This section lists some real-life use cases that are usually solved by implementing a data-intensive system. The use cases are divided into machine learning, data enrichment, and ETL use cases. These are just some of the many use cases, and the intention is to provide readers with an idea of the variety of use cases rather than an exhaustive list of use cases.
- Title Page
- Copyright and Credits
- Packt Upsell
- Contributors
- Preface
- Exploring the Data Ecosystem
- Defining a Reference Architecture for Data-Intensive Systems
- What is a reference architecture?
- Reference architecture for a data-intensive system
- Oracle's information management conceptual reference architecture
- Oracle's information management reference architecture
- Desired properties of a data-intensive system
- Defining architectural principles
- Listing architectural assumptions
- Architectural capabilities
- Summary
- Patterns of the Data Intensive Architecture
- Discussing Data-Centric Architectures
- Understanding Data Collection and Normalization Requirements and Techniques
- Creating a Data Pipeline for Consistent Data Collection, Processing, and Dissemination
- Building a Robust and Fault-Tolerant Data Collection System
- Challenges of Data Processing
- Let Us Process Data in Batches
- Handling Streams of Data
- What is a streaming system?
- Capabilities (and non-capabilities) of a streaming application
- High-level reference architecture
- Samza architecture
- Kafka streams
- Samza's stream processing API
- The scheduler/executor component of the streaming architecture
- Processing concepts and tradeoffs
- Micro-batch stream processing
- Windowing
- Summary
- References
- Let Us Store the Data
- The data explosion problem
- Relational Database Management Systems and Big data
- Introducing Hadoop, the Big Elephant
- HDFS file formats
- HBase
- Graph stores
- Semantic graph
- Stardog
- BITES – Unstructured/Semistructured document store
- Data integrity and validating constraints
- Monitoring and operation
- Performance
- Summary
- Further reading
- When Data Dissemination is as Important as Data Itself
- Data dissemination
- Discussing the non-functional aspects of the preceding architecture
- Summary
- Other Books You May Enjoy
Real-life use case examples
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