Knowledge Base

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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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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. [1]

In: Trends

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.[1]
Data analytics encompasses techniques such as regression analysis, pattern matching, forecasting, multivariate statistics, predictive modelling and forecasting. [2]

In: Trends

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.”[1]

In: Trends

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