Big Data Security, Governance, Stewardship

Big Data is the rapidly expanding mass of information generated by connected devices, sensors, systems, and people, characterized by high volume, velocity, and variety. Beyond these classic “3Vs,” the report stresses two decisive properties: veracity (how trustworthy the data is) and value (its potential to be transformed into useful outcomes). Big Data itself has little meaning; value is created when analysis converts it into Smart Information that improves decisions, forecasting, products, operational efficiency, customer service, and competitive positioning. Increasingly, this value depends on combining internal data with external sources such as social media, public-sector datasets, and cross-organizational sharing.

The same forces enabling new analytics—cloud computing power, Machine Learning Systems, cognitive technologies, and AI—also amplify risks. Big Data can enable identification of individuals in less transparent ways, while training data can introduce bias and many analytic systems cannot explain their reasoning, complicating accountability. Big Data also “turns the classical information lifecycle on its head”: data is often collected before its uses are known, frequently without a clear owner, classification, or retention plan. Externally sourced data adds uncertainty about provenance, rights to use, consent, and integrity.

Security and governance challenges are intensified by infrastructure realities: technologies designed for massive scalability may lack mature security controls, and many IoT devices exhibit weak security, limited encryption, physical exposure, and long lifetimes without upgrade paths. To address these issues, the report advocates Big Data information stewardship: governance that sets ethical objectives and risk appetite, lifecycle management with clear ownership and retention/disposal, an organization-wide stewardship culture, and information-centric security ensuring availability, integrity, and confidentiality with auditable controls.

• Big Data is commonly characterized by volume, velocity, and variety, with veracity and value also identified as important properties.
• UK subscriptions to Netflix, Amazon, and NOW TV exceed subscriptions to traditional pay TV services.
• Smartphones generate data beyond calling, including GPS location tracking and sensor readings that monitor device performance.
• Unstructured organizational content such as emails, documents, spreadsheets, and presentations is often created ad hoc and is difficult to inventory and control.
• Social platforms such as Facebook and Twitter produce data that can be analyzed for consumer preferences and complaints.
• The Hadoop MapReduce framework processes data in parallel across many standard computers.
• NoSQL databases support storage and retrieval of non-relational data types such as video, voice, and relationship graphs.
• IoT devices can transmit data without the explicit consent of the owner or in ways the owner does not expect.
• Some IoT devices have no ability to change the root administrator password.
• Research demonstrated de-anonymization of a dataset containing anonymous movie ratings of 500,000 Netflix subscribers.

• “Big Data, in itself, has no meaning and little value.”
• “Big Data extends beyond the enterprise and much of the potential value comes from being able to search for and utilize data from external sources.”
• “The important characteristics of big data are their value and veracity; these matter from the perspectives of security, governance and stewardship.”
• “The volume of data available together with the computing power provided by cloud services has led to the new forms of data analytics.”
• “Information stewardship is highly relevant to ensuring that information is not only properly secured but also that it is used ethically.”
• “Information needs to be treated as the operating capital a modern organization – that is to say like money.”
• “Big Data magnifies the challenges that apply to the use, governance and security of normal data.”
• “Big Data is often acquired before it is analysed and what will be discovered is not fully known at the outset.”
• “The gap between what is possible and what is allowed by laws and regulations defines an area where ethical questions must be raised.”
• “The results of the analysis of Big Data may have consequences that impact on people and society.”