Read the text and write a short brief using the following phrases:
The article is devoted ….. Статья посвящена….
The article deals (is concerned) with …. Статья касается….
The article touches upon the issues of….. Статья затрагивает проблемы……
The article is about….. Статья о…..
The purpose (aim) of the article is….. Цель статьи….
Much attention is given to….. Большое внимание уделено…..
It is reported that…. Сообщается, что….
It is spoken in detail about…. Рассказано в деталях….
The article gives a detailed analysis of…… Статья дает детальный анализ….
The following conclusions are drawn…. Следующие выводы сделаны….
Innovative technology for data visualisation
Businesses are well aware of the importance of Big Data analytics, but communicating information in an accessible and meaningful way can be challenging. That’s where data visualisation comes in. This can include anything from a simple timeline to an interactive infographic. But there’s an option that is decidedly more immersive - use VR to deliver data visualisation in a virtual environment.
VR for data visualisation
Merging Virtual Reality and Big Data isn’t a new idea. Virtual data visualisation has existed for years. However, it is hard to find an application that can combine Artificial Intelligence, Big Data and Virtual/Augmented Reality.
A Californian startup “Virtualitics” has recently created such a platform. It uses smart mapping, smart routines, machine learning and natural language processing to identify important patterns and display them in the virtual environment, which can then be customised by users. The platform can be applied to any industry that relies on data analytics, and lets users examine up to 10 dimensions of data.
Apart from “Virtualitics”, other companies are using Virtual Reality for data visualization, too. For example, LookVR is an app which allows businesses to explore and interact with data. Up until now there has been limited success, but a combination of sufficient funding and technological advancements will change that.
One of the main issues with visualising data is making it comprehensible. The human brain can only process so much data before it becomes meaningless. However, through analysing the reactions of users within the experience, graphics can be altered in real time to maximise understanding.
How will VR disrupt data visualisation?
As essentially all industries deal with data in some form, the scope for disruption is massive. Machine learning alone is faster and more efficient than traditional techniques, but pair this with VR and you have real accessibility. Applying VR technologies to data will be helpful for businesses on an internal level, by extracting key info and making it easy to understand. This could be benefit companies across the scale, from retailers to utility firms. It could also disrupt B2B negotiations, as using advanced, immersive data visualisation could determine whether a business agreement is successful or not.
Pairing VR with data visualisation is also an enabler for new business models, which combine the expertise of co-workers in different geographic locations. However, in light of upcoming legislation on data sharing and analysis, businesses will need to be careful with the machine learning platforms they use. Understanding and sharing comprehensive data is great, but analysing the wrong data (including private or sensitive) could be damaging to a company.
Data analysis is about making the most out of information. Innovative technology can play an important role in doing this – especially tech which is primarily designed for visualisation. By putting vast quantities of info into visually comprehensive environments, VR can unlock the potential of data in ways that traditional methods can’t. Even so, data collection and analysis is still a touchy subject, and it’s easy to see why. People are precious about their information, and for good reason. It’s not just the software providers that need to be aware of how the platform gathers and uses data. Users should think carefully before entrusting information to an external service, no matter what or who it is.
The article is devoted to the innovative technology for data visualisation.
The article deals with the use of VR to deliver data visualisation in a virtual environment.
The article touches upon the issues of current setbacks to find an application that can combine Artificial Intelligence, Big Data and Virtual/Augmented Reality.
The article is about the platform which uses smart mapping, smart routines, machine learning and natural language processing to identify important patterns and display them in the virtual environment, which can then be customised by users. The platform can be applied to any industry that relies on data analytics, and lets users examine up to 10 dimensions of data.
The purpose of the article is to introduce the audience to the Merging Virtual Reality and Big Data systems.
Much attention is given to the adaptive and disruptive features of existing VR applications.
It is reported that the human brain can only process so much data before it becomes meaningless. However, through analysing the reactions of users within the experience, graphics can be altered in real time to maximise understanding.
It is spoken in detail about the fact the machine learning alone is faster and more efficient than traditional techniques. Pairing VR with data visualisation is also an enabler for new business models, which combine the expertise of co-workers in different geographic locations. However, in light of upcoming legislation on data sharing and analysis, businesses will need to be careful with the machine learning platforms they use.
The article gives a detailed analysis of practical applications of such powerful data processing systems for businesses and the likely negative outcomes.
The following conclusions are drawn: understanding and sharing comprehensive data is great, but analysing the wrong data (including private or sensitive) could be damaging to a business or even the whole industry.
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