Types of Data Has data really changed? Well technically no, data generated by computers and digital devices is still groups of 1s and 0s. That has not changed. What has changed is the quantity, volume, variety, and immediacy of the generated data. Historically companies would have access to our information gathered from forms, spreadsheets, applications, credit card purchases and other types of files. Much of the information was stored and analyzed at a later date. Sensitive data was still collected, stored and analyzed but, historically, hackers were more interested in hacking into systems to obtain corporate or government secrets. Today, gathered data is taking on new characteristics. The digitized world has opened the floodgates for data gathering. IoT sensor-enabled devices are collecting more and more data of a personal nature. Wearable fitness trackers, home monitoring systems, security cameras, and debit card transactions are all collecting personal data as well as business and environmental data. Data is often combined from different sources and users may be unaware of this. Combining fitness monitoring data with house monitoring data could produce data points to help map the movements or location of a homeowner. This changing type of data collection and aggregation can be used for good purposes to help the environment. It also increases the possibility of invasion of our privacy, identity theft, and corporate espionage. Personally identifiable information (PII) or sensitive personal information (SPI) is any data relating to a living individual that can be used on its own or with other information to identify, contact, or locate a specific individual. The data gathered by companies and government institutions can also contain sensitive information concerning corporate secrets, new product patents, or national security. Because we are gathering and storing exponential quantities of both sensitive and informational data, it has increased the need for extra security to protect this information from natural disasters, hackers, and misuse. Expand each heading below to see examples of PII and Informational data. expand_less PII Social security number Email address Bank account numbers Student tuition bill Credit rating Debit card number Fingerprints Birth date Username/password Vehicle identification number (VIN) Mortgage information Home address Facebook photographs expand_less Informational
Evolution of Data Characteristics (00:00 - 01:15)
Evolution of data from basic binary sets to massive, immediate streams.
Discussion on how quantity, volume, and variety have changed the data landscape.
Historical vs. Modern Data Collection (01:15 - 02:30)
Comparison of historical static data (forms and spreadsheets) with today's real-time IoT sensor data.
Insights into how the motivation for hacking has shifted from corporate espionage to personal data theft.
Data Aggregation and Privacy Risks (02:30 - 03:15)
Exploration of the Internet of Things (IoT) and the risks associated with combining data from multiple sources.
Analysis of how aggregated data can map an individual's movements and routines.
Categorizing PII and Informational Data (03:15 - 04:00)
Definition of Personally Identifiable Information (PII) and Sensitive Personal Information (SPI).
Specific examples provided including Social Security numbers, biometric data, and financial records.
The increasing necessity for enhanced security measures to protect against misuse and disasters.