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SERVICES CATALOGUE

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REPORTS DEVELOPMENT USING SAP BUSINESSOBJECTS BI 2025 AND 4.3 SUITES

SAP BUSINESSOBJECTS BI 2025

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SAP BusinessObjects BI 2025 is the next version of SAP's business intelligence suite, scheduled for release on March 12, 2025.

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Main Components:

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  • SAP BusinessObjects Web Intelligence:  ad hoc reporting and analysis tool, which allows users to access and analyse data interactively.

  • Single source universes:  semantic model that facilitates interaction with various data sources, providing a layer of abstraction for end-users.

  • SAP Crystal Reports Classic:  solution for the generation of highly formatted and detailed reports, suitable for specific data presentation needs.

  • SAP Analysis for Microsoft Office:  integration that allows data analysis directly from Microsoft Office applications such as Excel and PowerPoint.

  • SAP BusinessObjects BI Platform:  central infrastructure that supports the administration, security and distribution of reports and analysis throughout the organisation.​

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Key Features:

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  • Web Intelligence improvements:  incorporation of new visualisations and interactive controls, enabling the creation of more attractive and functional dashboards.

  • Offline access:  the possibility of accessing data and reports without an internet connection, facilitating remote work and user mobility.

  • Optimised user interface:  more intuitive and efficient user experience, simplifying report generation and customisation.

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Important Considerations:

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  • End of Support for SAP BusinessObjects BI 4.2: Support for version 4.2 will end on 31 December 2024. Customers are encouraged to upgrade to BI 4.3 or BI 2025 to continue to receive updates and support.

  • Maintenance extension for BI 4.3: the main maintenance for BI 4.3 has been extended until the end of 2026, facilitating a smoother transition to BI 2025.

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SAP BUSINESSOBJECTS BI 4.3​

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SAP BusinessObjects BI 4.3 is the latest version of SAP's business intelligence suite, released on 12 June 2020.

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Main Features and Improvements:

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  • Better User Experience:  the interface has been redesigned to offer a more intuitive and consistent experience, aligning with other SAP products and improving usability and mobility.

  • Hybrid Integration:  SAP BusinessObjects BI 4.3 facilitates interoperability with cloud solutions, enabling organisations to manage various types of analytics across their business and leverage the capabilities of SAP Analytics Cloud.

  • Web Intelligence (Webi) improvements:  new functionalities have been introduced, such as the ability to combine multiple data cubes simultaneously, improving flexibility and reporting performance.

  • Crystal Reports Classic:  the use of Crystal Reports Classic has been enhanced, now allowing it to be connected to .unx universes as a data source, extending detailed reporting capabilities.

  • Improved Data Model:  the introduction of Data Mode allows users to preview, prepare, transform and combine data cubes dynamically and efficiently.

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Additional Considerations:

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  • End of support for previous versions:  SAP BusinessObjects BI 4.2 primary support ended on 31 December 2022, with priority support until 2024. Customers are encouraged to upgrade to BI 4.3 for continued support and updates.

  • BI 4.3 Lifecycle:  SAP BusinessObjects BI 4.3 will be supported until at least 2027, offering organisations a stable and reliable platform for their business intelligence needs.

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SAP Analytics Cloud

ANALYTICS APPLICATIONS WITH SAP ANALYTICS CLOUD (SAP)

SAP Analytics Cloud (SAC) is a powerful platform that combines analytics, planning and visualisation capabilities in a single cloud-based solution. Here are some examples of analytics applications you can develop using SAC, along with their features and benefits:


1. Financial Performance Dashboard

Description: an interactive dashboard that provides a comprehensive view of the company's financial performance.

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Features
 

  • Financial KPIs: visualisation of key indicators such as revenues, costs, profit margins and EBITDA.

  • Trend analysis: trend graphs and year-on-year comparisons to assess performance.

  • Segmentation: possibility to filter by departments, regions or specific products.

  • Forecasting: predictive models to estimate future financial results.​​​

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Benefits

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  • Improves visibility of financial performance in real time.

  • Facilitates strategic decision-making based on accurate and up-to-date data.

