Written by Ndz Anthony
This article will discuss an overview of analytics in the modern SAP digital economy, SAP's embedded analytics Strategy, the VDM model, and examples and use cases of Embedded Fiori Applications.
THE MODERN SAP DIGITAL ECONOMY
In today's business landscape, digital technologies and data-driven insights are increasingly important in driving economic growth and transformation. As a result, SAP has positioned itself as a key player in enabling businesses to thrive in this digital economy by providing cutting-edge software solutions such as ERP, CRM, SCM, and analytics tools.
The company's modern digital economy vision emphasizes the importance of data-driven decision-making and the need for businesses to be agile, adaptable, and customer-focused to compete in the rapidly evolving digital marketplace.
While SAP's data-driven strategy typically entails reporting and analytics using third-party tools, the company has taken it further by allowing analytical tools and capabilities to be embedded directly into business applications.
In this article, we'll explore this innovative approach and what it means for businesses looking to succeed in the modern digital economy.
SAP’s EMBEDDED ANALYTICS STRATEGY
In 2017, SAP introduced Embedded Analytics as part of its business suite.
This critical initiative was created to overcome traditional wait times for analytical reports and is now on the roadmap for most of SAP's flagship solutions.
The ability to provide users with analytics at the point of need - within a conventional workflow and business context is at the heart of this strategy.
Due to its seamless integration with the SAP Fiori interface and applications, SAP Embedded Analytics is widely used in most SAP S4HANA deployments today.
Now that we understand the purpose of embedded analytics, let’s explore its technological makeup, the virtual data model (VDM).
The VDM Model
In this section, we will get granular and explain the concept of the VDM model, the backplane of SAP embedded analytics.
The VDM model is subdivided into two major subcategories (CDS and DB Layer), which provides a way to define data models standardized for use across different applications and platforms within the SAP ecosystem.
The Core Data Services (CDS) Layer
The Core Data Services Layer makes up most of the VDM model with the exclusion of the DB Layer.
The CDS layer consists of two tiers; the reusable views layer and the consumption views layer.
The Consumption Layer - VDM Level 3
This is the uppermost layer of the VDM architecture. This layer provides access to the data model through various interfaces, such as OData services or analytical views. It's designed to be consumed by various applications and analytics tools.
The CDS view type used in this layer is consumption views. These views are built on top of reuse views and do not directly access the database tables but rather go through the reuse view layer.
The Re-Use View Layer - VDM Level 2
This layer defines the data model's basic building blocks, such as entities, attributes, and relationships using CDS.
The CDS layer incorporates business logic into the data model via semantic layer modeling; It specifies the business rules, calculations, and annotations for the business data.
The CDS types used in this layer are of four main types: Basic, Private, Interface, and Composite.
VDM Level 1 - The Database Layer
The database tables are at the most basic level. This layer serves as the base for the reusable and consumption models. VDM views are built on this layer to add semantics and make database objects more consumable within the application layer.
Benefits Of SAP Embedded Analytics
This section will explore the benefits of deploying SAP Embedded Analytics within your operational landscapes.
Improved Decision Making: Embedded Analytics can provide real-time insights within the context of an app, allowing users to make more informed decisions based on the data available to them.
Increased User Engagement: By embedding analytics within an app, users can access data without switching to a separate analytics tool, making the app more engaging and increasing the likelihood of user adoption.
Customization: Embedded Analytics can be tailored to the specific needs of an app, allowing developers to create custom reports and dashboards that provide relevant insights to users.
Time and Cost Savings: With Embedded Analytics, developers can save time and costs associated with developing a separate analytics tool. Instead, they can leverage the existing app infrastructure and build analytics capabilities directly within the app.
Scalability: Embedded Analytics can scale with the app, allowing it to grow and evolve alongside the needs of the business.
Security: With Embedded Analytics, data can be securely accessed within the app, ensuring that sensitive information is protected.
How To Explore Fiori’s Analytics Library (Embedded)
For creating and managing embedded analytical apps, SAP S/4HANA provides various tools and features for working with the VDM model, such as the custom KPIs and reports app, the analytical path framework (APF) app, the custom analytical query app, etc.
These tools cater to different user roles, such as analytics specialists, business analysts, and end-users.
In this section, we will focus on the end-user apps and provide a quick walkthrough of how to access sap’s embedded analytics applications in the SAP S/4HANA business suite.
First, access the Fiori Apps Library website
Navigate to All Apps
Click on the filter icon at the bottom of the left pane, select the SAP Fiori - Analytical option, and click ‘GO.’
Your embedded analytical apps should now be displayed on the apps pane to the left.
WRAP-UP
Embedded analytics has revolutionized the way businesses make decisions. With the help of SAP's embedded analytics, companies can now access real-time data and make informed decisions on the spot. For example, a manufacturer using SAP S/4HANA can access embedded analytics that shows low inventory levels and place orders for more supplies, all within the same application. This ability to see and act on data in one place is incredibly valuable and saves businesses time and resources.
Before embedded analytics, business users would have to use separate applications to access data and make decisions, which was a slow and inefficient process. With embedded analytics, users can access data and insights instantly without having to switch between different applications. This seamless integration of analytics into operational systems has made it possible for businesses to make informed decisions in real time, improving productivity, reducing costs, and increasing revenue.
Embedded analytics has transformed how businesses operate, making it easier to access data, make informed decisions, and drive growth. By bringing analytics to the forefront of operational systems, businesses can stay ahead of the competition and achieve their goals more efficiently.
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