Course Description
Big Data is the term used to describe our ability to make sense of the ever-increasing volumes of data in the world. Whether you call it big data, analytics, business intelligence or data analysis doesn’t really matter that much. What does matter is that we can now collect and analyze data in ways that wasn’t possible even a few years ago. Big Data is starting to transform most areas of business, industry, research and most other parts of our lives.
The promise and advantages of Big Data require new ways of looking at control, governance, security and processing. Big Data will only continue to increase in importance and criticality as we move more toward the Internet of Things (IoT)
This seminar will provide you with an understanding of Big Data, the security risks, differences between traditional corporate data and Big Data, and how to control and manage it.
Learning Objectives
- Understand the characteristics and value proposition of Big Data
- Understand the security advantages and disadvantages
- Identify the top security risks
- Describe the use and advantage of the Hadoop processing platform
- Identify control issues with Big Data
- Describe the top technical challenges with the use of Big Data
Course Outline
What is Big Data?
- General Concepts
- Characteristics of Big Data
- Volume
- Velocity
- Variety
- Veracity
- Variability
- Structured and Unstructured Data, Big Data Taxonomies
- Databases and the Relational Model
- Data Warehouses and Data Marts
- Tradeoffs between Big Data and “Traditional Data”
Data Analytics, Data Mining and Business Intelligence
- What are Data Analytics, Data Mining, and BI?
- Big Data uses
Big Data Value Proposition
- Horizontal and Vertical Apps
- Who’s collecting Big Data?
- Big Data and the Cloud – Internet of Things (IOT)
- Big Data and mobility
- Big Data in Use: Enterprises, healthcare, not-for-profit, government, election campaigns, legal discovery, video
Big Data and Hadoop Infrastructure
- Hadoop and the “Community”
- NoSQL Databases
The Four Critical Aspects of Big Data Management
- Data Quality
- Data Life Cycle and Stewardship
- Process and Data Auditing
- Access Security
Top 5 Technical Challenges
Top 10 Security challenges
Big Data Control Issues
- Data governance and policy
- Data risk management
- Life cycle management
- Stewardship
- Data privacy
- Audit and compliance: State, Federal, International Data Security and Breach Notification Act of 2015
Big Data Security Issues
- Access and change controls
- Real-time monitoring
- Data loss/leak prevention
- Data protection: masking, anonymization, encryption
- Backup and recoverability
Big Data Security Model
- Big Data Maturity model
- Find & Classify; Assess & Harden; Monitor & Audit; Enforce & Protect
Additional Information
Who Should Attend
- Information security professionals
- Internal control professionals
- IT and operational auditors
- Risk managers
Learning Level
Intermediate
Delivery
Group Live or Group Internet-Based
Field
Auditing
Advanced Preparation
None
Recommended Prerequisites
A good understanding of information security and IT audit controls, and associated terminology
Session Duration
On Site: 1 day
CPE Credits: 8