Big Data in Application of Big Data for National Security
Review what big data is and the applications of big data. Read Chapter 1 Introduction to Big Data in Application of Big Data for National Security: A Practitioners Guide to Emerging Technologies.
First, answer the following:
what is it
How is it different
structured and unstructured data
The five V’s of Big Data
Importance, application, advantages
Analytical capabilities of big data – greater risk intelligence and predictive modeling
Streaming analytics
Read Big Data Analytics: A Practical Guide For Managers.
Mother of Invention’s Triplets: Moore’s Law, the Proliferation of Data, and Data Storage Technology
Hadoop
HBase
Machine Learning
Statistics
Google
GIS
Discovery
Data Quality
Benefits
Concerns
Second, investigate analytics of big data.
Read Chapter 2 Drilling into the Big Data Gold Mine – Data Fusion and High-Performance Analytics for Intelligence Professionals
Read Chapter 6 Critical Infrastructure Protection by Harnessing Big Data
Read Cognitive Computing and Big Data Analytics
Chapter 4 The Relationship between Big Data and Cognitive Computing
Chapter 6 Applying Advanced Analytics to Cognitive Computing
Third, investigate Implementation and challenges of big data analytics
Watch IT Security: Big Data Challenges in the Cloud
Read Section 3 – Methods and Technology Solutions in application of Big Data for National Security: A Practitioner’s Guide
Requirements and challenges for big data architectures
Tools and technologies for implementation
Mining Social Media
Making Sense of Unstructured Natural Language Information
Literature Mining and Ontology Mapping Applied to Big Data
Big Data Concerns in Autonomous AI Systems
Read Section 4 Legal and Social Challenges
Legal Challenges of Big Data Application
Big Data and the Italian Legal Framework
Accounting for Cultural Influences in Big Data Analytics
Making Sense of Noise
Task 4: Since the company is dealing with very large amounts of data continuously, it I important for the IT team to develop a “Big Data” mindset so that they can use their analysis for predictive modeling. Set up a series of digital scenarios that you would have the IT team work through where they have to make predictive models from a large batch of data. You can find and use an existing data set for this project but need to clearly define what the team is analyzing and how they are to go about making their predictive models. Remember, this is a training exercise. Here is a link for a video on predictive modeling for your to see:
