Practical Guide To Sap Hana And Big Data Analytics

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Practical Guide to SAP HANA and Big Data Analytics

Author: Stefan Hartmann
language: en
Publisher: Espresso Tutorials Gmbh
Release Date: 2018-12-20
In this book written for SAP BI, big data, and IT architects, the authors expertly provide clear recommendations for building modern analytics architectures running on SAP HANA technologies. Explore integration with big data frameworks and predictive analytics components. Obtain the tools you need to assess possible architecture scenarios and get guidelines for choosing the best option for your organization. Know your options for on-premise, in the cloud, and hybrid solutions. Readers will be guided through SAP BW/4HANA and SAP HANA native data warehouse scenarios, as well as field-tested integration options with big data platforms. Explore migration options and architecture best practices. Consider organizational and procedural changes resulting from the move to a new, up-to-date analytics architecture that supports your data-driven or data-informed organization. By using practical examples, tips, and screenshots, this book explores: - SAP HANA and SAP BW/4HANA architecture concepts- Predictive Analytics and Big Data component integration- Recommendations for a sustainable, future-proof analytics solutions- Organizational impact and change managemen
Practical Guide to SAP HANA and Big Data Analytics

Author: Dominique Alfermann
language: de
Publisher: Espresso Tutorials GmbH
Release Date: 2018-12-20
In this book written for SAP BI, big data, and IT architects, the authors expertly provide clear recommendations for building modern analytics architectures running on SAP HANA technologies. Explore integration with big data frameworks and predictive analytics components. Obtain the tools you need to assess possible architecture scenarios and get guidelines for choosing the best option for your organization. Know your options for on-premise, in the cloud, and hybrid solutions. Readers will be guided through SAP BW/4HANA and SAP HANA native data warehouse scenarios, as well as field-tested integration options with big data platforms. Explore migration options and architecture best practices. Consider organizational and procedural changes resulting from the move to a new, up-to-date analytics architecture that supports your data-driven or data-informed organization. By using practical examples, tips, and screenshots, this book explores: - SAP HANA and SAP BW/4HANA architecture concepts - Predictive Analytics and Big Data component integration - Recommendations for a sustainable, future-proof analytics solutions - Organizational impact and change management
A Practical Guide to SAP Data Warehouse Cloud

Author: Klaus-Peter Sauer
language: en
Publisher: Espresso Tutorials GmbH
Release Date: 2022-07-28
Learn about the advantages of SAP Data Warehouse Cloud (DWC): from data management all the way through to visualization, this book covers all the tools you need to set up a modern, cloud-based data warehouse landscape. You can even set up hybrid architectures or convert on-premise SAP BW systems to the SAP BW Bridge. Operating departments will learn how they can use virtual work areas (spaces) to enrich central corporate data with local data without having to copy data or download files. New findings can be easily shared with others. For IT employees in particular, there is an extensive introduction to modeling and the Data Builder. With the editors and functionalities of this tool, you get to know the technical implementation of data modeling in more detail. In addition, the Business Builder offers professional users a simplified analysis of data by reducing the time required for semantic modeling and enrichment of data. After discussing important aspects of the configuration and security of SAP Data Warehouse Cloud, the author looks at the developments that can be expected for this highly dynamic topic in the future. - Basic principles of SAP Data Warehouse Cloud - Virtual interaction between operating departments and IT via spaces - Separation of semantic modeling and the data layer - SAP BW Bridge and Hybrid landscapes