How to be efficient as a GIS professional (part 3)

6. Automate, automate, automate

Whatever you are doing, take a second to think whether you will need to run the sequence of steps you’ve just completed again. It may seem first that you are very unlikely to run the same sequence of steps again, but in fact you may find yourself performing them over and over again later on.

Automating is not only about saving the time. It is also about the quality assurance. When you are doing something manually, there is always a chance to forget a certain step or detail which can potentially lead to an error. When having the workflow automated, you can always see what steps are being performed. An automated workflow is already a piece of documentation which you can share with others or use yourself as a reference.

Don’t trust your memory: you think you know what columns you’ve added to the table and why, yeah. Get back in two weeks and you will be surprised by how much of those memories you have left. If you will leave the job and get the work over to a new person, she will be happy to inherit a well maintained documentation and discrete description of the workflow he will be responsible for.

Considering desktop GIS automation, think about using Python for geospatial operations (think truncating tables + appending new data + perform data checks). For database automation, use SQL (add new columns + alter columns data type). Feel free to build SQL scripts with commands for adding/deleting/calculating columns and copying data, too. By preserving those scripts, you will always be able to re-run them on a another table, in another database or modify the script to match your needs. This gives you a way into looking at changes performed in your database. This is just like adding a field manually and then writing down that you have added field of type X into table Y at time Z. It is just so much easier to build a SQL script to avoid doing that.


Another advantage of the SQL for data processing is that it is very vendor neutral and can be executed either as is or with really minor adjustments on most DBMS platforms. This is applicable to SQL spatial functions which provide ISO and OGC compliant access to the geodatabase and database, too. Being able to execute SQL queries and perform data management operation is really advantageous when you work in a large IT environment. This might be helpful because you won’t always have the network connection to the production environment for data update and using ArcGIS might not be possible. Running a Python script would require having the Python installation on some machine and if you use arcpy – ArcGIS Desktop. Running a SQL code which has no dependencies might be your only alternative.

Many folks don’t know that one can use pure SQL with an enterprise geodatabase stored in any DBMS supported. This is just a short list of what you can do with SQL:

8. Python, Python, Python

I have blogged about using spatial functions of SQL Server earlier. Remember that you can also execute some of the SQL from Python code when using the arcpy.ArcSDESQLExecute class. Here is the SQL reference for query expressions used in ArcGIS some of which you can use in the arcpy.da cursors where clauses. Learn some of the useful Python libraries which could save you some time. Look at:

  • Selenium for automating ftp data download if this happens often and you have to browse through a set of pages;
  • scipy.spatial module for spatial analysis such as building Voronoi diagrams, finding distances between arrays, construct convex hulls in N dimensions and doing many other things;
  • Numpy, a fundamental package for scientific computing with Python, for handling huge GIS datasets (both vectors and rasters) with arcpy.

Read more about What are the Python tools/modules/add-ins crucial in GIS and watch an Esri Video on Python: Useful Libraries for the GIS Professional.

Get a chance to learn more about the SQL and Python and how you could take advantage of them in your work!

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