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2. Sales and Marketing Analysis

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Description: A dashboard to analyse sales and marketing metrics such as campaign effectiveness and salesperson performance.

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Features

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  • Customer segmentation: data analysis by customer segments, regions or products.

  • Campaign Effectiveness: evaluation of the return on investment (ROI) of marketing campaigns.

  • Sales Funnel Visualisation: graphical representation of the sales process from lead generation to closing.

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Benefits

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  • Enables sales and marketing teams to adjust strategies based on actual performance.

  • Optimises resource and budget allocation based on performance data.​​

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3. Financial and Budgetary Planning
 

Description: an application for business planning and budgeting.

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Feautures

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  • Planning models: creation of planning scenarios and financial simulation.

  • Data Integration: import of historical data to support budgeting.

  • Review and Approval: workflows for budget review and approval.​​

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Benefits

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  • Facilitates collaborative planning and budget management.

  • Allows simulations to assess the impact of different financial scenarios.

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4. Operations and Logistics Analysis
 

Description: a dashboard to monitor and optimise operations and the supply chain.

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Features

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  • Operational Indicators: tracking of operational KPIs such as cycle times, operating costs and inventory levels.

  • Performance Analysis: evaluation of supplier and logistics performance.

  • Alerts: configuration of alerts for significant deviations or operational problems.

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Benefits

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  • Improves operational efficiency and reduces costs through detailed analysis.

  • Facilitates rapid identification and resolution of supply chain issues.

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5. Human Resources Assessment
 

Description: a dashboard to analyse data related to personnel and human resource management.

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Features

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  • Turnover analysis: visualisation of turnover rates and causes.

  • Employee Performance: performance evaluation and productivity analysis.

  • Compensation and Benefits: analysis of salary structures and benefits.​

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Benefits

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  • Helps manage talent and improve employee retention.

  • Facilitates human resource planning and optimisation of organisational structure.

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6. Customer Experience Analysis
 

Description: an application to measure and analyse customer satisfaction and user experience.

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Features

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  • Satisfaction Surveys: integration of survey data and customer comments.

  • Feedback Analysis: identification of trends and areas for improvement based on customer feedback.

  • Experience segmentation: evaluation of customer experience by segment or channel.

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Benefits

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  • Enables the company to improve customer experience and loyalty.

  • Provides actionable insights to improve products and services.

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General Benefits of using SAP Analytics Cloud

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  • Integration: ability to integrate data from various sources, both internal and external.

  • Interactivity: interactive dashboards that allow users to explore and analyse data dynamically.

  • Accessibility: cloud-based access that enables query and analysis from anywhere.

  • Collaboration: collaborative functions that facilitate teamwork and joint decision-making.

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SAP Analytics Cloud provides a flexible and powerful platform for building analytics applications that meet a wide range of business needs, facilitating informed, data-driven decision making.

ETL Standard Process

EXTRACTION, TRANSFORMATION AND LOADING PROCESSES (ETL)

Developing extract, transform and load (ETL) processes with tools such as SAP Datasphere, SAP Data Services, Microsoft PowerBI and IBM DataStage involves a number of steps and considerations to ensure efficient and effective data integration. The following explains how this process is executed with each of these tools, as well as their key features and functionalities.​

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SAP Datasphere

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Description: SAP Datasphere (formerly known as SAP Data Warehouse Cloud) is an enterprise data integration and management solution in the cloud.

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ETL Process Development

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  • Extraction: connects to multiple data sources, including SAP and non-SAP systems. Provides connectors to various databases, applications and cloud services.

  • Transformation: uses container-based workflows and transformations to process data. Supports data cleansing, enrichment and advanced data transformation.

  • Load: define load targets and configure how data should be inserted, updated or deleted at the target. You can load data into SAP HANA, other cloud data stores or storage solutions.

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Key Features

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  • Enterprise Data Management: provides capabilities for enterprise data management and governance.

  • Data Integration: facilitates data integration in hybrid and multi-cloud environments.

  • Scalability: designed to handle large data volumes and complex cloud operations.

 

SAP Data Services

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Description: SAP Data Services is a data integration and data quality tool that enables complex ETL processes.

