Analytics

How to work with date fields in Data Engineering

As GIS professionals, it’s probably safe to say that we appreciate the spatial nature of things; the concepts of location, proximity, and contiguity permeate the way we think when trying to understand data and solve problems.

But what about time? Everything happens somewhere and at some time, doesn’t it?

The temporal nature of our data can work in conjunction with the spatial to help us better model and understand the world through our screens. This information usually comes to us in the form of date fields. Much like the latitude, longitude, and shape fields that kick off our location adventures, date fields can be the launching point to interesting analysis and answering important questions.

This blog and short video will show you how to work with date fields in Data Engineering in ArcGIS Pro. We’ll highlight the following:

The best way to get started is likely by seeing it in action, so put on some slippers, get under a warm blanket, and check out the following video:

The video is just the beginning: you can, for example, extract weekdays from date fields by accessing the Convert Time Field tool, or continue your analysis with the Space Time Pattern Mining tools.

If you already work with date fields, you now have additional tools at your disposal as you map and analyze space and time. If you’re just getting started, it’s a perfect time to get up to speed.

Stay tuned for our next post where we explore the mysteries of nulls in our data.

About the authors

Alberto Nieto is a Product Engineer on Esri’s Spatial Statistics team. In his role, he helps research, build, and maintain spatial data science capabilities in ArcGIS and works closely with government agencies to learn about the problems our software can help solve. Alberto’s background includes fourteen years of experience, including previous roles as a GIS Developer at Capital One and NOAA's Climate Prediction Center, and as a GIS Analyst at the Census Bureau and the Alachua County Environmental Protection Department.

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Ankita Bakshi is a Senior Product Engineer on Spatial Statistics Team at Esri. With a background in environmental engineering and computer science, she is passionate about solving social, economic, and environmental problems with Spatial Analysis and Data Science. In her role, Ankita enjoys researching, finding solutions to build software, and loves creating video and written content to make the software tools more approachable and applicable to real world challenges. Outside of work Ankita enjoys going on hikes, painting landscapes, and dancing to Bollywood music.

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Lynne Buie is a Product Engineer on the Spatial Statistics team. She helps build spatial statistics tools and Data Engineering capabilities for ArcGIS Pro. She's passionate about using GIS to help make the world a better place.

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