Dark Analytics: Illuminating business opportunities

15

October

2017

5/5 (2)

As indicated in the Deloitte 2017 annual Technology Trends report dark analytics is recognized as one of the disruptive technologies that will disrupt businesses in the next 18-24 months.

Data and the insights derived from them are multiplying at an incredible rate. It is estimated that 90% of all existing data is generated during the last five years. The digital universe with the data we create and copy is doubling in size every 12 months. Its size is expected to be 44 zettabytes in 2020. This results in a digital universe that almost contains as many digital bits as stars in our universe (Krambles, Roma, Mittel & Sharma, 2017).

According to Tom Coughlin (2017) we can divide data into light, grey and dark data. Light data consists all the data that is well-known, structured and readily available. Grey data is data that is only accessible to those player with the means and contact to access. Lastly, dark data includes all the data that is not readily accessible and requires modern data analysis tools to be exposed.

Dark analytics is especially focusing on the last form of data, in which they mine unstructured and inaccessible data sets with the use of modern data analysis tools. By tapping into this data, companies have the opportunity to turn unknown patterns and connections into forceful insights for the development of their market intelligence (Mittel, 2017). Therefore, the purpose of dark analytics is not to catalogue fast quantities of unstructured data but to derive actual insights which can be used in one’s own advantage (Deloitte UK, 2017).

In general, dark analytics is focusing on three dimensions of data (Krambles et al., 2017):

  • The untapped data already in the possession of a company; this data can be divided into structured data and traditional unstructured data. Where the former consists of untapped data a company had not yet been able to find connections between, the latter focuses on text-based data in the form of e-mails, messages, word documents, pdf files, spreadsheets which do not take part of the relational database or tools and techniques to analyze them are not acquired yet.
  • Non-traditional unstructured data; includes all data that cannot be mined by the use of traditional analytics techniques. Take for example audio files, video files or still images which require for example machine learning, advances pattern recognition, natural language processing and video and sound analytics to mine the data in non-traditional formats.
  • Data from the deep web; all data that is part of the deep web, which is largest body of untapped information. It refers to all information from academics, government agencies, communities and other third parties of which its domain size and unstructured nature makes it difficult to analyze specific data.

An example is a project at the Copenhagen Airport in which the airport is collecting information by crunching the data in the log files or its Wi-Fi routers. Passenger’s smartphones ping routers in case they walk through terminals which offers data on the movement of passengers. This data could offer (commercial) insights on which shops are most visited on the airport (Chowdhury, 2017).

As also seen in the previous example, it is especially the growth of the Internet of Things with the expectation of 20.8 billion connected devices by 2020 which largely expands the volumes of data. And most of this expansion can be labeled as dark (Krambles et al., 2017). Therefore, the ability to access and analyze this data before your rivals results in a great opportunity and possible competitive advantage.

How do we capture this advantage and do not get lost in large volumes of dark data? According to Mittel (2017) it is essential to pay attention to dark analytics as a business strategy instead of a technology. This way, one stays grounded in business questions and will be able to define a scope and measure value. Focus especially on those areas which matter for your business and it will become unlikely to get lost in the dark unstructured bulk of data.

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Cyborgs and Biohacking: Extending the IoT from Things to Human Bodies

28

September

2017

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Recently, a Swedish company has been experimenting with implanting microchips into the hands of its employees. The chips give them access to the building and other functionalities that would normally only be accessible via a hardware device, like a key fob.

In the light of human enhancement, we are already living in a society of cyborgs. Think of the people who have smart technologies within their bodies; pace makers, insulin pumps etc. All of them are smart, connected technologies that regulate various functions in the body.  They enable us to make the blind see again, the paralyzed feel again, the deaf hear again and the crippled walk again.

The RFID microchip invented for the Swedish company was developed by a Swedish biohacker, Hannes Sjoblad, whose original purpose was to reduce the amount of “stuff” in our pockets. By inserting the chip in his own hand, he invented a way to leave your membership- and business cards, USB sticks and keys at home. Further development of his invention has led to a microchip that can power almost anything that is battery operated. In this way, the integrated microchip is making everyday tasks and interactions faster and easier.

Animal-testing with microchips has already been done. Take for example “the cyborgs rats in maze experiment”, in which is demonstrated how rats can escape a maze with the integration of machine intelligence. But, biohackers are taking it a step further to human experimentation. They are hacking existing gadgets to use them for our own convenience instead of medical purposes. In this way, they are discovering new uses for technologies in human bodies, enhancing the body artificially and hacking the methods and objects of biology to use it to our own advantage. Their practice can therefore be regarded as a ‘Do-it-Yourself Biology’.

The effect of this development is that the connectivity between things is moving to the connectivity between human bodies, expanding the territory of the Internet of Things rapidly. The question is, do we actually want to be connected to others or devices through our bodies?

As remarked by CBS News correspondent John Blackstone, the microchips used in the experiment are radio frequency identification tags that are able to track everywhere we go.  Each touch leaves a digital footprint which can put one’s privacy at risk. In addition to this, Ian Sherr, an executive editor at CNET, stresses that we are talking about a non-stop connection to our bodies, which cannot be turned off.

Despite of these possible risks, a US based company called 32M is preparing to implant microchips in 50 staff –members who volunteered to take part in the experiment. As Hannes Sjoblad himself stresses, it is most important to educate people and give them the tools to use the technology. Especially when it is used against them.

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