A wikipedia project that is aiming to extract structured content from the information created in the project.
Getting the very best out of DBpedia
DBpedia was crafted to create maximum business value.
And yet, it didn't!
The value of DBpedia was reliant on the customer's capability to synchronise location- and organisation-data.
And since most customers struggle with system integration, DBpedia was forced to operate on less-than-optimal data.
Without high quality master data it is impossible for DBpedia to deliver maximum business value.
The DBpedia customer wasn't happy. They probably blamed DBpedia, even if there wasn't much DBpedia could do about it.
The DBpedia customer just couldn't make those systems talk.
Now DBpedia gets updated quality data
- without any integration or development
You see, by embedding Sesam into an DBpedia solution, DBpedia get free flow of data – no matter the system, no matter age nor language.
The DBpedia customer can now easily synchronise location- and organisation-data with any of these Sesam connected systems:
Wave Financial
Winorg
ArcGIS
Stripe
Freshdesk
Geonis
Microsoft Dynamics 365
Unit4
IFS
Maximo
AVEVA
Smallworld
SAP
HubSpot
Synergi-life
Infor M3
And talk is good for business
With Sesam in the solution, DBpedia got the updated quality data it needed to deliver the business value promised – and even gave them the flexibility to develop DBpedia 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:
Microsoft Synapse
Google Cloud Platform
Elasticsearch
Brreg
Microsoft Dataverse
Google BigQuery
PostgreSQL
MySQL
Qlik
Microsoft Azure
Microsoft Excel
Azure-service-bus
So, while talk admittedly can be difficult, system talk is quite easy.
All you need is Sesam.