Monday, November 13, 2017
08:30 AM - 12:00 PM
|Level: ||Technical - Intermediate|
Modern data analysis is moving past the Data Warehouse to the Data Lake to utilize emerging technologies for predicting behavior, not just reporting on what has passed. This presentation will cover the component architecture of the Data Lake for Data Scientists, for Big Data Analytics, and for Real Time Streaming Operation, and how it is different from and works with the other data applications in the organization.
Using my experiences with implementing Data Lakes, this session will cover various Data Lake Architectures and best practices in Data Lake Governance.
- Data Lakes, their uses, and architectural components
- How Data Lakes are different from Data Warehouses
- Architecture of a Data Scientist Sandbox
- Architecture of a Big Data Analytics Lake
- Architecture of a Real-Time Streaming Operation
- Components needed for Data Lake Governance
- Components Needed for Hadoop Data Governance
- Data Catalog and Data Services
April Reeve has spent the last 25 years working as an enterprise architect and program manager. Now she is incorporating her enterprise data management knowledge in new Big Data and Advanced Analytics implementations.
April is an expert in multiple Data disciplines including Data Integration, Big Data, Data Conversion, Data Warehousing, Business Intelligence, Master Data Management, and Data Governance.