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ETL Process Development

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  • Extraction: connects to various data sources, such as databases, flat files, SAP applications and web services. Uses pre-defined or custom connectors to access the required data.

  • Transformation: Use a visual design environment to define data transformations. You can apply data cleansing, enrichment, validation and transformation functions. Available transformers include filters, aggregations, joins and complex calculations.

  • Load: define data targets, which can be databases, data warehouses, or cloud systems. Configure load properties, such as updating, inserting or deleting data at the destination.

 

Key Features

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  • Graphical Interface: provides an intuitive graphical interface for designing and managing ETL processes.

  • Data Quality: includes tools to ensure data quality and cleanliness.

  • Integration: extensive connectivity with data sources in both on-premises and cloud environments.​​​

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Retool

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Description:  Retool is a development platform that allows you to create internal applications quickly and efficiently, simplifying the creation of complex interfaces and processes. With a low-code approach, Retool allows development teams to integrate, visualize and manipulate data from different sources with ease, without the need to build each component from scratch.

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Key Features
 

  • Integration with multiple databases and APIs:  supports connections to databases such as PostgreSQL, MySQL, MongoDB, and REST or GraphQL APIs, making it easy to create applications that interact with data in real time.

  • Intuitive user interface:  offers a variety of pre-built visual components (tables, charts, graphs, forms, buttons) that can be dragged and customized, reducing development time.

  • Process automation:  facilitates the automation of tasks and workflows within applications, ideal for managing and visualizing large volumes of data efficiently.

  • Security and scalability: being hosted in the cloud, Retool offers secure and scalable integrations, particularly when used on platforms such as Microsoft Azure.

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Microsoft PowerBI

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Description: Microsoft's data analytics service aimed at providing interactive visualisations and business intelligence (BI) capabilities with an interface simple enough for end users to create their own reports and dashboards. The tool in this package for building ETL processes is called Power Query.

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ETL Process Development

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  • Extraction: connects to a variety of data sources, including databases, files, web services and other applications. Power Query in PowerBI allows you to connect to and extract data from these sources.

  • Transformation: Use Power Query's query editor to apply transformations to data. Transformations can include cleaning data, merging data, creating calculated columns and applying filters.

  • Load: loads the transformed data into the PowerBI data model, where it is ready for viewing and analysis. You can define how the data is updated, either manually or on a scheduled basis.

 

Key Features

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  • Data integration: extensive connectivity with different data sources and support for multiple formats.

  • Interactivity: powerful visualisation and interactive analysis capabilities.

  • Ease of Use: intuitive and easy-to-use interface for designing ETL processes and creating reports and dashboards.

 

IBM Datastage

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Description: IBM DataStage is a robust data integration tool for designing and executing ETL processes.
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ETL Process Development

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  • Extraction: uses connectors and adapters to extract data from a variety of sources, including databases, files, enterprise applications and web services.

  • Transformation: designs ETL processes using a graphical interface that enables the application of complex transformations. DataStage supports transformations such as filtering, grouping, sorting and data derivation.

  • Load: configures load processes to insert, update or delete data to defined destinations, which can be databases, data warehouses or cloud systems.

 

Key Features

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  • Distributed Architecture: enables the execution of ETL processes in a distributed environment to improve performance.

  • Flexibility: supports a wide variety of data sources and destinations.

  • Scalability: capable of handling large volumes of data and complex processes.

 

Overall Comparison

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SAP Datasphere:  ideal for cloud-based data integration and analysis within the SAP environment, with a centralised business approach.

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SAP Data Services:  excellent for complex ETL processes and projects that require high data quality and connectivity between different sources.

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Retool:  low-code platform for rapid internal application development and ETL process management, ideal for migrations from traditional platforms to the cloud (such as Microsoft Azure), with easy integration and workflow automation.

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Microsoft PowerBI:  powerful for data visualisation and analysis, with basic ETL capabilities through Power Query, ideal for interactive dashboards.

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IBM DataStage:  robust and flexible, perfect for distributed data environments, large volumes and advanced ETL workflows.

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Each tool has its niche based on project size, data complexity and integration, development or analysis needs and can be chosen based on specific project requirements, data environment and integration needs.

SAP BW to Datasphere

FUNCTIONAL CONSULTING IN MIGRATION OF SAP BW SYSTEMS TO SAP BW/HANA OR SAP DATASPHERE

Migrating an SAP BW system to SAP BW/4HANA or SAP Datasphere involves a detailed process that may vary depending on the specific characteristics of the current system and target solutions. A description of migrations to each platform is listed below:​

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SAP BW to SAP BW/4HANA Migration

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SAP BW/4HANA is the SAP HANA-optimised version of the SAP BW system. This migration is generally performed to take advantage of the improved performance, simplified architecture and new functionalities available in SAP BW/4HANA.

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Steps for SAP BW/4HANA Migration

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  • Assessments and Planning:

    • Current System Assessment: performs a comprehensive analysis of the existing BW system. Identifies data models, ETL processes, InfoProviders, and dependencies.

    • Migration Planning: Develops a detailed plan including timelines, resources required, and strategies for managing the differences between BW and BW/4HANA.

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  • Environment Preparation:

    • SAP BW Upgrade: ensure that the current BW system is upgraded to an SAP BW/4HANA compatible version.

    • Data Preparation: cleans and consolidates data to facilitate migration. Remove obsolete objects and review extract, transform and load (ETL) processes.

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  • Use of the SAP BW/4HANA Migration Cockpit component:

    • Migration of Objects: you use the SAP BW/4HANA Migration Cockpit component to convert objects from the BW system to BW/4HANA. This includes InfoObjects, InfoProviders, DSO (DataStore Objects), and loading processes.

    • Model Reconfiguration: adapts existing data models to the new BW/4HANA architecture. This ensures that models are optimised for the SAP HANA database.

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  • Testing and Validation:

    • Data Integrity Testing: extensive testing is performed to verify that data has been migrated correctly and that ETL processes are working as expected.

    • Performance Validation: Evaluates the performance of the new system and adjusts configurations to optimise response time and workload.

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  • Deployment and Support:

    • Production Deployment: proceeds with the deployment of the BW/4HANA system in the production environment.

    • Post-Migration Support: Ongoing support is provided to resolve issues that may arise and to optimise performance.

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Benefits of SAP BW/4HANA Migration

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  • Improved Performance: Leverages the in-memory processing capabilities of SAP HANA.

  • Simplification: reduce the complexity of the data model and architecture.

  • Advanced Functionality: access new tools and functionality for data analysis and visualisation.

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SAP BW to SAP Datasphere Migration

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SAP Datasphere is a cloud data integration and management platform that enables data orchestration and integration in hybrid and multi-cloud environments. Migrating to SAP Datasphere is appropriate when looking to modernise your data infrastructure and leverage advanced cloud integration capabilities.
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Steps for SAP Datasphere Migration

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  • Assessments and Planning:

    • Current System Analysis: examines the existing SAP BW system to understand data models, ETL processes and current integrations.

    • Migration Planning: defines a migration strategy that considers the transition to SAP Datasphere and how to integrate existing data and processes.

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  • Environment Preparation:

    • Data Preparation: data cleansing and preparation is performed. It is necessary to ensure that the data is ready to be integrated into SAP Datasphere.

    • SAP Datasphere Configuration: the SAP Datasphere environment is configured, including connections to data sources and integration settings.

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  • Data and Process Migration:​

    • Use of Migration Tools: SAP tools and services are used to migrate data and processes from SAP BW to SAP Datasphere. This may include the use of Data Intelligence for data integration or the SAP BW Bridge component.

    • ETL Process Reconfiguration: ETL processes are adapted and reconfigured to work in the new SAP Datasphere environment.

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  • Testing and Validation:

    • Integration Testing: verifies that data is correctly integrated into SAP Datasphere and that ETL processes are working properly.

    • Functionality Validation: ensures that all functionalities and data processes are operational and that users can access the required information.

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  • Deployment and Support:​

    • Production Deployment: deployment is performed in the production environment and ensures that everything is working as expected.

    • Post-Migration Support: Ongoing support is provided to address any issues that arise and to make adjustments and optimizations as needed.

