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Data Dictionary

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Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Dictionary.
Provides a practical guide to designing and using data dictionaries. It includes a discussion of the different types of data dictionaries, the benefits of using data dictionaries, and the challenges of data dictionary management.
Provides a comprehensive overview of data management, including data modeling, data integration, and data governance. It includes a discussion of the different types of data management tools and techniques, the challenges of data management, and the best practices for data management.
Provides a practical guide to information governance. It includes a discussion of the different aspects of information governance, the challenges of information governance, and the best practices for information governance.
Provides a practical guide to data management for analytics. It includes a discussion of the different aspects of data management for analytics, the challenges of data management for analytics, and the best practices for data management for analytics.
Provides a practical guide to using Spark. It includes a discussion of the different aspects of Spark, the challenges of using Spark, and the best practices for using Spark.
Provides a practical guide to artificial intelligence. It includes a discussion of the different aspects of artificial intelligence, the challenges of artificial intelligence, and the best practices for artificial intelligence.
Provides a practical guide to Keras. It includes a discussion of the different aspects of Keras, the challenges of using Keras, and the best practices for using Keras.
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