Big Data Architecture Workshop

3 Days

18 CPD hours

Senior Executives
CIOs and CTOs
Business Intelligence Executives
Marketing Executives
Data & Business Analytics Specialists
Innovation Specialists & Entrepreneurs
Academics, and other people interested in Big Data

More specifically, BDAW addresses advanced big data architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, security and privacy, minimizing the risk of an unsound architecture and technology selection.

Big Data Architecture Workshop (BDAW) is a learning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, students apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for students to learn techniques for architecting big data systems, not only from Cloudera?s experience but also from the experiences of fellow students.

Workshop Application Use Cases

• Oz Metropolitan
• Architectural questions
• Team activity: Analyze Metroz Application Use Cases

Application Vertical Slice

• Definition
• Minimizing risk of an unsound architecture
• Selecting a vertical slice
• Team activity: Identify an initial vertical slice for Metroz

Application Processing

• Real time, near real time processing
• Batch processing
• Data access patterns
• Delivery and processing guarantees
• Machine Learning pipelines
• Team activity: identify delivery and processing patterns in Metroz, characterize response time requirements, identify Machine Learning pipelines

Application Data

• Three V?s of Big Data
• Data Lifecycle
• Data Formats
• Transforming Data
• Team activity: Metroz Data Requirements

Scalable Applications

• Scale up, scale out, scale to X
  Determining if an application will scale
  Poll: scalable airport terminal designs
  Hadoop and Spark Scalability
  Team activity: Scaling Metroz

Fault Tolerant Distributed Systems

• Principles
  Transparency
  Hardware vs. Software redundancy
  Tolerating disasters
  Stateless functional fault tolerance
  Stateful fault tolerance
  Replication and group consistency
  Fault tolerance in Spark and Map Reduce
  Application tolerance for failures
  Team activity: Identify Metroz component failures and requirements

Security and Privacy

• Principles
• Privacy
• Threats
• Technologies
• Team activity: identify threats and security mechanisms in Metroz

Deployment

• Cluster sizing and evolution
• On-premise vs. Cloud
• Edge computing
• Team activity: select deployment for Metroz

Technology Selection

• HDFS
• HBase
• Kudu
• Relational Database Management Systems
• Map Reduce
• Spark, including streaming, SparkSQL and SparkML
• Hive
• Impala
• Cloudera Search
• Data Sets and Formats
• Team activity: technologies relevant to Metroz

Software Architecture

• Architecture artifacts
• One platform or multiple, lambda architecture
• Team activity: produce high level architecture, selected technologies, revisit vertical slice
• Vertical Slice demonstration

Additional course details:

Nexus Humans Big Data Architecture Workshop training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.