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Benefits of SAP Datasphere Migration

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  • Cloud Flexibility: enables data integration in hybrid and multi-cloud environments.

  • Data Governance: improves data governance and quality through advanced tools.

  • Scalability: offers a scalable architecture to handle large volumes of data and complex processes.

 

Comparative Summary

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SAP BW/4HANA: ideal for organisations looking to optimise performance and simplify architecture using SAP HANA technology. It is suitable for companies that want to maintain an integrated SAP solution.

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SAP Datasphere: best for organisations looking for a more flexible and modern data integration solution, capable of operating in hybrid and cloud environments. It is suitable for companies that want to integrate and manage data across a broader and more diverse data architecture.

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Both options offer significant improvements over the traditional SAP BW system, but the choice between SAP BW/4HANA and SAP Datasphere will depend on the organisation's specific integration needs, technology environment and data management strategies.

S/4HANA Greenfield Implementation

FUNCTIONAL CONSULTING ON NEW SAP S/4HANA SYSTEM IMPLEMENTATIONS BASED ON SAP AND NON SAP SOURCE SYSTEMS

When undertaking a new SAP S/4HANA (Greenfield) implementation, the focus is on building a new SAP S/4HANA instance from scratch, rather than upgrading or migrating an existing system. This can be an opportunity to re-engineer processes and adopt the latest best practices without the limitations of the old system. Key areas of functional consulting in this type of implementation, for both SAP and non-SAP source systems, are detailed here.

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Initital Assessment and Planning

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  • Interviews and Workshops: working sessions are held with key stakeholders to understand their needs and expectations.

  • Requirements Documentation: functional requirements are documented in detail, identifying critical processes and areas for improvement.

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Project Planning

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  • Scope definition: the scope of the project is established, including modules and functionalities to be implemented.

  • Timeline and Resources: a project plan is developed with milestones, timeline and resource allocation.

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System Design

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System Blueprint:

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  • Process design: business processes are designed in SAP S/4HANA based on the requirements gathered, using SAP best practices and standard models.

  • Initial Configuration: the initial configuration of the system is defined, including organisational structures and basic parameters.

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Customisations and Extensions:

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  • Necessary Extensions: we seek to identify and develop specific extensions using tools such as SAP Fiori and SAP Business Technology Platform, if the standard processes do not cover all needs.

  • Functionality Integration: interfaces and integration points are designed to connect SAP S/4HANA with other non-SAP systems.

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SAP and non-SAP Source System Integration

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  • Integrations with SAP Source Systems:

    • Data Mapping: data mapping and data integration between SAP S/4HANA and existing SAP systems (if any) is performed using the SAP S/4HANA Migration Cockpit tool.

    • Interfaces and Connectivity: interfaces are configured to ensure smooth data transfer and integration between SAP S/4HANA systems and source systems.

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  • Integration with non-SAP systems:

    • Connectivity: interfaces are developed and configured to integrate SAP S/4HANA with non-SAP systems using SAP Cloud Platform Integration (CPI).

    • Data Transformation: Data transformation and cleansing processes are established to ensure consistency and integrity of information.

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Configuration and Development

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Modules Configuration

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  • Functional Configuration: SAP S/4HANA functional modules such as Finance (FI), Logistics (LO), Human Resources (HR), etc., are configured according to business needs.

  • Process Optimisation: new SAP S/4HANA capabilities and enhancements are leveraged to optimise processes and improve operational efficiency.

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Development and Customisation

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  • Customisation development: customisations are developed (if necessary) to meet specific requirements not covered by the standard configuration.

  • Customisation testing: extensive testing is carried out to ensure that customisations work correctly and do not adversely affect other areas of the system.​

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Training and Change Management

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Users Configuration

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  • Training Plan: a training plan is designed and implemented for end users, including training on the new functionalities and processes in SAP S/4HANA.

  • Documentation and Support: user documentation and support is provided during the adoption phase.

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Change Management

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  • Communication: Clear and continuous communication is maintained with all stakeholders to manage expectations and facilitate the transition.

  • Change Management Plan: a plan is developed to manage resistance to change and facilitate the adoption of the new system.

