What do you do if you're overwhelmed by large datasets in GIS?

2 Use data formats and compression

Another way to handle large datasets in GIS is to use appropriate data formats and compression methods. Data formats and compression can affect how your data is stored, accessed, and displayed. For example, you can use vector tiles instead of vector layers to render your data dynamically and efficiently. Vector tiles are small chunks of data that are created on the fly and only load the features that are visible at a certain zoom level. You can also use raster compression techniques such as JPEG, PNG, or LZW to reduce the file size of your images without losing quality.

3 Apply filters and queries

A third way to deal with large datasets in GIS is to apply filters and queries. Filters and queries allow you to select and display only the data that meets certain criteria or conditions. For example, you can filter your data by attribute, location, or time to narrow down your analysis or visualization. You can also use queries to perform calculations, join tables, or create subsets of your data. Filters and queries can help you extract relevant information and insights from your data.

4 Use cloud computing and storage

A fourth way to handle large datasets in GIS is to use cloud computing and storage. Cloud computing and storage enable you to access, process, and store your data remotely on servers or platforms that have more capacity and power than your local computer. For example, you can use services such as Google Earth Engine, ArcGIS Online, or QGIS Cloud to perform spatial analysis, create web maps, or share your data online. Cloud computing and storage can help you overcome the limitations of your hardware and software.

5 Learn new tools and techniques

A fifth way to deal with large datasets in GIS is to learn new tools and techniques. GIS is a constantly evolving field that offers new solutions and opportunities for working with large datasets. For example, you can use tools such as GeoPandas, Dask, or PySpark to manipulate and analyze large datasets using Python. You can also use techniques such as machine learning, deep learning, or big data analytics to discover patterns, trends, or anomalies in your data. Learning new tools and techniques can help you enhance your skills and knowledge in GIS.

6 Seek help and feedback

A sixth way to handle large datasets in GIS is to seek help and feedback. GIS is a collaborative and interdisciplinary field that requires communication and cooperation with others. For example, you can ask for help from your colleagues, mentors, or experts who have experience or expertise in working with large datasets. You can also seek feedback from your clients, users, or stakeholders who have different perspectives or expectations from your data. Seeking help and feedback can help you improve your work and solve problems in GIS.