Netezza and Teradata are both great examples of distributed processing databases that combine the power of SAS with their own platform to deliver a powerful analytics tool.
The problem? Clients rarely use it. We have seen several clients who possess this functionality. Some of who purchased the DB at the request of the analysts, only to see them never use the processing. The issues usually arise from old code, new analysts, ad-hoc scenarios, etc, etc.
If your organization is working with an in database system like Teradata or Netezza with SAS, let us know. We have put together a guide for analyst to use. This gives you code to borrow for the some of the most resource intensive SAS processing.
Here are a quick reference to some of the SAS docs:
We write a LOT of SQL here and although SQL is a powerful database language, it can be tedious. So here is one tip for shortening all that typing.
Typical join sytax:
from one_table join another_table on one_table.column_1 = another_table.column_1 and one_table.column_2=another_table.column_2
where some_column > someother_column ;
Not too bad, right?
In order for this tip to work, you must be joining on columns with the same name (ie. column_1 and column_2 have the same name in both tables).
Here it is:
from one_table join another_table using (column_1, column_2)
where some_column > someother_column ;
Now, in our example it's not a drastic difference in coding, but as any programmer knows, this shorthand example doesn't accurately represent the real world. So give this syntax a try on your next project and let us know if it doesn't save you some typing.
As we begin to add posts in 2011, we stepped back to look at our business and our blog. We realized that the two are perfectly aligned. Although the majority of our focus is within the SAS product suite, our focus is marketing analytics and operations.
Given that, it is time for us to expand our commentary. So, in the coming weeks you will begin to see more content regarding some of our other technology partners including Teradata, Netezza and Unica.
If you have a question about a particular technology or topic, we'd love to hear from you. Comment below or email us a email@example.com .
Fastexport is the fastest way to get large data out of teradata. Fastexport utilizes multiple connections to deliver data and therefore speeding up the transfer of data between Teradata and SAS.
Here are a few examples of fastexport.
/* libname statement*/
libname teradb teradata username=&un password=&pw dbsliceparm=all;
/* explicit sql */
connect to teradata(username=&un password=&pw dbsliceparm=all);
How do you know if fastexport was used?
Use this option:
options sastrace=',,,d' sastraceloc=saslog;
If it is working, you should see something in your log like:
Select was processed with fastexport.
There are many other factors that come into play if fastexport doesn't work. Check the requirements on the SAS support page for troubleshooting.
If you have worked with marketing technologies for any length of time, you've encountered this problem. How can we integrate our CRM with the rest of our organization? How does CRM interact with our call center, website, applications, database, loyalty system, etc., etc.
We've been there.
Throughout our travels, we've picked up a few tips. Hopefully they'll help you.
- Tight integration is dangerous. Just don't do it. - Marketing technology changes faster than fashion. Today's latest and greatest is quickly replaced with tomorrow's new market maker.
- Integrate through marketing concepts not technical application specs. - Abstracting technologies through the use marketing concepts like 'campaign', 'offer', 'contact history', 'registration', 'enrollment', etc. Define what these mean for the organization and build a data structure flexible enough for all applications to contribute to those concepts.
- Databases and services are the lifeline. - Long term success hinges on ease of use and flexibility. Simple services allow for plug and play scenarios. Well designed databases create environments that record interrelated transactions based on their role or concept. This makes business people happy. They can measure, analyze and predict without spending precious hours compiling, cleaning, and organizing data.
- Think replaceable. - Always remember that what you are adding to your technology stack could be replaced in a year and you will need to re-integrate something else. How much of your current work will be thrown away? Minimize the one-time development and maximize your efficiency and cost savings to the organization over the long haul.
We like to think we aren't integrating technology. We are simply making all of our applications play nicely together.
There is much more to this topic, but these 4 tips can minimize your stress for ears to come.
As any good analyst knows, working with data is not the problem. Good analysts have the skill necessary to combine, split, merge, slice, aggregate, or summarize data any way you can imagine. However, is that enough?
What good does data do if you can't communicate its meaning in a logical way. The day of sending a spreadsheet with pivot tables are heading out the door. Today users are wanting more. They are expecting more. And why is that?
Here are a few reasons users expect more from their data experiences:
- Google Analytics
These are just some of the companies leading the way in user interface. The days of cheezy HTML or excel graphs won't cut it. Users quickly see they have to work to understand the information and move on.
A complete toolbox of data tools and a team of professionals with tool experience. Today's environment requires (along with some of our favorite vendors/partners):
- a storage solution
- an analysis tool
- a display layer
If your organization isn't firing on all analytic cylinders, let us know. We have the tools, relationships, and people to move you to the next level. We have a proven track record of moving the needle through the integration of data into decision making.
NOTE - SAS changed the default settings for fastload in SAS9. This has not been an improvement. SAS has documented how to change the setting back to the previous default in their note here... click here
The fastload facility for Teradata through SAS ACCESS is one that every analyst loading data into Teradata should be aware of. This tool allows you to pump data from SAS to Teradata in the quickest manner. The target table must be empty. There are other limitations as well, but most are uncommon problems.
To use the fastload option, follow the example below (SAS9 and above may require more manual settings to see max performance):
data td_lib.empty_table (bulkload=YES);
proc append data=source_table
If your organization uses Teradata and could use some help utilizing the full power of SAS with Teradata, we are available to assist you.