Big data and advanced analytics
About the publication
ISBN
9788246433844
Size
751.1 KB
Language
Norwegian
The concept of big data remains elusive to define, but is in this work characterized as data of a varied
nature (variety), that arrives in large amounts (volume), and is updated at a high rate (velocity), and
due to this cannot be efficiently treated with traditional methods.
Using the same starting point, big data problems are calculations that cannot be efficiently solved
by traditional methods due to the complexity or speed of growth of the task, or the amount of data
needed to solve it. Big data solutions, correspondingly, are systems designed to solve big data
problems.
Today, more data than ever is produced. This means that the Norwegian Armed Forces will encounter
big data problems in the process of translating available data into good decisions. They will therefore
need to improve their ability to deal with these issues.
The FFI project Information integration for a modern defense has studied big data and advanced
analysis, mainly through literature studies on key concepts and technical experimentation to also
gain practical experience with technologies associated with these issues. The purpose of this report
is to summarize the findings of the project and communicate recommendations in four key areas:
Big data solutions, knowledge graphs, neurosymbolic artificial intelligence, and model reuse.
The development of technologiesfor dealing with big data problems have long had a big momentum,
thanks in large part to large technology actors sharing many high-quality components as open source.
This has led to the situation where the supply of technical components that can be used in big data
solutions is plentiful. We therefore believe that it is time for the Norwegian Armed Forces to make
use of big data technologies, and recommend that:
• The Armed Forces set up a big data solution for a selected big data problem in order to gain
experience of how to describe such problems, and how solutions should be specified and
realized. In this way, the Armed Forces will also gain valuable insight into the competence
required to carry out such a process.
• The Armed Forces start testing the use of knowledge graphs for a selected analysis task to
see if these tools provide value in the form of better and faster analysis results.
• The Armed Forces make sure that they have the ability to use techniques in neurosymbolic
artificial intelligence for automated processing and analysis of data at an early stage.
• The Armed Forces ensure access to updated expertise on the reuse of models for machine
learning so that such techniques quickly can be taken advantage of as soon as the need
arises.
These are measures that will reduce the risk related to acquiring big data solutions, and will in our
view ensure that the Norwegian Armed Forces take an important step towards being able to solve
their current and future big data problems.