SAS Tips and Tricks consists of half days/full days of knowledge transfer in SAS programming language and are organized by an motivated SAS Expert who combines theory and demonstration to helps you refreshing your SAS skills, discover news technics and meet other experts.
Organized for employees, sessions are organized on a monthly basis in our business center (near Brussels-North train station) and, to guaranty an optimal quality, the number of participants is limited to 8 persons. Contact us to assist to a session (scheduled or not) or click the register button in the course details, we will recontact you with more informations.
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Log files contains tons of useful information, they help you when you have syntax errors, warnings and notes but you could use your logs in order to monitor your daily processes and identify the potential bottlenecks.
Windows scheduler can be used to execute automatically SAS code at specific moment of the day or at specific days of the month. They execute the same code every time but, thanks to macro, the output result could change thanks to the environment (data, time, user (etc.).)
Gathering job statistics could help you to detect proactively problems in your data by comparing current values with their estimated values. The idea behind is to collect as much as possible information on your daily run processes (number of records, times it take, number of missing (etc.)) and store them in an historical table. If the values of the current run differs with the values of previous run for the same jobs, this could indicate potential problem.
Getting quickly metadata information on your datasets could be useful in some context of conditional execution of SAS programs (e.g.: Don't execute this step if empty dataset). Different methods exists to achieve that: using metadata functions, using Proc contents, or dictionary tables.
Using a SAS table to control job execution can be useful when lot of jobs have to be scheduled regularly but depending on circumstance some don't have to be scheduled. In normal situation we would have to adapt the job scheduler and this could be time consuming. You could use instead a SAS Dataset or Excel spreadsheet where all the jobs are listed with a flag variable indicating the list of jobs to schedule.
The SAS hash object is meant to enable you to quickly and efficiently store, search, and retrieve data based on lookup keys , Conceptually, the hash object provides programmers the means to easily define and utilize a hash table within the Data Step.
XML files are not simple line of records, they have a hierarchy and they are not easy to create programmatically. Sometimes software cannot create complex XML files and it becomes mandatory to pass through this step. In this tips and tricks, we will see how we can create XML in Data Step.
A Slowly Changing Dimension (SCD) is a dimension that stores and manages both current and historical data over time in a data warehouse. It is considered and implemented as one of the most critical ETL tasks in tracking the history of dimension records. Different SCD strategies could be implemented and this tips and tricks is focused on SCD1 where records are updated no history is kept and SCD2 where history is kept,
It's not always easy to choose between Proc SQL and Data Step programming. In this tips and tricks, we will see the big differences between Proc SQL and Data Step and list the pro's and the con's of both of them.
Creating or reading flat files from SAS can be done in several ways in SAS: proc import, proc export are common examples. When flat files are not simple line of records, it becomes impossible to use default technics and Data Step programming becomes required.
SAS macro language allows you to process dynamically all the files of a directory or all the files of a library . Different technic exist depending on the nature of the files. This tips and tricks discuss the case when your files are datasets present in a single library and discuss the case when we manipulate flat files in a folder structure.