 

Testing and Deployment

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System Testing

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  • Unit and Integration Testing: unit and integration testing is performed to ensure that all system components function correctly and that integrations are successful.

  • User Testing: user acceptance tests are carried out to validate that the system meets business requirements and expectations.

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Deployment

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  • Deployment Strategy: A deployment strategy is defined which may include a gradual transition or a complete changeover depending on the size and complexity of the project.

  • Post-Deployment Support: Ongoing support is provided after deployment to resolve issues and make necessary adjustments.

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Additional Recommendations (for all phases described above)

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  • Adoption of Best Practices: the aim is to use best practices recommended by SAP and success stories to ensure an efficient and effective implementation.​

  • Continuous Assessment: periodic reviews of the project are intended to identify and resolve problems in a timely manner.

  • Innovation and Flexibility: it is suggested to the whole team to keep an open mind to innovation and adapt the system to new technologies and changes in the business.

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In conclusion, a Greenfield SAP S/4HANA system implementation offers a unique opportunity to redefine and optimise business processes from the ground up. With careful planning and execution, it is possible to achieve effective integration and maximise the value of the new system.

Selective Data Transition S/4HANA

FUNCTIONAL CONSULTANCY IN SAP S/4HANA SYSTEM MIGRATIONS WITH SELECTIVE DATA TRANSITION

Selective data transitions in the SAP S/4HANA implementation focus on moving only the necessary data from the source systems to the new SAP S/4HANA instance. This approach is useful when you want to avoid migrating historical or redundant data, thus ensuring a cleaner and more efficient implementation. The following details how to perform effective functional consulting for a selective data transition based on SAP and non-SAP source systems.

 

Functional Consultancy on Selective Data Transitions​​

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Requirements Assessment and Planning

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  • Data Requirements Assessment:​

    • Understand Business Needs: identify what data is critical to current and future operations. This includes master data, transactional data and historical data.

    • Define Data Scope: determine what data will be migrated, what data will be archived and what data will not be migrated.

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  • Data Migration Planning:​

    • Project Plan: a project plan is developed for the data transition, including timeline, resources, and key activities.

    • Migration Strategy: The migration strategy is defined, which may include tools, methods and processes for data migration.

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Data Analysis in SAP Source Systems

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  • Data Inventory:

    • Data Review: an inventory of the data in the SAP source systems is performed, including master data (customers, suppliers, materials), transactional data (orders, invoices) and historical data.

    • Data Quality: data quality is assessed and incorrect or redundant data that will not be migrated is cleaned.

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  • Data Mapping:

    • Definition of Mapping Rules: mapping rules are established to transform data from the source system to the format required by SAP S/4HANA.

    • Migration Tools: tools such as SAP Data Services or SAP S/4HANA Migration Cockpit are used for data mapping and transformation.

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Data Analysis in Non SAP Source Systems​

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  • Non SAP Data Integration:​

    • Connection and Extraction: connections to non-SAP systems are set up to extract the necessary data. This may involve the use of ETL (Extract, Transform, Load) processes or data integration tools.

    • Data Transformation: non-SAP data is adapted to the format required by SAP S/4HANA through transformation and cleansing processes.

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  • Interfaces Definition:

    • Interface Design: interfaces and integration points are designed to ensure that data is transferred correctly from non-SAP systems to SAP S/4HANA.

    • Integration Validation: Tests are performed to validate that non-SAP data integration works correctly.

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Configuration and Testing

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  • SAP S/4HANA System Configuration:

    • Data Structures: you configure the data structures in SAP S/4HANA, such as organisational structures and master data parameters.

    • Data Loading Process: you define the data loading process in SAP S/4HANA, ensuring that the data is loaded correctly in the corresponding modules.

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  • Data Testing​:

    • Data Integrity Testing: tests are performed to ensure the integrity and accuracy of the migrated data. This includes data reconciliation and validation testing.​

    • User Testing: User acceptance tests are conducted to ensure that the migrated data meets business expectations.

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Change Management and Training

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  • Change Management:

    • Communication: maintain ongoing communication with stakeholders on the progress of the data migration and any issues that arise​.

