Graph Knowledge based data science with

GRAKN.AI

@micbucci

Knowledge Science

We now work in an incredibly complex and heterogeneous data space

The first task is to get all of this into tables of various sizes

Problem 1: I have many-to-many relationships

ID Customer Name

1 Zaphod Beeblebrox

… …

ID Sales Order Amount

1 ZYX123 $10000

1 ABC789 $15000

… … …

ID Customer Profile

1 Fashion Enthusiast

1 Traveller

… …

ID Customer Name Sales Order Amount Customer Profile

1 Zaphod Beeblebrox ZYX123 $10000 Fashion Enthusiast

1 Zaphod Beeblebrox ZYX123 $10000 Traveller

… …

Problem 2: hierarchical data

How do you model the management structure of a company?

Employee Manager

Dave Bob

Alice Bob

Bob Steve

… …

Now the data is there, how do I find out who Dave’s managers are?

Why Grakn.ai (Graph of Knowledge)?

• Effective Data integration

• A natural data model - it is easy to describe application areas

• Enforce the schema – ensure data is correct when it is loaded into the graph

• Flexible data schema – can change to support additional data sources - no restructuring of tables

• Migration tools - customised mappings from common formats csv, json, owl (automated) and more to come…

• Inference capabilities via logical rules

https://grakn.ai/

https://grakn.ai/slack.html

https://discuss.grakn.ai/

https://github.com/graknlabs/grakn

https://grakn.ai/download/latest

We are open source!Try the stack for yourself or get in touch with the GraknLabs

Image Attribution

Thanks to the following for the images used in this presentation: