Matt Shearer

This video was aired on 6th May at the Knowledge Graph Conference 2022 in NYC, as part of the "Knowledge Graph Tools Track".

The 13-minute knowledge graph: Netflix, Disney, Amazon, Hulu

This video was aired today at the Knowledge Graph Conference 2022 in NYC, as
part of the "Tools Track".

This video was aired live at KGC2022We showed participants how they can create a
Knowledge Graph in 13 minutes using open Netflix, Disney+, AmazonPrimeVideo, and
Hulu data from Kaggle.

It ends with a graph path analysis of how Kevin Bacon connects with Sandra Oh,
via shows and casts, using the graph that we implemented in Data Graphs in 13
minutes.

NB - we had made some careful model design and data preparation before setting
up the knowledge graph.

We took our Knowledge Graphs as a Service product "Data Graphs" to The Knowledge Graphs Conference 2022, loaded with Netflix, AmazonPrimeVideo, Hulu and Disney+ data.

Knowledge Graph Conference 2022

The 13-minute knowledge graph, with Netflix, Disney+, AmazonPrimeVideo, and Hulu data

Find out about our feature at KGC2022, and explore this Netflix, Hulu, and Amazon Prime knowledge graph, using our product "Data Graphs".

Data Graphs at the Knowledge Graph Conference 2022

We've launched a read-only version of Data Graphs for participants at the
Knowledge Graph Conference 2022 to have a go, hands-on.

Data Graphs is our Knowledge Graphs as a Service product. It is used by global
brands to provide a knowledge graph platform to accelerate product
time-to-value.

Lowering the barrier to entry for Knowledge Graph Platforms
Often knowledge graphs are seen as a high-cost and high-risk strategy that only
the largest of companies can implement, over a very long time. 

With Data Graphs, we've ensured that businesses can see value rapidly.
Specifically, this means speeding up the ability to do proof of concepts, and
simple but informative demos that allow organizations to realise early value at
low cost and low risk. Here's an example of one of those demos right now.

13 mins to set up:
Netflix, Disney+, AmazonPrime, and Hulu
When developing Data Graphs, we wanted to make the setup and creation of a
knowledge graph, simple and quick. 

This video, prepared for KGC2022, shows how we created a knowledge graph,
complete with secure API and powerful UI tools, ready for production, in 13
minutes:

Try it yourself! - play with the Data Graphs demo here
[https://media-graph.datagraphs.io/media-demo/_all/concepts/?q=&pn=1&ps=15&sf=_label&sd=asc&layout=list&viewport=s000000000,1&utm_source=website&utm_medium=kgc-post&utm_campaign=faceted-search]
This demo version was created using Netflix, Disney+, AmazonPrime, and Hulu
data, and gives you a good view of just some of the key Data Graphs features.

1. Create your Domain Model for your Knowledge Graph
After you have designed and created your domain model with the business entities
and the relationships that link them together, Data Graphs generates a visual
representation of the model so that you can see clearly how the knowledge of
your business interconnects. 

Check out the Domain Model for Shows, Cast, Genres, Ratings here
[https://media-graph.datagraphs.io/media-demo/_domain-model/?utm_source=website&utm_medium=kgc-post&utm_campaign=domain-model]
.

2. Use our powerful Faceted Search over your knowledge graph
The search capabilities of Data Graphs are stellar and allow you to find and
explore your data precisely and most importantly, quickly. With the Advanced
Search feature, you can build complex queries by chaining and grouping a series
of boolean and numeric expressions, to pinpoint the targets of your search. 

Test the search capabilities of Data Graphs here, on 115k concepts including
shows, cast, directors, genres, countries, and more
[https://media-graph.datagraphs.io/media-demo/_all/concepts/?utm_source=website&utm_medium=kgc-post&utm_campaign=faceted_search]
.

As well as an intuitive visual search tool, all the Data Graphs search features
are available via API so you can integrate them with your business systems and
apps.

Explore the Data Graphs API here [https://support.datagraphs.io/].

3. Use the Graph Explorer to visualise your knowledge graph
The graph explorer is one of the star features of Data Graphs. You can now
visualise your knowledge graph in an interactive representation of your data,
that you can then explore and dive into, using the nodes. By visualising your
entire knowledge graph, from any concept in your dataset, we open up a wealth of
possibilities for your structured data. 

