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Khattak, W., Buhler, P., & Erl, T. (2016). Big data fundamentals: Concepts, drivers, & techniques. Pearson.
Read Chapter 4: Enterprise Technologies and Big Data Business Intelligence.
This chapter describes the enterprise technologies that support the layered system used in the implementation of big data in the enterprise environment. Specifically, the data from within the operational-level information system of the organization is handled using multi-dimensional structures.
Read Chapter 5: Big Data Storage Concepts.
This chapter explains the concepts related to clusters, file systems, and distributed file systems, sharing, replication, the CAP theorem, atomicity, consistency, isolation, and duration (ACID), and principles of basically available, soft state, and eventual consistency (BASE).
Read Chapter 6: Big Data Processing Concepts.
This chapter describes the different technologies and techniques used in big data processing, including parallel and distributed data processing, Hadoop, processing workloads, and processing in batch and real-time modes.
Read Chapter 7: Big Data Storage Technology.
This chapter describes the various storage systems used for big data, including on-disk and in-memory storage devices, and the differences between NoSQL and SQL databases.
Ryzko, D. (2020). Modern big data architectures: A multi-agent systems perspective. Wiley.
Read Chapter 6: Big Data Architectures.
This chapter describes the latest architectures used for big data processing, including MapReduce, Directed Acyclic Graph Models, Kafka, and more.
National Institute of Standards and Technology. (2019). NIST big data interoperability framework: Volume 6, reference architecture, NIST.
Read Chapters 1-4 (Introduction, High-Level Reference Architecture Requirements, NBDRA Conceptual Model, and NBDRA Architecture Views).
These chapters describe how big data is defined by the NIST Big Data Public Working Group (NBD-PWG) through a collaborative effort with academia, industry, and government. Topics such as architecture, security, implementation challenges, use cases, and a roadmap for standards are discussed.
