(upbeat music)
- Welcome back to the Azure Cosmos DB Essential Series.
My name is Mustafa, and in this episode we'll explore
some industry use cases for Cosmos DB
to get a better feel for how
and why developers are using NoSQL
in their applications.
So, let's start with health providers.
In the past, movement of patient files
from hospital to hospital was done via manila folders
and physical CDs.
So if an accident happened and I needed to be transferred
from hospital one to hospital two
to receive the level of care necessary,
my folder would have to move with me.
Now, today, we don't typically use physical files.
Like everything else, patient data has migrated
to a digital medium, but still,
health providers have had difficulty
standardizing digital assets across their organizations.
Now, legacy technologies mean legacy health messaging,
which means incompatibility and friction
across the healthcare system.
So New South Wales Pathology looked
to solve a similar problem within their own organization
using Cosmos DB.
For doctors to make informed clinical diagnosis,
they needed access to patient health data
in a standardized digital format.
Now, New South Wales serves over eight million patients
in a geographic region four times the size of the UK,
so the volume of patient data is large and always growing.
Now add in security and compliance considerations necessary
when safeguarding sensitive public health data
and quickly it becomes a very difficult challenge
to try and implement new solutions.
Azure Cosmos DB's data structure was a central piece
of an architecture that was able
to translate legacy health messaging to the new
and broadly-supported FIHR standard,
making it accessible both at scale and across solutions.
By converting messages from the HL7 standard
into FIHR with an Azure Cosmos DB,
New South Wales was able to create modern digital assets
that could be used across their organization.
In addition to being a challenge created
by the sheer volume of data points,
supply chain is a data representation challenge.
When modeling organizations, people, and resources,
there are a wide variety of small factors
with compounding impact on the efficiency
of the supply chain all up.
With a graph data model, we see supply chain companies
modeling the relationship between components
of a larger system through millions of vertices
and edges in Cosmos DB.
Now, a great example of this is Bentley Systems,
which makes software for civil engineers,
construction owners, and architects.
These are the people that design our roadways,
utilities, and infrastructure.
Now, with Cosmos' DB graph data model,
Bentley's design insight software gives project teams
visibility into the implications of design decisions
on cost, schedule, safety
and other performance indicators early in the project.
This mitigates issues down the line.
Broad data model support is what makes it possible
for both healthcare providers and supply chain systems
to both use Cosmos DB for entirely different applications.
Now let's imagine we're a logistics company
that ships grills or bench presses,
anything that typical postal carriers will not deliver.
Daimler manufacturers trucks and sells vehicles
to those companies with a set of fleet management tools
built right into the fleet.
The Connected Cars Project is a joint effort
by the North American and German research
and development teams that specialize in autonomous driving,
vehicle infotainment systems, and telematics.
Now, the connectivity module is the brain
of a connected truck.
It receives and transmits data in real time
and is the interface for all connectivity-related services.
Now, like a smartphone, it uses Bluetooth,
mobile comms network and GPS to communicate
with the traffic infrastructure, with other vehicles,
and with other systems that are involved
in the logistics process.
These trucks create an over a hundred thousand strong
vehicle network of moving IOT devices.
Now, when working in IoT, just like in our previous
use cases, data volume quickly becomes a challenge.
Since thousands of vehicles are reporting
to the database multiple times per second,
Cosmos DB has to play a key role
in Daimler's fleet management solution.
By ingesting and analyzing the vehicle telematics,
the systems automatically notify the fleet operator
and the workshop if repairs or maintenance are needed.
Critical situations are thus detected early on
so that they can be resolved before the vehicle breaks down.
And by coordinating the fleet, platooning allows vehicles
to drive in a fuel-efficient cluster
in route to their destinations,
reducing fuel consumption and emissions across the fleet.
Azure Cosmos DB provides the georedundancy needed
for high availability and low latency reads and rights
from global fleet vehicles.
The acceleration of e-commerce
and the advanced fleet tracking capabilities companies
like Daimler are providing are not decoupled phenomena.
Today, it's often more convenient
and often less expensive for consumers
to purchase products online.
As a result, the U.S. Bureau of Labor Statistics
expects delivery truck drivers are projected
to see the largest employment growth
across all occupations through 2029.
Facilitating a smooth online experience
for consumers is mission critical.
User expectations for low latency
and instant page loads are higher than ever,
and on a holiday like Black Friday
where millions of consumers are adding, removing,
submitting, and refreshing shopping carts,
downtime and latency translate to lost revenue.
ASOS runs their entire shopping cart
and recommendation engine on Cosmos DB
to take advantage of the low latency,
high availability and elasticity necessary
when adjusting to spikes in traffic.
In addition to the shopping cart,
ASOS performs real-time recommendation
and personalization with materializing views in Cosmos.
By pre-calculating vectors which describe the likelihood
X user will want to purchase Y product
and on a daily cadence, ASOS can surface lightweight,
real-time recommendations to millions of concurrent users.
Now, at Microsoft, a few of our own services
also run on Cosmos DB.
Microsoft Teams relies on the performance and scalability
of Cosmos to handle everything from messaging
and litigation to transportation services.
Running a modern Saas platform
that see six to seven petabytes of data
and close to two trillion transactions
across all of their global tenants
is a massive scale, performance and availability challenge.
Running a multi-tenant SaaS platform means
our software needs to scale as every tenant's usage scales,
and Cosmos DB is how Teams can get this done reliably.
Thanks for tuning in.
I'll link some more resources on use cases below.
And please join us in the next episode
to discuss consistency in Cosmos DB.
(upbeat music)