Interact with the knowledge graph explorer here, starting from the "Stranger
Things" node
[https://media-graph.datagraphs.io/media-demo/shows/concepts/urn:media-demo:TvShow:netflix-s3686/explore/?utm_source=website&utm_medium=kgc-post&utm_campaign=knowledge-graph-explorer]
.

4. Use the Graph Path Analysis to gain insights
Data Graphs lets you visually explore paths between any entities in the graph,
in order to find the shortest paths, and to specify constraints on both nodes
and properties that make up these paths. A key feature of knowledge graphs, this
type of analysis is typically used in compliance, fraud detection, and supply
chain analytics. 

You can try out the graph path analysis here
[https://media-graph.datagraphs.io/media-demo/_all/_graph-search/?utm_source=website&utm_medium=kgc-post&utm_campaign=graph-path-analysis]
.

About the Data Graphs demo
The Data Graphs demo is a read-only view of the full version of Data Graphs
[https://datagraphs.com]. The complete product provides a full suite of tools
for curating, ingesting, editing, and maintaining data in a knowledge graph,
along with APIs for integration of your graph data with apps and business
systems.

About the Media Graph data
The media graph data has been sourced from the open data provided by Netflix,
Hulu, Amazon Prime, and Disney+ via kaggle.com here
[https://www.kaggle.com/datasets/shivamb/netflix-shows]. The data sets from
these 4 publishers have been cleaned, loaded, and linked together in our graph
to join 72k actors and directors across 21k  TV shows and movies, all faceted by
genre, rating, country, and year of production.

A knowledge graph is a collation of information and data typically within the domain of your business context. The information is stored in a database, often a graph database such that it can be queried, maintained, and interacted with by humans or machines. We have exceptional experience in the design, implementation and deployment of knowledge graphs. We have been working with graph databases since our inception and have delivered knowledge graphs solutions for global organisations.

We have exceptional experience in the design and implementation of knowledge graphs and have delivered knowledge graphs solutions for global organisations.

Knowledge Graphs - our Work, Features, News and Updates

Knowledge Graphs

Data Graphs at The Knowledge Graph Conference 2022

Alexi Buckingham

Taken from our newsletter which you can subscribe to here
[https://datalanguage.com/newsletter].

Last week we presented our knowledge graph product, Data Graphs
[https://datagraphs.com/?utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=intro] 
at The Knowledge Graph Conference [https://www.knowledgegraph.tech] at Cornell
Tech on Roosevelt Island, New York.

Based on the presentation topics and workshops at the conference, and backed up
by the "2nd Annual Knowledge Graph Survey", here are our 3 takeaway messages for
you:

Takeaway 1: Organisations are struggling to get started
We heard a lot about the challenges of skills gaps, organisational inertia, and
governance gaps, and that when trying to adopt knowledge graphs, many
organisations just don’t know where to start. This is reflected in the 2nd
Knowledge Graph Annual Survey with 86% of responses saying that 'Organisational
Inertia' was an important inhibitor to their adoption of knowledge graphs.

Organisations can break through the inertia by using a reference implementation
Our preferred approach to breaking through this inertia is to build a reference
implementation rapidly. Using Data Graphs, you can have a working reference
implementation ready within a day - we did it in 13 minutes here
[https://datalanguage.com/news/13-mins-to-set-up-a-knowledge-graph-with-netflix-disney-amazonprimevideo-and-hulu]
.

A working reference implementation has 3 main benefits:

 1. It helps stakeholders grasp the value of data meaning and interconnection,
    hands-on.
 2. Seeing the knowledge graph visually, and being able to explore it by simply
    clicking from node to node sparks new ideas for all disciplines.
 3. A working version gives teams a real basis on which to iterate and answer
    key questions, including “What KG features do we need?”, “What model works
    well?”, “What kind of inference and path analysis do we need?”, and more.

Have a look at the Knowledge Graph Explorer
[https://media-graph.datagraphs.io/media-demo/people/concepts/urn:media-demo:Person:3Vn1Bxu4W6yzLNL54eB4b5/explore?utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=reference-implementation] 
feature of our product Data Graphs below. A reference implementation like this
helps organisations to break through the inertia, and save time spent wallowing
in indecision.

