My name is Puntis Palazzolo and I am part of the SAP Data Intelligence Product Management team.
I'll be your presenter in this course. I am excited to talk to you about SAP's new product
for data scientists, and to hear your stories on how you used the SAP Data Intelligence
to make the world a better place. After this short introduction
let's get started with the course content. This course consists of 11 units.
In the first three units, we will talk about SAP's strategy on delivering the Intelligent Enterprise,
and how SAP Data Intelligence fits into the whole picture by providing you with some customer use cases and examples.
During the units four to eight, we will focus on the technical features
and capabilities which allow you to develop your data-driven scenario.
And in unit nine and 10, we will talk about end-to-end stories and using some ML services
out of the box. At the end of each unit, you'll be asked
some self-assessment questions, to see what you have learned in that unit.
And at the end of the course, you can take the course assignment, which is based on the content
covered by this course. Doing this assignment allows you to earn points
for your record of achievement and digital badge. Let's start our learning.
SAP's strategy for delivering the Intelligent Enterprise defines how to operate businesses in the future.
Here you see a high-level overview of this strategy, which consists of three key components.
From top down, the intelligent suite, intelligent technologies, and the digital platform
at the foundation. As you can see, we have a digital platform,
where you can build your intelligent suite with the help of some of SAP's intelligent technologies.
The intelligent suite can then be served for different purposes, such as the customer experience,
a digital core, people engagement, and so on. To get an end-to-end feeling,
think about the several tools and data sources from different vendors, who want to connect and integrate
with our Intelligent Enterprise, or the applications which consume and serve our processes.
As you will see in this unit, SAP Data Intelligence is a digital platform,
and provides intelligent technologies to enable the intelligent suite.
SAP Data Intelligence helps SAP to enable and deliver the Intelligent Enterprise.
Furthermore, SAP Data Intelligence can also be used by our customers and partners for their own
intelligent applications and analysis. Let us have an overview of the Machine Learning technologies
available at SAP, and the intelligent applications, based on Machine Learning or AI.
Here you can see the different products at SAP which provide ML or AI capabilities
to our customers and partners to enable their Intelligent Enterprise.
One, as an end user, you might just want to get help in your daily work by AI models,
which are running in the background and simplify your life. Therefore, we embed intelligent models
in our business products. Alternatively, we also have some standalone applications,
which you can use in addition to our standard business suite.
And we also provide so-called business services, which can be used by customers and partners
for building their own intelligent applications. In unit two, you will get an overview
on those different options of intelligent applications. Number two is the SAP Intelligent Robotic Process Automation,
which allows you to automate processes within your SAP applications,
while also interacting with non-SAP apps, tightly integrated with the SAP digital core.
It mimics a human user's working on a PC, integrating UI components and extracting the data
it needs to execute tasks, such as virtual copying, pasting, clicking, and so on.
Number three is SAP Conversational Artificial Intelligence, which provides all the tools necessary
to create chatbots and conversational applications. It includes an NLP engine and a bot builder,
which offers a graphical user interface to easily create bots, and models
a bot's conversational flow. Number four is what we call Intelligence,
SAP Data Intelligence, which is a combined product of SAP Data Hub and SAP Leonardo ML,
that covers the entire data science process, from data access with the connectors
you might already know from Data Hub, to the AI capabilities you might already know
from the SAP Leonardo Machine Learning, which will be shown in units three and 10 in this course.
We mentioned that the result of an Intelligent Enterprise can be consumed as an intelligent application.
At SAP we have built-in intelligence in all our applications.
And as an end user you realize that you get a lot of support
by ML models in your daily life or work. Here, you can see some examples of embedding intelligence
in S/4HANA, C/4HANA, Concur, and SuccessFactors, but that is not the extent.
These are just some examples. You also have access to the entire
Intelligent Enterprise suite. In the next units we will discuss service ticketing
from C/4HANA, Concur Invoice, and the Learning Recommender in SuccessFactors, and so here I will just focus
on one example from S/4HANA. Let us pick SAP Cash Application,
which is available in S/4HANA, but also down ported to ECC.
It is one of the first intelligent applications available as a standalone application.
All large companies send out a lot of invoices, which have to be matched with incoming payments.
Some companies send out millions of invoices per month, so matching invoices with incoming payments
is very important, and can also be a time- consuming task. You can define rules for matching payments
to invoices automatically, but this does not work for all payments.
Even with having complex rules, a high number of invoices cannot be matched automatically.
As the raw data is stored in the system, you can use a labeled dataset and train a neural network.
Then the trained model can automatically clear matching payments with invoices.
For the payments that cannot be cleared automatically, it proposes the best fitting invoices in a list
in descending order of matching probability. This helps to save a lot of time.
As part of the intelligent technologies we mentioned Robotic Process Automation,
or Intelligent RPA, which can improve business processes by automating repetitive actions across systems.
This could be done in attended or unattended modes. Attended is when robots are coworking with humans,
also called robotic desktop automation, or RDA. Attended bots are useful when the entire end-to- end process
can't be automated. In such cases, the actions of RPA bots
can also be triggered by system-level events that can give and take data to and from human workers.
Unattended, or fully automated process, is when robots are working autonomously.
Unattended bots typically perform batch operations that do not require user intervention.
For example, a batch of new client information is received in a spreadsheet and needs to be entered
into multiple applications. Conversational AI is another technology
which can make your enterprise suite intelligent. It is essentially a collection of NLP
plus chatbot building services, that allows you to build powerful conversational agents.
You can then integrate and surface these bots in your business application.
Our focus in this course is SAP Data Intelligence, which can be classified both as intelligent technology
because of the intelligent services that it provides, and also a digital platform which can manage
the entire AI lifecycle at scale in your enterprise. We will learn more in the next chapters,
but in a nutshell, it provides you with a platform that can connect to various data sources
on-premise and in the cloud, to extract value from them. It allows you to work across them seamlessly,
provides metadata information, provides flexibility to run your SAP
and non-SAP libraries and programming languages, facilitates the transition between the POC and a product,
and on top of that offers intelligent services, which can be used in your processes,
and you can benefit from that. With SAP Data Intelligence you can rapidly
provision AI labs as a service for data science agility. Hope you enjoyed this unit.
We learned about the SAP strategy to deliver the Intelligent Enterprise,
got familiar with some of the intelligent technologies at SAP, such as Intelligent RPA and Conversational AI,
and learned where and how SAP Data Intelligence fits into SAP's delivery for an Intelligent Enterprise.
In the next unit, we will focus more on SAP's intelligent applications.
Good luck with your self-assessment quiz.