This tutorial presents Big Data Engineering (BDE), which is defined as the practical application of a systematic, disciplined, quantifiable approach to the analysis, design, construction, operation, and maintenance of Big Data solutions.
BDE is a holistic method focusing on 8 crucial areas: Methodology, Program, Governance, Resources, Quality, Risk Mitigation, KPI & Financials, and Practice. BDE also systematically addresses the lifecycle of Big Data solutioning in 12 stages: Plan, Requirement, Analysis, Modeling, Platform, Design, Development, Integration, Testing, Runtime, Deployment, and Operation.
Each of these 12 stages comprises individual elements as subdisciplines. For example, the NoSQL platform options include key-value, column-based, document-oriented, graph, NewSQL, and In-memory stores. Case studies and working examples will be discussed in great details in the session to illustrate the pragmatic use of BDE in the real-world implementations. Best practices and lessons learned are articulated as well.
Topics you will learn about include:
- Engineering discipline
- Best practices