.pem files here,

Configure the certificates in HANA

Once the key.pem and trust.pem files have been created they need to be configured in HANA.

In HANA Studio go to

• Administration
• Configuration tab
• Expand indexserver.ini
• Expand communication
• Configure the entries related to SSL

Start and Stop HANA to pick up the SSL configuration

• HDB stop
• HDB start

HANA Studio Configuration

When setting up the connection to HANA, check the option 'Connect using SSL', as seen below.

To confirm the connection has SSL, look for the lock icon on the server icon, as seen below.

BI4 Feature Pack 3 SSL Configuration

SSL in BI4 needs to configured for the HANA connectivity you plan to use. 

JDBC Configuration

For JDBC SSL configuration, we’ll need to add the trust.pem trust store to the Java Key Store (JKS) using the keytool utility provided by the JDK/JRE.  This is done via the command line.  Change the paths for your own configuration:

Add trust.pem to the JKS

C:\Documents and Settings\Administrator>"C:\Program Files (x86)\SAP BusinessObjects\SAP BusinessObjects Enterprise XI 4.0\win32_x86\jre\bin\keytool.exe" -importcert -keystore "C:\Program Files (x86)\SAP BusinessObjects\SAP BusinessObjects Enterprise XI 4.0\win32_x86\jre\lib\security\cacerts" -alias HANA -file trust.pem

You will be prompted for the keystore password.  The default password is: changeit

When prompted to 'Trust this certificate' enter yes.  The alias can be any value, however it must be unique in the keystore.

Confirm that your certificate has been added to the keystore

C:\Documents and Settings\Administrator>"C:\Program Files (x86)\SAP BusinessObjects\SAP BusinessObjects Enterprise XI 4.0\win32_x86\jre\bin\keytool.exe" -list -keystore "C:\Program Files (x86)\SAP BusinessObjects\SAP BusinessObjects Enterprise XI 4.0\win32_x86\jre\lib\security\cacerts" -alias HANA

If successful, you will see trustedCertEntry in the output, as below

Information Design Tool  (IDT) Configuration

In IDT, the connection will need to be setup with the JDBC Driver Property encrypt=true to make the connection use SSL when connecting to HANA,

ODBC Configuration

Once the HANA client driver has been installed, you can set up a ODBC connection for HANA.  To connect via SSL, check the box 'Connect using SSL', as below:

If you added any Special property settings', they won't be displayed in the driver configuration.  To view them, launch the Windows Registry Editor and go to the key:

• HKEY_LOCAL_MACHINE\SOFTWARE\Wow6432Node\ODBC\ODBC.INI\<Your Data Source Name>

Installing the CA Root Certificate

Depending on which CA you get the certificate signed from, you may run into SSL errors.  For example, in Crystal you may see this error,

To resolve this, install the CA Root Certificate allowing it to be trusted by the server.

• Copy the CA Root Certificate to the machine where the error is coming from

• Double click on the certificate and click 'Install Certificate'

• Click next

• Select the first option and click next

• Click finish

Confirming if SSL is being used

Using a tool like Wireshark, the communication between the server and client can be traced, as seen below to verify that SSL is being used.

http://scn.sap.com/community/in-memory-business-data-management/blog/2012/05/30/ssl-with-hana-and-bi4-feature-pack-3?utm_source=twitterfeed&utm_medium=twitter

Two major improvements related to Enterprise Data Warehousing that can be achieved by migrating SAP NetWeaver BW to the SAP HANA database platform are (1) the dramatic improvement in data load times for Data Store Objects being the data containers within BW, and (2) the significantly boosted performance while reporting from them. With the latest BI Content releases SAP NetWeaver 7.30 BI Content 7.37 SP 01 or SAP NetWeaver 7.31 BI Content 7.47 SP 01, a large fraction (about 2/3) of DataStore Objects that were delivered so far with BI Content have now been prepared for HANA-optimization.

When you copy these HANA-prepared DataStore Objects (DSO) from the delivered to the active version they will be created automatically as SAP HANA-optimized DataStore Object side-stepping the manual conversion step from standard to HANA-optimized DSO. The delivery of DataStore Objects prepared for HANA-optimization marks the next consequent step towards total cost of administration reduction after the migration of all relevant data flows to SAP BW 7.x technology. This is one important prerequisite for HANA-optimization of involved DataStore Objects (migrated data flows were delivered with SAP NetWeaver 7.30 BI Content 7.36 SP 02 or SAP NetWeaver 7.31 BI Content 7.46 SP 02). If DataStore Objects contain data, you cannot avoid the manual conversion step to HANA-optimization. Therefore, you best benefit from the HANA-prepared DataStore Objects when you copy new data flows from the delivered to the active version in your BW system powered by SAP HANA.

You can benefit from automatic creation of HANA-optimized DataStore Objects during BI Content activation if you are using (1) SAP HANA database as of release SAP HANA 1.0 Support Package 03 and (2) SAP NetWeaver BW 7.3, Support Package Stack 07 or SAP NetWeaver BW 7.3, including Enhancement Package 1, Support Package Stack 04.

Find the complete list of all 1025 HANA-optimized DataStore Objects attached to note 1708668.

http://scn.sap.com/community/data-warehousing/business-content-and-extractors/blog/2012/05/29/shipment-of-bi-content-for-sap-netweaver-bw-powered-by-sap-hana-datastore-objects-are-now-prepared-for-sap-hana-optimization?utm_source=twitterfeed&utm_medium=twitter