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Produktbild: SAP Data Intelligence

SAP Data Intelligence The Comprehensive Guide

Aus der Reihe SAP Press Englisch

89,95 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

29.12.2021

Verlag

Rheinwerk Publishing

Seitenzahl

783

Maße (L/B/H)

26,2/18,4/5,1 cm

Gewicht

1746 g

Auflage

1

Sprache

Englisch

ISBN

978-1-4932-2162-2

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

29.12.2021

Verlag

Rheinwerk Publishing

Seitenzahl

783

Maße (L/B/H)

26,2/18,4/5,1 cm

Gewicht

1746 g

Auflage

1

Sprache

Englisch

ISBN

978-1-4932-2162-2

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: SAP Data Intelligence

  • ... Preface ... 21



    ... Why Read This Book? ... 21



    ... Audience ... 22



    ... Structure of the Book ... 23



    ... Acknowledgments ... 28



    ... Conclusion ... 29



    PART I ... Getting Started ... 31



    1 ... The Data Fabric for the Intelligent Enterprise ... 33



    1.1 ... Data Fabric ... 34



    1.2 ... Data Orchestration ... 38



    1.3 ... SAP Business Technology Platform ... 40



    1.4 ... SAP Data Intelligence ... 43



    1.5 ... Summary ... 50



    2 ... Architecture and Capabilities ... 51



    2.1 ... Genesis of SAP Data Intelligence ... 52



    2.2 ... SAP Data Intelligence Architecture ... 60



    2.3 ... Deployment Options and Bring Your Own License Model ... 63



    2.4 ... Kubernetes Cluster and Containers ... 68



    2.5 ... SAP Data Intelligence Launchpad ... 86



    2.6 ... Summary ... 91



    3 ... Setup and Installation ... 93



    3.1 ... Landscape Sizing ... 93



    3.2 ... SAP Cloud Appliance Library ... 99



    3.3 ... On-Demand Cloud Provisioning and Instance Sizing ... 107



    3.4 ... Setting Up SAP Data Intelligence on SAP Cloud Appliance Library ... 113



    3.5 ... SAP Data Intelligence 3.0 Installation On-Premise ... 150



    3.6 ... Summary ... 168



    4 ... Using SAP Data Intelligence Applications ... 169



    4.1 ... SAP Data Intelligence Launchpad Applications ... 169



    4.2 ... Applications for Data Engineers ... 172



    4.3 ... Applications for Data Scientists ... 177



    4.4 ... Applications for Modelers and Auditors ... 179



    4.5 ... Applications for System Administrators ... 182



    4.6 ... Summary ... 189



    PART II ... Data Management, Orchestration, and Machine Learning ... 191



    5 ... Metadata-Driven Data Governance ... 193



    5.1 ... Metadata Explorer for Data Governance ... 194



    5.2 ... Data Profiling to Understand Data ... 197



    5.3 ... Managing Publications and Data Catalogs ... 202



    5.4 ... Defining Data Quality Rules and Running Rulebooks ... 214



    5.5 ... Data Lineage from Transformation History ... 230



    5.6 ... Summary ... 235



    6 ... Modeling Data Processing Pipelines ... 237



    6.1 ... Using the SAP Data Intelligence Modeler ... 237



    6.2 ... Creating and Managing Connections ... 250



    6.3 ... Self-Service Data Preparation with the Metadata Explorer ... 255



    6.4 ... Integrating, Processing, and Orchestrating Workflows ... 261



    6.5 ... Scheduling and Monitoring Data Pipelines ... 270



    6.6 ... Summary ... 273



    7 ... Creating Operators and Data Types ... 275



    7.1 ... Creating Custom Operators ... 276



    7.2 ... Implementing Runtime Operators ... 288



    7.3 ... Creating Data Types ... 290



    7.4 ... Summary ... 293



    8 ... Building Docker Images ... 295



    8.1 ... Containers in Pods and Pods in Clusters ... 295



    8.2 ... Assembling a Docker Image ... 298



    8.3 ... Dockerfile Inheritance ... 303



    8.4 ... Using Docker with Python ... 305



    8.5 ... Summary ... 308



    9 ... Machine Learning ... 309



    9.1 ... Machine Learning with SAP ... 310



    9.2 ... Machine Learning with SAP Data Intelligence ... 328



    9.3 ... Using the ML Scenario Manager ... 333



    9.4 ... ML Data Manager in Data Workspaces and Data Collections ... 365



    9.5 ... Summary ... 371



