A Data Lake is a highly scalable platform for storing huge volumes of multistructured data from disparate sources with centralized data management services. This book explores the potential of Data Lakes and explores architectural approaches to building data lakes that ingest, index, manage, and analyze massive amounts of data using batch and real-time processing frameworks. It guides you on how to go about building a Data Lake that is managed by Hadoop and accessed as required by other Big Data applications.
This book will guide readers (using best practices) in developing Data Lake's capabilities. It will focus on architect data governance, security, data quality, data lineage tracking, metadata management, and semantic data tagging. By the end of this book, you will have a good understanding of building a Data Lake for Big Data.

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Spis treści

Data Lake Development with Big Data. Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies eBook -- spis treści

• 1. The Need for a Data Lake
• 2. Data Acquisition
• 3. Data Integration, Quality, and Enrichment
• 4. Data Consumption
• 5. Data Governance