We love maps because they act as a great canvas for tracing many things;
- Events; what happened where?
- Elements; who or what was here?
- Time; when did it happen over there?
But, if you are a Data wrangler, you are often more interested in solving the puzzle of why there? This means that you have to dig deeper. Digging deeper takes time. But should it?
ARLAS.io build on ARLASⓇ framework – an open-source geospatial intelligence solution – believes that diving deeper into your geo-big data shouldn’t be unnecessarily time-consuming.
Hence we release ARLAS version 14.
ARLAS14 is the ultimate robust geospatial big data solution on a budget. By budget we mean, free if you head over here to access our documentation.
We made sure that it is OGC compliant because we understand that you may need to move your data from other platforms; meaning that you have utmost interoperability with other GIS data formats.
To get back to how we get you saving time, we have a new application for you. ARLAS-wui builder that will get you to configure your ARLAS exploration dashboards in no time. For example, in about 10 minutes, you will have launched your: map, search functions, timeline and analytics board (histogram, doughnut, power bars) to get the first visualisation on your data.
That means that you present your data in a visual language that is understood by your audience
ARLAS CONFIGURATION OF LAYERS
Configuration of the analytics board
You say your data is unique, we agree. This is why we are giving you access to ARLAS hub where you get to configure your data to match your various projects.
You then are able to save your dashboards – sometimes referred to as projects – in ARLAS hub that offers you a workspace to; save, duplicate or edit your configuration.
List of dashbords in ARLAS-wui-hub
We aim to easily and quickly get geospatial intelligence teams of diverse skills to the same page with their analysis.
Take a tour of our tutorial here to get a feel of ARLAS in action.
Once you get started, let us know about your experience with ARLAS powering your data.
Also, stay tuned for more information about using ARLAS for machine learning because geo big data is only useful when it helps you answer the ‘why there’ query.