 
Hi, my name is Geir Engdahl
and I am making this video to show you the Cognite Data Fusion architecture.
Cognite Data Fusion
is what is backing all the industrial applications
that Cognite and partners are making.
It is all about making previously siloed
data easily available and understandable.
It starts at the bottom with the source systems.
They can be anything from industrial control
systems supplying sensor data,
through ERP systems to massive 3D CAD
models in engineering systems.
We use extractors,
typically running on premise or
on the edge out in the field,
to connect to and copy data from these systems.
The extractors are custom built for
some of the industry-specific systems we have encountered,
and standard off-the-shelf ETL tools
for more traditional tabular data in SQL-
compatible databases.
Data is flowing from the extractors
into the CDF ingestion API.
Everything from here on lives in the cloud.
The first stop is the raw storage layer,
where tabular data is stored in its
original format.
The reason for this is that we want to minimize the logic
in the extractors and want to be able to run
and re-run transformation on
data in the cloud.
From the raw layer,
data is transformed into the Cognite data model.
We provide a data model out of the box,
so that users and application developers
can make assumptions about the structure of the data
and build applications on top of it at a much
faster pace than today.
Our data model is centered around
the assets, but unfortunately
different systems have different names for the same
physical object.
The first part of Cognite’s contextualization
process is mapping all the asset names
from different systems to one global unique
identifier per asset.
For instance, an object inside a 3D model
may have an ID that can be mapped
to an asset.
A time series from an instrument
monitoring system, may have another ID
that can be mapped to that same asset.
This allows a user to click on a component
in the 3D model and
see connected time series data.
The second part of Cognite’s contextualization process
is linking different assets together
based on how they are connected in the real world,
for instance through physical flows.
Fluid can flow from a pump through a pipe
and a valve into a tank,
and Cognite Data Fusion should know
about those connections so that a user
can for example ask for
all the pressure readings along a particular flowline.
To ensure fast aggregations and queries,
Cognite Data Fusion indexes the data
in different ways and allows search, filtering
and computations on the data as part of
the API.
This enables powerful and responsive applications
to be built with low effort.
Another way to run calculations near the data
is to use the model hosting environment provided
as part of Cognite Data Fusion.
It can run custom Python code to make
predictions from machine learning models or
calculations from physics-based simulators.
A unique feature is the ability
to ingest large 3D models
of several gigabytes in size
and process them so they can be viewed
in a regular browser on a phone.
This combined with the Cognite 3D web
viewer makes it easy to visualize industrial data
in its physical context in a
user-friendly way.
All the information liberated by Cognite is
available through a modern REST based API.
The API does not expose any
of the details of the technology used inside
Cognite Data Fusion, meaning
that Cognite can rapidly innovate and replace internal
components as new ones become available,
without breaking any applications using
the APIs.
In addition to a well-documented API,
Cognite provides connectors and
Software Development Kits for many common
programming languages and analytics tools,
such as Python, JavaScript,
Spark, OData and Grafana.
We also offer a library of low-code
reusable components that make it
very easy to build web applications on
top of Cognite Data Fusion.
I hope that gives you a better understanding of what
Cognite Data Fusion is
and the capabilities it offers.
We believe it is a key technology to
liberate industrial data and making it
easy and intuitive to use and create value from.
 
