XMPRO Data Stream Designer - Event Intelligence Applications

The XMPRO Data Stream Designer enables you to integrate to multiple data sources and orchestrate the flow of data without having to code. Go to https://xmpro.com if you want to learn more about how you can build real-time applications with our low-code Event Intelligence Platform.

Transcript

a data stream is the visual

representation of a streaming data

pipeline it is created by a user inside

XM pro data stream designer and a data

stream is typically composed through the

sequencing of a collection of

integration and other services agents

such as listeners context providers

transformations functions I on machine

learning services as well as action

agents each data stream is typically

constructed around a business use case

and it's done by a business user or a

subject matter expert so let me run you

through the data stream designer this is

the landing page for the XM pro data

stream designer we have different ways

that we can organize or categorize

information it could be done

functionally it could be done around

asset classes it could be done around

geographies or locations and in this

instance the information is is

categorized around functional areas so

around equipment maintenance and inside

that multiple data streams that feed my

use cases or applications of equipment

maintenance for example so these could

be pumps fans compressors heat

exchangers all around equipment

maintenance from a categorization point

of view now again this categorization is

shared with the app designer so we're

now going to the apps I see exactly the

same categories of equipment to drill

down and just have a quick look at what

is inside data stream and there are more

extensive videos that cover the all the

elements and how to configure this and

how to put it together but this is just

a high-level overview so this is an

example of an exemplary data stream it

is a visual way of representing or

building out the flow you can visually

construct all the elements of this and

it allows you to build the data flow

based on the use case or the application

or the problem that you're trying to

solve again making it visual makes it

really easy to first of all

constructed and sequence the the the

different components together from all

the building blocks that we have as

either listeners context providers

transformations machine learning and AI

capabilities functions such as

phosphorus and actions that we want to

do in other systems these are all

drag-and-drop

drag-and-drop blocks that we drag onto

the canvas and we can then sequence and

orchestrate in a very visual way what

are you trying to do from my dataflow

point of view so in this instance we're

bringing in flow and pressure from a

story n' we combine it with sensor data

from a third party sensor that's plugged

onto the pump in this example which

gives us vibration and temperature we

combine that we get the mic and model

from s AP so we can contextualize the

data that we have in this flow and we

can check certain thresholds if we want

to but we can then also pass it on to a

predictive model to predict whether this

is likely to file now that's the visual

sequencing this is the story that I'm

telling I'm connecting data I'm

combining it I'm bringing in context

from from the business system in this

instance the ERM system so that I have

my canned model and maintenance

information and something else that I

want I then want to run a predictive

model in meantime I want to store some

of the records and once I know that some

of the pumps are likely to fail based on

this predictive model I can then predict

the remaining useful life running or

sequencing another or chaining another

predictive model into this data flow

that creates this data pipe of

intelligent information that starts

flowing out so I start off with big data

I start bringing in intelligence and

turning it into smarter data and now I

can drive actions inside the data stream

that we've constructed for this specific

use case so in this one I'm sending out

sms's starting space and work order

requests and and run some recommendation

rules at the back but this is how you

visually construct the logic the blocks

that are used for that again we have a

library it's extensible library and

there are other videos that care that

cover this in more detail but just to

give you a high-level overview of what

the data stream designer is all about