In 2001, the industry analyst Douglas Laney at Gartner described data management challenges along the three dimensions volumes, velocity and variety in the E-commerce branch. Volumes stands for the quite huge increase of volumes of data, Velocity for increased point-of-interaction speed and the pace of data generated by interactions and used to support interactions. Data Variety means variety of incompatible data formats, non-aligned data structures and inconsistent data semantics. This 3-V-model has been widely used attempting to define big data since this publication in 2001. 
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The Big Policy Canvas Knowledge Base is a state-of-the-art, online and dynamic repository that functions as an accumulator uniting all the knowledge produced during the project. It is structured along the three dimensions of needs, trends and assets and furthermore offers a mapping among them by defining how they are interconnected and how they influence each other.
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Predictive analytics brings together advanced analytics capabilities. It extracts information from existing data sets in order to determine patterns and predict future impacts and trends. It forecasts what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessments.
Data analytics encompasses techniques such as regression analysis, pattern matching, forecasting, multivariate statistics, predictive modelling and forecasting. 
Privacy by design is an approach that promotes privacy and data protection compliance throughout the whole system engineering process. The Information & Privacy Commissioner of Ontario has taken a leading role in developing the privacy by design concept, establishing a reference framework of “Seven foundational principles of privacy by design” with respect to a proactive, transparent and user-centric engineering process. 
The 7 principles are:
• Proactive not Reactive; Preventative not Remedial
• Privacy as the Default setting
Security by design is an approach in software engineering that promotes to design software from the ground up to be secure.
Core pillars of information security are confidentiality (only allow access to data for which the user is permitted), integrity (ensure data is not tampered or altered by unauthorized users) and availability (ensure systems and data are available to authorized users when they need it). 
Governance is a term that has a quite broad context and means in its core to shape or design areas of life. E-Governance (Electronic Governance) is devoted to the challenges of shaping life areas in face of digital revolution and information era and affects all sectors encompassing the public, private and civil sector. It also affects communication and exchange between the sectors.
Data philanthropy is a kind of strategic partnership between private and public sector in which private companies donate data as a valuable resource for public benefit, i.e. for humanitarian, corporate, human rights, and academic use. 
However, there are numerous challenges to be mastered, such as competing tensions on data control and ownership, personal data protection and the lack of adequate frameworks for coordination and governance. 
Core idea of the lean approach is to maximise customer value and to focus on its key processes in order to continuously increase it through an optimum value creation process that has zero waste.
Lean thinking changes the focus of management from optimising separate technologies, assets, and vertical departments to optimise the flow of products and services through entire value streams that flow horizontally across technologies, assets, and departments. 
Technological Unemployment is about the societal impacts of technologies. Danaher defines technological unemployment “as the replacement of human workers […] by technological alternatives (machines, computer programs, robots and so forth)”. Furthermore, he assumes that artificial intelligence and robots will take over the work of humans in future. This is one reason why technological developments often come with people´s fear of the consequences. Everything is automated to such an extent that human work is no longer needed. 
The term “smart” in this trend indicates, that it is not only about collecting and storing data, but about automation of data analyses. Kim et al. describe this as follows: “Smart surveillance system is mainly composed of automatic video/audio analysis. Therefore, an emerging surveillance system must consider multimedia information for monitoring activities and extracting meaningful information from the environment.”