Silectis used public building permit data from DC’s open data portal to determine which neighborhoods in Washington DC are proving they care about the future of solar energy.
Security is absolutely critical in data lakes, since a data lake oftentimes contains the majority of an organization’s data. Giving users access to the data they need to do their job should not necessarily mean giving them access to all of the data in the lake. Unfortunately, many data lake tools, especially custom do-it-yourself (DIY) implementations, do not provide an easy way to manage and audit data access.
In Magpie, security is a core concept, where every user action is verified and logged for future review. In this post, we’ll demonstrate how to secure your data lake quickly and effectively with Magpie.
More and more companies are turning to data lakes as a way to unify and get value out of their growing collections of data. However, it can be a challenging to navigate the ever-changing technology landscape around these lakes, set one up, and quickly get value from it.
In this post, we’ll walk through a technical tutorial of how Magpie can help companies get up and running with a data lake quickly. We’ll show how companies can easily configure and explore a set of enterprise data sources, enrich that enterprise data with third party sources, and perform initial analysis.