Optimizing an SAP Fiori Application Based on a Real World Example

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Z sap boe-2016-techws-04_vs_fiori-app-with-eclipseluna-accessing-zsap-system

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The document provides steps for developing a sample SAP Fiori application called "Purchase Order Approval" that accesses a SAP backend system running on IBM zSystems. It describes importing backend ABAP code, creating an OData model, configuring SAP Gateway, developing the frontend UI with SAPUI5, and uploading the app to the ABAP frontend server and SAP Fiori Launchpad. The sample app demonstrates how to leverage new proprietary Fiori apps with an on-premise SAP system using Eclipse for development.

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This document summarizes the key impacts of migrating to SAP S/4HANA Finance. Some of the main points are: - Many classic SAP modules will be sunset such as classic asset accounting, credit management, cash management and others. New SAP S/4HANA Finance modules must be used instead. - Summarization hierarchies and summary tables will be removed and replaced by new CDS views for on-the-fly summarization and reporting. - A new integrated planning solution is available to combine financial and management accounting planning with an improved user experience using Excel and BI capabilities. - Variance calculation, WIP calculation, and reporting will have new programs and processes optimized for

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This document provides guidance on implementing script logic in SAP BPC 10.0/7.5. It begins with an executive summary and outlines a sample business scenario. It then describes the data model and key dimensions used in the solutions. The document explains the basic structure of script logic and provides steps for implementation. It also includes a list of common script logic commands and provides examples of how to use some of the main commands like *XDIM_MEMBERSET to define the scope of data. The purpose is to educate users on using script logic to automate key business processes and calculations in SAP BPC.

SAP Business Planning and Consolidation 10.1, version for SAP NetWeaver, provides a unified planning suite to address a wide range of business issues. Now fully supported by the SAP BW on HANA platform, BPC 10.1 provides deeper integration with SAP NetWeaver and can leverage the platform's Integrated Planning (IP) and Planning Applications Kit (PAK) framework. The introduction of SAP Cloud for Planning builds upon this by offering the ability to roll out a public cloud planning application to strategic business units that can plug into the central BPC Plan.

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This document provides guidance on implementing ownership and consolidation calculations in SAP BPC NW 10.0. It discusses creating dimensions and models, preparing data, defining business rules for ownership and consolidation calculations, using logic scripts, inputting data and reports. Specific topics covered include ownership calculations, eliminating ownership using the purchase method, and the consolidation monitor, controls monitor and journal. The implementation follows a typical ownership manager process using hierarchies to track parent-child relationships and an ownership model to store ownership data.

SAP BPC Environment Export Import Implementation Guide

This document provides steps to export and import a BPC environment in SAP HANA. The key steps are: 1. Login to SAP HANA and enter the command '/OUJBR' to access the export/import functionality. 2. Select the 'Execute Backup' option, enter the environment ID and export location, and click 'Execute' to export the BPC environment. 3. To import, enter the command '/OUIMP' , select the exported file, and click 'Execute' to import the BPC environment into the target system. 4. Login to BPC to verify the imported environment.

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SAP BPC on HANA Environment Security Management Implementation Guide

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Clone skills, inc. sap bpc on hana data management v9

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Sapbpc nw 10.0 transactional data load guide

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This document provides step-by-step instructions for loading transactional data from flat files into SAP BPC NW 10.0 using the Data Manager in EPM Office Add-in for Excel. It outlines the required building blocks, describes a sample data model for sales revenue planning, and details the process of verifying dimensions, uploading data files, creating conversion and transformation files, adding and running data load packages, and generating reports.

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This document provides a tutorial overview of Apache Flink, including what Flink is, why it is useful, how it processes both bounded and unbounded data, the anatomy of a Flink application, windowing in Flink, and how it handles event time and process time. Flink is an open-source stream and batch processing platform that can process infinite datasets continuously while maintaining accuracy and recovering from failures. It provides exactly-once semantics through checkpointing and handles both bounded finite datasets and unbounded streaming data through its DataStream and DataSet APIs. The tutorial then discusses windowing concepts in Flink and provides code examples of word count applications with and without windows. It also explains the concepts of event time and processing time in F

Ahead of the Curve: How 23andMe Improved UX with Performance Edge

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This document summarizes a webinar presented by Courtney Ball, Antonio Contreras, and Whelan Boyd from 23andMe on how the company improved user experience through A/B testing and implemented Performance Edge to optimize page load times. The webinar discussed how website performance directly impacts business metrics like conversion rates, highlighted best practices for measuring performance, and explained how standard A/B testing can negatively affect page speeds. It then introduced Performance Edge as a solution that delivers only necessary code variations to visitors, significantly reducing file sizes and browser execution times. 23andMe's case study showed how implementing Performance Edge through Cloudflare Workers dramatically improved their page load performance metrics and allowed them to scale up testing without slowing down

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2015 ist "Big Data" im Gartner Hype Cycle Report verschwunden, und Business-Intelligence-Lösungen finden vor allem in der Cloud neue Beachtung. BI-Experten freuen sich, den Big-Data-Hype mit all seinen neuen Technologien überstanden zu haben. Was passiert aber wirklich in der Praxis? Datengetriebene Firmen erkennen Lambda-Architekturen als geeignete Plattformen, um Daten in Echtzeit und Batch-Modus zu verarbeiten und um flexibel auf neue Anforderungen zu reagieren. In diesen Lambda-Architekturen finden neue Big-Data-Technologien und bewährte BI-Lösungen zusammen, und nur zusammen wird neuer Geschäftswert erzeugt. Dieser Vortrag erklärt Lambda-Architekturen und bringt Big Data sowie BI zusammen.

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