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This is a two day seminar on Big Data and how to achieve real business value. The first day is on Big Data and the second day is on unstructured data. All data in Big Data is unstructured so it is necessary to have a lengthy discussion on the issues related to unstructured data.Today there is a high failure rate associated with Big Data because corporations jump into Big Data without asking these two basic questions - how do I achieve business value from Big Data and once I have captured Big Data how do I do business intelligence and analytical processing from the data I have captured. The seminar is structured so that there is ample time to ask questions and interact with the instructor. The course is peppered with real life examples and case studies. This is a very practical seminar and is vendor neutral.
2 Days/Lecture & Lab
This seminar is designed for a general audience. Both management and technicians will find this seminar useful. The primary purpose of this seminar is to prepare the organization with being successful with their experience with Big Data.
- Big Data - What is it? A brief description of the technology known as Big Data
- Big Data - some critical questions - achieving business value and using Big Data to do analytical processing
- Achieving Business Value with Big Data I - an introduction to textual disambiguation
- Achieving Business Value with Big Data II - an implementation of textual disambiguation
- Big Data and Map Reduce - reinventing assembler programming
- Context - the difference between searching and analytical processing
- Disambiguated data in Big Data - some architectural considerations
- Textual disambiguation - what is it and why do I need it
- Placing Structured Data in Big Data - some surprising limitations
- Placing Disambiguated Data in Big Data - some architectural considerations
- Document and reports - some basic types of unstructured data
- Creating Analysis from Unstructured data - the importance of context
- Document Fracturing and Named Value Processing - putting context back into unstructured data
- Report Decompilation - structuring table data so that it can be analyzed
- Mapping - preparing the document for textual disambiguation
- Textual Disambiguation - techniques for putting context back into unstructured data
- Visualization - where the payoff is - throwing the victim a red lifeline