What are the use cases of SAP Datasphere over SAP BW4/HANA

[vaibhav_1609]

ABSTRACT 

This blog explores the significance of SAP Datasphere as a centralized hub for managing data in organizations, aiming to address challenges related to scalability, outdated analytical capabilities, data governance, security, and compliance. Through two distinct use cases, the blog demonstrates how SAP Datasphere integrates with DataRobot for advanced machine learning capabilities and enables business builders to identify potential clients, understand their needs, and develop tailored strategies. By leveraging self-service functionalities, data virtualization, and partnerships with platforms like DataRobot, SAP Datasphere empowers businesses to drive innovation, improve decision-making, and foster growth in the data and analytics space. 

Introduction to why datasphere? 

SAP Datasphere is the hub for all our data. We are connected to various source systems and store the data into the datasphere. We have a very decentralized business, so the goal of implementing the datasphere was to centralize to a single source of truth. 

SAP Datasphere offers several benefits for business users that may make it a more attractive option than SAP BW: 

1. Self-service functionalities: SAP Datasphere provides self-service functionalities for business users, enabling them to build their own models and reports using Business Builder, which is designed for semantic modeling. This allows business users to be more involved in data modeling, which can help to relieve the IT department and implement requirements more quickly. 
2. Separation of responsibilities: SAP Datasphere enables a strict separation of responsibilities between IT and the business departments. IT can focus on technical issues such as data cleansing, preparation, business logics, high availability, performance, and data access control, while the business departments can model based on the prepared data models and enrich and supplement the data models with CSV uploads. 
3. SAP BW Bridge: SAP BW Bridge is an extension of SAP Datasphere that enables the migration of data flows from on- premises systems to the cloud. This allows data modeling in SAP Datasphere to take place with data from the SAP BW system, without the need for a full SAP BW/4HANA system. 
4. Hybrid data modeling: SAP Datasphere's hybrid data modeling capabilities allow businesses to federate data via SAP BW/4HANA Model Transfer or use SAP BW Bridge to import data models based on analytical queries. This enables businesses to leverage their existing data models and enrich them using self-service functionalities. 
5. Data virtualization:  SAP Datasphere's data virtualization enables the integration of data from various sources, such as SAP and non-SAP systems, without physically moving or replicating the data.  

SCENARIOS 

First use case of SAP Datasphere with Data robot: 

The customer, a large retail organization, has been using SAP BW for several years. However, they are now facing several challenges that are limiting their ability to innovate and grow. These challenges include: 

Limited scalability: The customer's SAP BW system is struggling to handle the increasing volume of data being generated by their business operations. This is causing delays in processing and reporting, impacting on the customer's ability to make timely decisions. 

Outdated analytical capabilities: The customer's SAP BW system is not equipped with advanced analytical capabilities, such as machine learning and natural language processing. This is limiting the customer's ability to unlock new insights from their data and drive innovation in their business operations. 

Data governance challenges: The customer is facing challenges in managing and governing their data across various systems. This is causing inconsistencies in data quality and increasing the risk of errors in their business operations. 

Security and compliance challenges: The customer is struggling to maintain trust with their stakeholders due to security and compliance challenges in their SAP BW system. This is impacting their ability to attract new customers and partners. 

To address these challenges, the customer has decided to migrate from their SAP BW system to SAP Datasphere. This migration will enable the customer to leverage advanced analytical capabilities, data governance, and scalability, driving innovation and growth in their business operations. 

The migration plan will involve the following steps: 

• Assess the current SAP BW system 
• Plan the migration 
• Migrate the data models: Using SAP BW Bridge, migrate the data models from the SAP BW system to SAP Datasphere. This may involve converting the data models to a format compatible with SAP Datasphere, such as the SAP Data Warehouse Cloud (SDWC) model. 
• Migrate the data quality rules: Migrate the data quality rules from the SAP BW system to SAP Datasphere. This may involve converting the rules to a format compatible with SAP Datasphere, such as the SAP Data Quality (SDQ) rule format. 
• Migrate the data transformation processes: Migrate the data transformation processes from the SAP BW system to SAP Datasphere. This may involve converting the processes to a format compatible with SAP Datasphere, such as the SAP Data Integration (SDI) process format. 
• Test the migration 
• Deploy the migrated data platform 
• Monitor and maintain the migrated data platform 

To use tables from SAP Datasphere in DataRobot, you can follow these steps: 

• Connect to SAP HANA using DataRobot's JDBC connector. 
• In the DataRobot platform, navigate to the AI Catalog tab. 
• Click "Add to Catalog" and select "Existing Data Connection". 
• Choose the connection that holds the data you want to add and select an account. 
• Enter the credentials for the connection, and once validated, select a source for the data. 
• After the content is selected, click "Proceed with registration". 
• DataRobot registers the new tables (datasets) and you can then create projects from them or perform other operations, like sharing and querying with SQL. 

