Consuming CAPM Application's OData service into SAP Fiori Application in Business Application Studio

OBJECTIVE

Consuming OData Service of CAPM Application into SAP Fiori Application in Business Application Studio.

CAPM (Cloud Application Programming Model)

It is an open-source framework that uses tools, libraries, and languages to create applications that can be used across multiple SAP products. CAPM is a multi-target application that runs at different times, with the persistence layer running in the HANA DB run time, the server layer running in the Node.js run time, and the UI/UX layer running in the browser run time.

CAPM is one of the approaches to developing cloud applications using the BTP platform. CAPM offers a more structured and seamless framework for data modelling and enhancing integration with services.

Nested JSON to SAP HANA Tables with SAP Integration Suite

In this blog post, I will demonstrate how to send data to SAP HANA Cloud using the Integration Suite. Additionally, I will explain how to handle nested JSON data and distribute it across multiple tables utilizing parallel multicast and mapping functions.

Problem Statement:

We have exposed an API endpoint through which we push data in JSON format and in response we get the insert count in particular tables. The input data contains user details and role details in nested form. We are supposed to insert the user details in User Table whereas in the User-Role mapping table for each role associated with a user, we ensure the creation of a corresponding entry, linking the user's details with their roles. Our requirement is to process the JSON data via CPI and populate these two tables.

Workload in the SAP HANA

Options for Managing Workload

Workload management can be configured at multiple levels: at the operating system-level, by using global initialization settings, and at the session level.

There are a number of things you can do to influence how workload is handled:

• Outside the SAP HANA system on the operating system level you can set the affinity of the available cores.
• You can apply static settings using parameters to configure execution, memory management and peak load situations.
• You can influence workload dynamically at system runtime by defining workload classes.

All of these options have default settings which are applied during the HANA installation. These general-purpose settings may provide you with perfectly acceptable performance in which case the workload management features described here may not be necessary. 

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: 

Integrate C4P-Resource Management with SAP Analytics Cloud or SAP DataSphere

Summary

Embarking on the journey of leveraging SAP S/4HANA Cloud for Projects, Resource Management (C4P), this blog simplifies the process of accessing its APIs, with a focus on the Resource Request functionality. Beginning with preparations, where we gather key information like API URL and credentials, we then explore the capabilities of the Resource Request API in the Business Accelerator Hub. We break down how to find the right URL for accessing resource requests and demonstrate how to connect these APIs to tools like SAP Analytics Cloud or SAP DataSphere. By following these steps, users can seamlessly integrate data from C4P into their analytics workflow, enabling better decision-making and operational efficiency.

Job and Automation Monitoring features - SAP Cloud ALM

SAP Cloud ALM is an out-of-box, native cloud solution which serves as the central hub for managing SAP landscapes, offering guided implementation driven by content and highly automated operations. In this blog post, I aim to delve into a very crucial capability of cloud ALM: Job and Automation Monitoring.

Through Job and Automation monitoring within SAP Cloud ALM, it is possible to monitor SAP S/4 HANA Application jobs, SAP ABAP jobs, SAP BW Process Chains, SAP Build Process Automation Jobs(or SAP Intelligent RPA jobs) and SAP Business workflow and Job scheduler service jobs in customer BTP application.

SAP S/4 HANA Event Management (EM) Deployment Options – stand-alone vs S/4 HANA add-on

Summary

In this decision accelerator, you will know how to decide between S/4 HANA Event Management (EM) to be deployed as stand-alone or as an add-on on SAP S/4HANA in on-premise or private cloud.

Business Requirements

SAP Event Management on SAP S/4HANA is a business application to enable real-time end-to-end business process visibility and status monitoring. It provides a wide range of functions to monitor milestones (called “expected events”), report actual events correlating to the related expected event, and unexpected events. Alerts, notifications, and any kind of automated follow-up activities are triggered by rules evaluating the events upon receiving to automate the detection of deviation and automated reaction to events.

Sharing SAP HANA Cloud instance to multiple subaccounts and creating HDI containers

Overview

This article is telling you how to share single SAP HANA Cloud instance to multiple subaccounts and create HDI container from each subaccount. I am using SAP Cloud Application Programming Model (CAP) Node.js for this article.

Background

When I am planning SAP BTP project system architecture, I am following account model and preparing three subaccounts (development, test, production). At that time, I feel how can I reduce cost of subscription to each subaccount, especially for development environment.

Efficient Memory Storage and Data Loading of SAP HANA Column Tables

Memory storage and Computing Power are fundamental blocks of Cloud Platforms and Infrastructure. The abundance of Memory storage and cost-effective computing power has ensured a lower baseline for cloud adoption. However, anything in excess without considering its consequences can corrupt our practices. I see a similar pattern with the cloud data models.

In SAP HANA, we replicate data predominantly from SAP systems through tables and CDS. Data replicated for tables may range from 1000s or rows to millions of records per month. The queries that join multiple tables without optimal selection of columns and filter conditions can consume the working memory resources. Eventually, despite the promise of infinite data and computing capacity(CC), the reality is there is a finite amount of memory and CC.

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.

An overview of XSA commands for beginners

Overview:

In this article I'll try to explain the expected outcome of XSA commands when executed in Linux environment via command line (xs cli). This blog is aimed at helping understand the xs commands. At first, I also faced the similar dilemma of how XS command works and what is expected outcome. So learning by my experience, sharing most commonly used commands which you can easily use to understand and monitor xs too.

Pre-requisite:

1. OS level access via <sid>adm on HANA DB host

2. User credentials of xsa_admin