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DBpedia

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 human-, location- and organisation-data.

Location
Organisation
Person

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

Icon Speechbubble Numbers Illustration.png

- 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 human-, location- and organisation-data with any of these Sesam connected systems:

AVEVA
AVEVA
Winorg
Winorg
Rotorsoft
Rotorsoft
Stripe
Stripe
ArcGIS
ArcGIS
Freshdesk
Freshdesk
Auth0
Auth0
YouTrack
YouTrack
Unit4
Unit4
IFS
IFS
360°
360°
Active Directory
Active Directory
Zendesk
Zendesk
SAP
SAP
Salesforce
Salesforce
Smallworld
Smallworld
Jira
Jira
Zoho
Zoho
Microsoft Dynamics 365
Microsoft Dynamics 365
Survey Monkey
Survey Monkey
Motimate
Motimate
Wave Financial
Wave Financial
Infor M3
Infor M3
Synergi-life
Synergi-life
Omega 365
Omega 365
HubSpot
HubSpot
Geonis
Geonis

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:

Azure-service-bus
Azure-service-bus
Microsoft Dataverse
Microsoft Dataverse
Google BigQuery
Google BigQuery
MySQL
MySQL
Brreg
Brreg
Apache Druid
Apache Druid
Microsoft Synapse
Microsoft Synapse
Elasticsearch
Elasticsearch
PostgreSQL
PostgreSQL
Firebase
Firebase
Google Cloud Platform
Google Cloud Platform
Apache Solr
Apache Solr
Microsoft Power BI
Microsoft Power BI
Qlik
Qlik
Twitter
Twitter
Microsoft Excel
Microsoft Excel
Microsoft Azure
Microsoft Azure

So, while talk admittedly can be difficult, system talk is quite easy. 

 

All you need is Sesam.

Making those systems talk

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