Knowledge Graph Explorer
[https://media-graph.datagraphs.io/media-demo/people/concepts/urn:media-demo:Person:3Vn1Bxu4W6yzLNL54eB4b5/explore?utm_source=email&utm_medium=newsletter&utm_campaign=internal-inertia]
Click here to try out the Knowledge Graph Explorer
[https://media-graph.datagraphs.io/media-demo/people/concepts/urn:media-demo:Person:3Vn1Bxu4W6yzLNL54eB4b5/explore?utm_source=email&utm_medium=newsletter&utm_campaign=internal-inertia]
Takeaway 2: Organisations are looking for key features to enable their plans
In this slide from the KG Annual Survey, you can see the areas here that reflect
what knowledge graph users are interested in, for example 'Search', 'Better
Ontology Management', 'Integration' and 'No-Code/Low-Code'.

Features of interest to KG Survey Respondents

Search
Data Graphs' Advanced Search feature allows you to build complex queries by
chaining and grouping a series of boolean and numeric expressions.

Try Data Graphs' Advanced Search here
[https://media-graph.datagraphs.io/media-demo/_all/concepts?aq=c[director:Person:2mdyLPMIMopbPB0kVUvghw:Quentin%20Tarantino].(c[cast:Person:3ENPqEkRhLUCxj3W3RG1Hp:Samuel%20L.%20Jackson])&pn=1&ps=15&sf=_label&sd=asc&layout=list&viewport=s000000000,1&utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=search]

Better Ontology Management
This area has always been complex and somewhat expert-dependent. "No code"
schema development is now in demand. In our demo, you can see the domain model
(the output of our no-code custom schema tools) for shows on Netflix, Disney+,
Amazon Prime Video, and Hulu.

Try Data Graphs' Domain Model here
[https://media-graph.datagraphs.io/media-demo/_domain-model?utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=ontology-management]

Integration
Using APIs and webhooks, how can we help developers integrate with minimum
friction? This step-by-step guide shows how to set up your knowledge graph
quickly and effectively.
[https://support.datagraphs.io/knowledge-base/get-started/building-a-knowledge-graph?utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=integration]

Building a Knowledge Graph: Step by Step Guide
[https://support.datagraphs.io/knowledge-base/get-started/building-a-knowledge-graph?utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=integration]

No-Code/Low-Code
How might businesses get their knowledge graph up and running without having to
dedicate engineers to coding? The tools in this space are improving, and you can
see how we set up a knowledge graph with Data Graphs using data from Netflix,
with APIs and fully featured management UI production-ready, in 12 minutes here.

Creating a Knowledge Graph in 12 Minutes
[https://datalanguage.com/blog/creating-a-knowledge-graph-in-minutes&utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=integration]

Takeaway 3: Organisations want to reduce 'Time to Value'
In order to get to market rapidly, and be able to iterate based on real customer
needs, organisations are aiming to get their knowledge graph platforms launched
faster. From inception to commercial operation, how do we do this? Whether it is
for a reference implementation, or for commercial use, tools to enable rapid
model building, data ingest, and ready-to-go APIs are front of mind.

This video shows how a knowledge graph with Netflix, Disney+, Amazon Prime Video
and Hulu data can be built, with APIs and powerful UI, in just 13 minutes.

Watch: 13 minutes to setup the media graph
[https://datalanguage.com/news/13-mins-to-set-up-a-knowledge-graph-with-netflix-disney-amazonprimevideo-and-hulu&utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=time-to-value]

But Remember... Preparation is Key
One thing we consistently emphasise is that good preparation is essential. The
speed and relative simplicity of the setup of Data Graphs is only possible with
solid information preparation - data that was already clearly structured and
well organised. Designing your domain model is an essential step in establishing
the shape of your data before embarking on your first implementation. It will
change, no doubt, but do avoid rushing in without a plan. Spend time thinking
about the specifics of your data, the core entities in your domain, the key
relationships between them, and this will enable you to make an effective start.

More on why good preparation is key
[https://datalanguage.com/blog/creating-a-knowledge-graph-in-minutes?utm_source=website&utm_medium=kgc-newsletter-blog&utm_campaign=preparation]

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