This blog will lay out the key aspects of a hothouse, show how it differs from the standard hackathon and cover some of the key Azure technologies that work well in the tight schedules of this approach. These technologies (such as Power BI, Azure SQL DB, Logic Apps, Cosmos DB etc ) take away much of the configuration and infrastructure work allowing participants to focus on functionality.
Solving the GDPR Discovery problem – Azure Data Catalog is
Microsoft’s solution to understanding & cataloguing the data estate of any organisation. Designed to promote self serve data discovery it has several capabilities which support the GDPR process and furthermore, as a SaaS solution it has a minimal footprint, low start up cost, requires minimal training and can therefore be rapidly deployed at scale..
SQL Server Analysis Services is a powerful analytics engine & Azure Analysis Services builds on it’s strengths & adds exciting new capabilities. Out of the box Scale up/out, high availability, a powerful semantic layer & now support for bi-modal analytics means that Azure Analysis Services may just have become a game changer.
“Where’s my raw data? Is this data set complete? Am I using dev or test data from the lake? Can I trust this data set, where did it come from and who owns it?” Data Lakes are a great design feature for a modern data warehouse however they can quickly deteriorate into a Data Swamp if there is no governance on their structure. But governance means process and process can be the enemy of agility. This post will introduce Azure…