Google BigQuery was crafted to create maximum business value.
And yet, it didn't!
The value of Google BigQuery was reliant on the customer's capability to synchronise agreement-, asset-, documentation-, event-, human-, organisation- and task-data.
And since most customers struggle with system integration, Google BigQuery was forced to operate on less-than-optimal data.
Without high quality master data it is impossible for Google BigQuery to deliver maximum business value.
The Google BigQuery customer wasn't happy. They probably blamed Google BigQuery, even if there wasn't much Google BigQuery could do about it.
The Google BigQuery customer just couldn't make those systems talk.
Now Google BigQuery gets updated quality data
- without any integration or development
You see, by embedding Sesam into an Google BigQuery solution, Google BigQuery get free flow of data – no matter the system, no matter age nor language.
The Google BigQuery customer can now easily synchronise agreement-, asset-, documentation-, event-, human-, organisation- and task-data with any of these Sesam connected systems:
And talk is good for business
With Sesam in the solution, Google BigQuery got the updated quality data it needed to deliver the business value promised – and even gave them the flexibility to develop Google BigQuery and its value to the customer further.
Happy customer, less dependencies, and in addition, great connectivity to to a set of data and analytic services:
So, while talk admittedly can be difficult, system talk is quite easy.
All you need is Sesam.