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Course Outline
Day 1 - Fundamental Big Data
- Understanding Big Data
- Fundamental Terminology & Concepts
- Big Data Business & Technology Drivers
- Traditional Enterprise Technologies Related to Big Data
- Characteristics of Data in Big Data Environments
- Dataset Types in Big Data Environments
- Fundamental Analysis and Analytics
- Machine Learning Types
- Business Intelligence & Big Data
- Data Visualization & Big Data
- Big Data Adoption & Planning Considerations
Day 2 - Big Data Analysis & Technology Concepts
- Big Data Analysis Lifecycle (from business case evaluation to data analysis and visualization)
- A/B Testing, Correlation
- Regression, Heat Maps
- Time Series Analysis
- Network Analysis
- Spatial Data Analysis
- Classification, Clustering
- Outlier Detection
- Filtering (including collaborative filtering & content-based filtering)
- Natural Language Processing
- Sentiment Analysis, Text Analytics
- File Systems & Distributed File Systems, NoSQL
- Distributed & Parallel Data Processing,
- Processing Workloads, Clusters
- Cloud Computing & Big Data
- Foundational Big Data Technology Mechanisms
Day 3 - Fundamental Big Data Architecture
- New Big Data Mechanisms, including ...
- Security Engine
- Cluster Manager
- Data Governance Manager
- Visualization Engine
- Productivity Portal
- Data Processing Architectural Models, including ...
- Shared-Everything and Shared-Nothing Architectures
- Enterprise Data Warehouse and Big Data Integration Approaches, including ...
- Series
- Parallel
- Big Data Appliance
- Data Virtualization
- Architectural Big Data Environments, including ...
- ETL
- Analytics Engine
- Application Enrichment
- Cloud Computing & Big Data Architectural Considerations, including ...
- how Cloud Delivery and Deployment Models can be used to host and process Big Data Solutions
Day 4 - Advanced Big Data Architecture
- Big Data Solution Architectural Layers including ...
- Data Sources,
- Data Ingress and Storage,
- Event Stream Processing and Complex Event Processing,
- Egress,
- Visualization and Utilization,
- Big Data Architecture and Security,
- Maintenance and Governance
- Big Data Solution Design Patterns, including ...
- Patterns pertaining to Data Ingress,
- Data Wrangling,
- Data Storage,
- Data Processing,
- Data Analysis,
- Data Egress,
- Data Visualization
- Big Data Architectural Compound Patterns
Day 5 - Big Data Architecture Lab
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Incorporates a set of detailed exercises that require delegates to solve various inter-related problems, with the goal of fostering a comprehensive understanding of how different data architecture technologies, mechanisms and techniques can be applied to solve problems in Big Data environments.
35 Hours
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