When we see entities in real world, we notice that there is a complex relationship occurs between the entities. Every entity type is unique and has multiple possible relationships. Graph databases solve this problem by providing ways to model the relationships in the database and that makes the insights very simple and easy
The key steps organizations can take to cross that hurdle/chasm and move ahead of the roadblock and prepare the foundation which will enable them to move along the curve
Organizations need leaner and agile structure to focus on the business outcome. Following are the key roles that should be part of the analytics organization which is focused solely on delivering business value
There are some gaps in data management and maintenance space in Azure. Following are the two things that I feel are missing from the current landscape of Azure and will hopefully be addressed soon
Imagine a scenario where we can maintain an immutable persistent stream of data and instead of processing the data twice, we can use the stream to replay the data for a different time using the code. That is the premise of Kappa architecture
This article includes the kind of tools and methods that go along with maturity steps. I also want to introduce the concept of Chasm. Its essentially a bump or a gap in the journey of analytics maturity which takes a little more than usual effort to cross.