Comparative Analysis of Data Selection Techniques in SAP

In SAP systems, selecting the right data extraction method plays a pivotal role in ensuring system efficiency and performance. With vast amounts of data stored in SAP databases, it's essential to choose the right method for data retrieval, especially to keep operations responsive and well-optimized.

In this article, we will explore various SAP data selection techniques such as the Open Cursor, Core Data Services (CDS) views, Database views, and some other advanced strategies. Each has its strengths and weaknesses and understanding them will help you determine the best fit for your specific use case.

How to Connect S4HANA Public Cloud With SAP Datasphere

Introduction:

After reading this article you will be able to establish a connection between SAP S4HANA Public Cloud with SAP Datasphere Public Cloud

Benefits:

You will be able to replicate data from S4HANA Public Cloud to SAP Datasphere Public Cloud

Importing Entities with Semantic of CDS views from S/4HANA On-Premise in SAP Datasphere

Introduction

This blog will explain the details of accessing the CDS views from S/4HANA On-Premise in SAP Datasphere with semantics. This feature helps accessing the data from ERP system with business context and logic intact through CDS views. 

Prerequisite

SAP S/4 HANA version should be 2021, or newer with SAP_BASIS Release 756 or newer. The below note has all the prerequisites in detail

SAP BW Bridge – Integrating with On-Premises ECC / BW servers

To begin with, first we need to add on-Premises server to SAP Cloud connector.

Login to SAP Cloud connector as Administrator.

Go to the path: Sub-account -> Cloud To On-Premise

Extracting Data from S4HANA ODP to SAP Datasphere

An ODP (Operational Data Provisioning)-enabled data source is a data extraction mechanism that uses the ODP framework to allow the transfer of data between systems. It leverages the ODP infrastructure to manage the data extraction process efficiently, ensuring that data is consistently and reliably transferred from the source system to the target system.

To consume S4HANA data to SAP Datasphere via ODP, we need a datasource that is ODP enabled, either we can use some standard datasources like (e.g. 2LIS_11_VAHDR - Sales Document Header Data, 2LIS_11_VAITM - Sales Document Item Data) or we can also create a custom datasource either by using a view or table or some custom CDS view.

Integration Between SAP Datasphere and SAP Analytics Cloud

Introduction

This blog series discusses the integration between SAP Datasphere with SAP Analytics Cloud for data harmony. I aim to provide an overview of SAC, discuss the process of establishing both live and OData connections between SAC and Datasphere, explore Optimized Design Experience, delve into the current planning capabilities bridging these two products, and more.

 

In this introductory blog, I want to provide an overview of the following key aspects for integrating data between SAP Datasphere and SAP Analytics Cloud:

SAP DataSphere – SAP HANA Database Monitoring

Login to SAP DataSphere and navigate to path System -> Configuration. Select the Menu option 'Database Access' -> Database Analysis Users.

Select the option Create for new DB user.

Currency Translation in SAP Datasphere

Currency translation refers to the process of converting financial data from one currency to another.

This is particularly important for multinational companies that operate in multiple countries and use different currencies for their financial transactions.

Currency translation in SAP typically involves the following steps:

1. Setting up currency exchange rates: Before performing any currency translation, exchange rates need to be maintained in SAP. These rates can be manually entered or automatically updated from external sources.

SAP Datasphere's updated Pricing & Packaging: Lower Costs & More Flexibility

The power of SAP Datasphere is growing every day. Bringing together data warehousing, data integration, data catalog, and semantic modeling it perfectly fits the definition of a modern business data fabric.

Replication flows: SAP Datasphere to Google BigQuery

In this blog, we will explore one of the latest innovations from SAP Datasphere. Effectively, from version 2021.03 onwards, SAP Datasphere has introduced the concept of ‘Replication Flows’.  

Think of replication flows as your trusty sidekick in the world of data management. This feature is all about efficiency and ease. It lets you effortlessly copy multiple tables from a source to a target, without breaking a sweat. 

The beauty in this story is that it is cloud-based all the way! Say goodbye to the hassle of dealing with on-premises components like installing and maintaining data provisioning agents. Thanks to SAP Datasphere's cloud-based replication tool, those headaches are a thing of the past. Replication flows support the following source and target systems: 

Connect & Visualize: SAP Datasphere with Qlik Sense

In this Blog, We'll explore how to consume data from SAP Datasphere through ODBC (Open Database Connectivity) and Visualize the data in Qlik Sense which is one of the leading Data Visualization Tools.

Why SAP Datasphere over others?

SAP Datasphere allows seamless connectivity with a wide range of data sources, including on-premises and cloud-based systems. SAP Datasphere is designed to handle large volumes of data efficiently, making it suitable for organizations of all sizes, from small businesses to large enterprises. Its scalable architecture ensures optimal performance even as data volumes grow over time. Graphical low-code/no-code tools to support self-service modeling needs for business users. It has Powerful built-in SQL and data flow editors for sophisticated modeling and data transformation needs.

Modeling an advanced Hierarchy with Directory in SAP Datasphere

In our previous blog, we covered the basics of creating a Hierarchy with Directory. Now, we're taking a step further in this blog by enhancing our model with an extra node type, language-dependent texts, and time-dependency, both for the hierarchies and node assignments. These advanced features are often seen in SAP S/4HANA or SAP BW hierarchies but are also applicable to non-SAP hierarchies. We continue to use a simplified data model with local data for clarity, making it easier to grasp these concepts before applying them to more complex, real-world data sources. The additions to the data model are pointed out in Figure 1, with the numbering corresponding to the section numbers in this blog post. The figure shows all views, and each view has a table with data underneath.

Modeling a basic Hierarchy with Directory in SAP Datasphere

In the previous blog, we provided an overview of the new features introduced with the Hierarchy with Directory. In this blog, we'll guide you through creating a basic Hierarchy with Directory, starting from scratch and progressing to the data preview in an Analytic Model. Our focus is on simplicity, ensuring you grasp the fundamental concepts with minimal complexity. To keep it simple, we use data from local tables, before moving on to data from SAP S/4HANA or SAP BW in future posts. However, the model is complete and comes with a few lines of transaction and master data. In our upcoming blog, we'll enhance the model by introducing advanced elements such as language-dependent texts, additional node types, and time-dependency features.