The Atlas is specific in detailing an area's geographical and political features, which brings us to mapping projections, crucial for geospatial data analytics.
Spatial aggregation is one of the techniques used to ensure data is protected when citizens disclose their personal information during census.
One major strength of Geohashing is that it can also be used to provide a good degree of anonymity.
Visualizing geospatial data can help users communicate how different variables correlate to geographical locations by layering the same variables over maps.
Geospatial data has morphed into one of the most in-demand forms of data. Before the different commercial industries started tapping their potential, Geospatial Data was mainly used by the military, maritime, aeronautical organizations, and intelligence agencies.
Business capabilities and opportunities result from these Big Data Landscape maturity levels of an enterprise. We describe what they are and how they matter.
In-memory database is a database that keeps the whole dataset in RAM.
Key-Value Database can be said to be the simplest form of a NoSQL database offering tremendous performance.
Graph databases are the future, and even if you’re just a beginner, it’s never too late to get started.
Data visualization is always a better way to explain the data to both technical and non-technical audiences.