Understanding SAP HANA Systems: Revolutionizing Data Management

In today's fast-paced digital landscape, businesses require robust data management systems to handle the vast amounts of data generated every second. SAP HANA, a high-performance in-memory database developed by SAP SE, has emerged as a game-changer in this domain. This article delves into the core aspects of SAP HANA systems, highlighting their features, benefits, and the impact they have on modern enterprises.

What is SAP HANA?

SAP HANA (High-Performance Analytic Appliance) is an in-memory, column-oriented, relational database management system designed to handle both high transaction rates and complex query processing. Unlike traditional databases that rely on disk storage, SAP HANA stores data in RAM, allowing for incredibly fast data retrieval and processing. This architecture significantly accelerates analytics and transactional processing, making real-time data access a reality.

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:

Unleashing the Power of Custom Widgets in SAP Analytics Cloud

In today's world where data is crucial, it's really important to have analytics solutions that fit our business needs perfectly. With SAP Analytics Cloud (SAC), we can create custom analytical applications that are just right for our needs. One cool thing we can do with SAC is develop custom widgets. These widgets help us add more functions to SAC beyond what it already offers. In this blog post, I'm excited to talk about my experience making a custom SAC widget using a JSON file.

Prerequisites:

1. Proficiency in JavaScript and JSON: Custom widgets in SAC are developed using JavaScript and defined using JSON files. Ensure that you have a good understanding of these languages and their syntax.

Syniti RDG provides a simplified design to create Multi Value Validation and Derivation Rules

Syniti RDG is an SAP-endorsed application on the Business Technology Platform (SAP BTP) to facilitate MDG implementation with intuitive UI and process automation. RDG automates many of the technical configuration steps that are required to implement SAP MDG and it offers a user-friendly interface to be more relatable to business users.

◉ A multi-value check rule is for validating multiple attribute values against a logical condition.

◉ A multi value derivation rule is to derive multiple attributes values based on a logical condition.

The below example is used to create Multi value validation to be triggered for a specific Change Request Type to validate attribute values of Entity ‘BP_CENTRL’ of data model ‘BP’.

SAP HANA Database Creation from SAP BTP

Creation of SAP HANA Database Instance in SAP BTP

1. Open SAP BTP Cockpit and click on subaccount.

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.

Import Data Connection to SAP S/4HANA in SAP Analytics Cloud: Technical Configuration

In this blog we’ll discuss complete steps for Import data connection from S/4 hana on-premise system to SAP Analytics Cloud. The Operating system we are using on which S/4 Hana system is installed is SUSE Linux SP 15.

Here, Our Data source is S/4 Hana from which the SAP Analytics Cloud is connected using the SAP Analytics Cloud Agent and SAP Cloud Connector.

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.

Cost optimized SAP HANA DR options on Google Cloud

Abstract

Business Continuity is of utmost importance for any organization. A well defined High Availability (HA) & Disaster Recovery (DR) strategy ensures business critical SAP Applications accessibility during any planned or unplanned outage. SAP HANA database being a central component of a SAP Application is configured with relevant HA/DR setup to make the business data available at secondary node/site to ensure business continuity.

HA for HANA database is being used as fault tolerance mostly for any infra related failures where HANA database fails over to secondary hot standby node deployed in cluster mode within a single region. RPO and RTO are almost zero in this case as most of the steps are seamless and automated with cluster management. Synchronous HANA replication across zones of the same region ensures the secondary HANA node is in sync with the primary node all the time.