Building a Semantic Layer for Disparate Data Consumers
There’s a pattern that I have come across that seems to work quite well for the majority of organizations that meet a two basic criteria:
There are multiple platforms that consume the same datasets (BI tools, CRM, APIs, etc)
There’s potential for embedding data into an external or internal facing product either via an iframe or custom web app
An Elegant Data Stack for Embedded Analytics
At Astrodata, we have seen embedded analytics stacks of all shapes and sizes. We’ve learned the hard way that the cost of an embedded analytics data stack, combined with the front end application, can balloon beyond the anticipated ROI quickly without careful consideration of 1) technology pricing models and unit cost, 2) realized value 3) developer productivity.
Benchmarking Case Studies
In the realm of data monetization, the integration of a semantic layer stands out as a key component in building a pricing strategy.
Embedded Analytics - Under the Hood
Why is this something people should think about?
“Embedded Analytics” is among the buzzwords buzzing across the data world, and there is real market value available to those who get it right. With the appropriate technologies and organizational practices in place, companies can position themselves to leverage embedded analytics to monetize their data and drive and product usage.
Data Delivery Options
If you are working on a data monetization product chances are you are rightfully focused on designing a useful data delivery layer – after all, this is the component in your stack where your data first enters your customers’ workflows and thus where they begin to realize value from your efforts.
How a Semantic Layer Impacts Pricing Strategies
In the realm of data monetization, the integration of a semantic layer stands out as a key component in building a pricing strategy. A semantic layer serves as a translator between intricate data structures and actionable business insights, fostering clarity for both technical and non-technical data consumers/customers. The way that data is presented to an end user inherently affects the perceived value of that data. Semantic layers make pricing tiers easy to manage by offering the ability to dynamically provision data content access.