    • Documentation: document the data migration processes and any customisations made.

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  • User Training:

    • Training: training is provided to users on how to work with the data in the new system and how to interpret the migrated data.

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Post-Migration Support

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  • Ongoing Support:

    • Troubleshooting: ongoing support is provided to resolve issues related to the migrated data and adjust processes as needed.

    • Data Monitoring: Data is monitored after migration to ensure that no problems arise and that data quality remains high.

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Additional Recommendations (for all phases described above)

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Continuous Assessment

  • Periodic Reviews: Periodic reviews of the migration process are suggested in order to identify and resolve problems in a timely manner.

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Use of Tools and Methodologies​

  • SAP tools: it is suggested to take advantage of specific SAP tools for data migration, such as SAP S/4HANA Migration Cockpit and SAP Data Services.

  • Best Practices: It is suggested to apply SAP recommended best practices to ensure efficient and effective data migration.

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Adaptability

  • Flexibility: The whole team is encouraged to maintain flexibility to adapt to any changes in data requirements or project scope.

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In conclusion, a well-planned and executed selective data transition can significantly improve the efficiency and effectiveness of the SAP S/4HANA implementation.

Teamwork in the systems room

ADMINISTRATION OF SAP BUSINESSOBJECTS, SAP DATA SERVICES AND SAP BW PLATFORMS (UNDER UNIX, LINUX AND WINDOWS OPERATING SYSTEMS) 

The administration of SAP BusinessObjects, SAP Data Services and SAP BW platforms involves a number of specific tasks and skills to ensure the performance and stability of the systems in different operating environments such as UNIX, Linux and Windows. Below is a general breakdown of what is involved in the administration of each of these platforms:

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SAP BusinessObjects

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General Administration

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  • Installation and Configuration: installation of the software on Windows or UNIX/Linux servers, and initial configuration of BusinessObjects services.

  • Maintenance: application of patches and updates; monitoring and optimisation of server performance.

  • Security: configuration of roles and permissions, administration of users and groups.​

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Content Management

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  • Universes: administration and maintenance of universes, which act as a semantic layer between the database and the reporting tools.

  • Reports and Dashboards: configuration of reports, dashboards and the scheduling of their updates.​​

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Monitoring and Troubleshooting

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  • Logs: Review error and event logs for troubleshooting.

  • Performance: monitoring system performance and adjusting settings as needed.

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SAP Data Services

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General Administration

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  • Installation and Configuration: installation of SAP Data Services in the appropriate environments (Windows/Linux/UNIX) and configuration of the necessary components.

  • Maintenance: application of patches, updates and maintenance of the servers.

 

ETL Workflows

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  • Design and Management: creation and maintenance of ETL (Extract, Transform and Load) workflows to integrate data from different sources.

  • Monitoring: monitoring of ETL jobs to ensure proper execution and error resolution.​

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Security

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  • Roles and Permissions: configuration of roles and permissions for users and ensuring data integrity.

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SAP BW (Business Warehouse)

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General Administration

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  • Installation and Configuration: installation of the SAP BW system on Windows, Linux or UNIX servers, and configuration of the basic components.

  • Maintenance: application of updates and patches; administration of associated databases.

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Modelling and Data Management​

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  • Infoproviders: creation and administration of InfoProviders, including InfoCuboss, Data Store Objects (DSOs), and MultiProviders.

  • ETL and Transformations: configuration of ETL processes and data transformations.​

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Monitoring and Optimization

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  • Performance: monitoring BW system performance and adjusting settings to improve efficiency.

  • Logs and Errors: reviewing and resolving errors and performance issues through logs and diagnostic tools.​

 

Operating Environments (for all listed applications)

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  • Windows: administration includes service management, task scheduling and system security administration.

  • ​Linux / UNIX: administration includes script management, system level service configuration and file and directory permissions management.

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Other Services Considered for Platform Management

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  • Documentation: Detailed documentation of all configurations and changes made will be maintained.

  • Training: we keep abreast of the latest updates and best practices through continuous training of our administrators.

  • Testing: Performance and security testing will be performed regularly to identify and resolve issues before they impact the production environment.

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