By migrating from their SAP BW system to SAP Datasphere, the customer will be able to overcome the challenges they are currently facing and drive innovation and growth in their business operations. DataSphere focuses on data integration, governance, and advanced analytics, while DataRobot specializes in automated machine learning and model deployment.  

Figure 1: model transfer and data transferring from sap BW system to sap datasphere using sap BW bridge and datasphere connectors 

Figure 2: integrated architecture of sap datasphere and datarobot  

Second use case of SAP Datasphere with Business builder functionality: 

The business builder in SAP Datasphere is responsible for identifying potential clients, understanding their business needs, and developing strategies to meet those needs. The business builder can leverage Collibra, a knowledge management platform, to enhance their capabilities in this process. Here is a step-by-step breakdown of the use case: 

Identify potential clients: The business builder identifies potential clients by conducting market research, attending industry events, and networking with professionals in the data and analytics space. 

Understand client business needs: The business builder gains insights into the client's business needs by conducting interviews, analyzing client data, and observing client behavior. 

Develop strategies to meet client needs: The business builder develops strategies to meet the client's business needs by offering tailored real-time data and analytics solutions, providing consulting services, or offering training and support services. 

Prepare sales pitches: The business builder prepares sales pitches that highlight the benefits of SAP Datasphere and the strategies they have developed to meet the client's business needs. These pitches are tailored to the specific needs of each client. 

Engage in sales activities: The business builder engages in sales activities, such as presenting sales pitches, conducting demonstrations, and participating in industry events. These activities are targeted at potential clients and are designed to generate interest in SAP Datasphere and the strategies the business builder has developed. 

Follow up and close deals: After engaging in sales activities, the business builder follows up with potential clients to ensure that their needs are being met. Once the client's needs are being met, the business builder closes the deal and secures the client as a customer for SAP Datasphere. 

Figure 3: Virtualization 

By following these steps, the business builder in SAP Datasphere can effectively identify potential clients, understand their business needs, and develop strategies to meet those needs. This will enable the organization to attract new clients and grow its business in the data and analytics space. 

Conclusion 

SAP Datasphere, with its advanced self-service capabilities and data virtualization feature, offers a powerful solution for business users to access and analyze their data without relying on IT. By seamlessly integrating with DataRobot, SAP Datasphere enables enterprises to leverage advanced machine learning models, resulting in more intelligent business predictions with advanced analytics. Partnership with DataRobot and integration with Business Builder functionality provides a powerful and comprehensive solution for businesses, enabling them to leverage machine learning models, cut across data silos, and improve their decision-making process. 

[MKreitlein]

Hello @vaibhav_1609 

this is quite an interesting "Blog" ... but somehow I have the feeling that various parts may have been written by KI already, ChatGPT or else, maybe?

What is for example this? I never heard of it inside Datasphere:

SAP Data Quality (SDQ) rule format.
SAP Data Integration (SDI) process format.

I have not yet used the BW Bridge, but for my understanding e.g. all your ABAP transformations work there exactly like in the original BW system.... no new formats required.

What you unfortunately missed to explain in detail is in the first use case:

You are not really precise what the problems are, and how they can be overcome now. You can have the best tool... if don't know how to handle it, it will not work, just like with a bad tool.

E.g. only one topic: "Limited scalability" ... if you cannot handle your data with a scale-out scenario, e.g. 6x 3TB, then you will be lost in Datasphere and broke in the end (max 4TB available for 3,8 Mio. EUR in 5 years). So this is quite a strange case, right?

BR, Martin

[TuncayKaraca]

Hi @vaibhav_1609,

You should have posted this as a blog and not a Q&A.

https://community.sap.com/t5/technology-blogs-by-members/bg-p/technology-blog-member

Regards,
Tuncay