    10 ... Jupyter Notebook ... 373



    10.1 ... Jupyter Notebook Fundamentals ... 374



    10.2 ... Working with SAP HANA Cloud ... 386



    10.3 ... Data Science Experiments with Jupyter Notebook ... 405



    10.4 ... JupyterLab as the Next-Gen Jupyter Notebook ... 430



    10.5 ... Summary ... 437



    11 ... SAP Data Intelligence Python SDK ... 439



    11.1 ... Using SAP Data Intelligence Python SDK ... 440



    11.2 ... Accessing Artifacts Using Methods ... 448



    11.3 ... Machine Learning Tracking SDK ... 450



    11.4 ... Summary ... 454



    PART III ... Integration ... 457



    12 ... Integrating with ABAP Systems ... 459



    12.1 ... Integration Scenarios ... 459



    12.2 ... Provisioning Data from ABAP Systems ... 465



    12.3 ... Using Operators to Trigger Execution in an ABAP System ... 472



    12.4 ... SAP BW/4HANA and SAP Data Intelligence Hybrid Data Virtualization ... 478



    12.5 ... Additional Connectivity ... 485



    12.6 ... Summary ... 495



    13 ... Integrating with Non-SAP Systems ... 497



    13.1 ... Non-SAP Cloud System Connectivity ... 497



    13.2 ... Non-SAP On-Premise System Connectivity ... 510



    13.3 ... Summary ... 513



    14 ... Integrating Big Data Workloads with SAP Vora ... 515



    14.1 ... SAP Vora in Kubernetes Framework ... 516



    14.2 ... Data Modeling in SAP Vora ... 524



    14.3 ... Hierarchies in SAP Vora ... 536



    14.4 ... Full-Text Search in SAP Vora ... 540



    14.5 ... Summary ... 542



    15 ... Integrating with SAP Data Warehouse Cloud ... 543



    15.1 ... Overview of SAP Data Warehouse Cloud ... 543



    15.2 ... Understanding Spaces ... 549



    15.3 ... Exploring Connections and Using the Data Builder ... 561



    15.4 ... Data Builder in SAP Data Warehouse Cloud versus Pipelines in SAP Data Intelligence ... 570



    15.5 ... Summary ... 570



    16 ... Integrating with SAP Analytics Cloud ... 571



    16.1 ... Overview of SAP Analytics Cloud ... 571



    16.2 ... Use Operators: Read File, Formatter, and Producer ... 582



    16.3 ... Pipelines to Train, Predict, and Visualize Data ... 587



    16.4 ... Summary ... 591



    PART IV ... System Management, Security, and Operations ... 593



    17 ... Administration ... 595



    17.1 ... System Management Command-Line Client Reference ... 595



    17.2 ... Administration Applications ... 599



    17.3 ... Monitoring the SAP Data Intelligence Modeler ... 616



    17.4 ... SAP Data Intelligence System Logging ... 626



    17.5 ... System Diagnostics ... 631



    17.6 ... Summary ... 637



    18 ... Security ... 639



    18.1 ... Approach to Data Protection ... 639



    18.2 ... Authenticating Services and Users ... 642



    18.3 ... Securely Connecting On-Premise Systems ... 658



    18.4 ... Summary ... 659



    19 ... Maintenance ... 661



    19.1 ... Understanding Operational Modes or Run Levels ... 661



    19.2 ... Switching the Platform to Maintenance Mode ... 662



    19.3 ... Increasing System Management Persistent Volume Size ... 665



    19.4 ... Performing Backups ... 668



    19.5 ... Summary ... 671



    20 ... Application Lifecycle Management ... 673



    20.1 ... Version Control System ... 673



    20.2 ... Git ... 674



    20.3 ... Continuous Integration and Continuous Delivery ... 707



    20.4 ... DevOps Fundamentals and Tools ... 713



    20.5 ... SAP Data Intelligence as the MLOps Platform ... 723



    20.6 ... Migrating from SAP Leonardo Machine Learning Foundation ... 730



    20.7 ... Summary ... 734



    21 ... Business Content and Use Cases ... 737



    21.1 ... Digital Transformation and SAP Data Intelligence ... 737



    21.2 ... Business Content by Industry ... 740



    21.3 ... Finance Use Cases ... 746



    21.4 ... Supply Chain Use Cases ... 747



    21.5 ... Manufacturing Use Cases ... 749



    21.6 ... Summary ... 751



    ... Appendices ... 753



    A ... Outlook and Roadmap ... 753



    B ... The Authors ... 763



    ... Index ... 765