Most foresters may never have the need or desire to learn SQL, and that’s okay. Nevertheless, I think there are good business reasons for learning the language of relational databases. Foresters who know SQL have an appreciation for how data is stored, why it’s important for data to be clean and well formatted, and can unlock insights in data by asking the right questions.

My introduction to SQL was with Microsoft Office’s Access database system. As a beginner, Access provided a good safety-net, so-to-speak, while learning how to build proper table relationships and to structure queries. If Microsoft Access is available, this is a great place to start in my opinion.

This post will not teach SQL, but it will provide reasons why I think it is a valuable skillset for forestry professionals.

What is SQL?

• SQL (Structured Query Language) is the standard language used to ask questions of, and pull information from, relational databases — such as the databases behind most modern forest inventory and GIS systems. There are two dialects of SQL – Data Definition Language (DDL) which is used to create the database structure (i.e., schema) and Data Manipulation Language (DML) which is used to interact with the actual data, and most relational databases support both.
• At its core, SQL is built around a handful of simple commands: SELECT (retrieve data), WHERE (filter it), JOIN (combine tables), and GROUP BY (summarize it) — you don’t need to master all of SQL to get real value.
• It’s a non-proprietary tool used by many databases — the same basic syntax works across many platforms.

Why is it a useful skillset to know?

• Speed and independence — instead of asking others for help or waiting for a custom report, you can build queries to extract stand, species, or volume data as needed.
• Better questions lead to better answers — writing a query forces you to think precisely about what to ask – such as “all loblolly stands over 25 years old with a site index above 70”, which helps sharpen analysis skills.
• Career leverage — as forestry operations lean more on data-driven decision-making, foresters who can bridge field knowledge and database skills provide additional business value.
• Error-checking — being able to query raw data makes it easier to find mistakes in cruise data, GIS attributes, harvest data, or inventory summaries before they lead to misleading results or poor decisions.
• Build better tools – leverage SQL skills to create new databases to suit your own personal or business needs. If you are a small company or a consultant working alone, then creating your own database solutions may be preferred over spending money on expensive commercial products.

Where is SQL most valued in forest business?

• Forest inventory management — querying cruise and plot data to summarize volume, basal area, or species composition by stand, compartment, or ownership.
• GIS and mapping systems — most GIS platforms store attribute data in relational databases under the hood, so SQL skills let you filter and analyze spatial data beyond what other systems might offer.
• Harvest scheduling — querying mill delivery, load ticket, or contract data to track volumes, payments, and scheduling across multiple jobs or vendors.
• Timberland valuation and reporting — pulling and summarizing data across large ownerships for appraisal, certification (SFI/FSC) audits, or annual reporting to landowners and stakeholders.

In my opinion, it is a good additional skillset for foresters to at least have a basic understanding of SQL. You don’t have to be a technology guru or a database wizard to learn SQL. If your goal is to work with databases consistently, then being proficient with SQL is strongly encouraged. Foresters who don’t need direct access to query or analyze data can still gain tremendous business value from knowing basic SQL.

There are plenty of free online resources available for those who want to learn SQL. W3Schools provides a great introduction to SQL and other common programming languages as well.

Categories: Data Analytics Forest Inventory Geospatial Record Storage Technology Investments

Tagged as: sql Technology

JwL