Datafication
Datafication
Introduction :
Datafication is a technological trend turning many
aspects of our life into data which is subsequently transferred into
information realised as a new form of value. Kenneth Cukier and Viktor
Mayer-Schönberger introduced the term datafication to the
broader lexicon in 2013. Up until this time, datafication had been
associated with the analysis of representations of our lives captured through
data, but not on the present scale. This change was primarily due to the impact
of big data and the computational opportunities afforded
to predictive analytics.
Datafication is not the same as digitization, which takes analog
content—books, films, photographs—and converts it into digital information, a
sequence of ones and zeros that computers can read. Datafication is a far
broader activity: taking all aspects of life and turning them into data [...]
Once we datafy things, we can transform their purpose and turn the information
into new forms of value
There is
an ideological aspect of datafication, called dataism: "the
drive towards datafication is rooted in a belief in the capacity of data to
represent social life, sometimes better or more objectively than pre-digital
(human) interpretations.”
Theory
Datafication refers to the collective tools, technologies and processes
used to transform an organization to a data-driven enterprise. This buzzword
describes an organizational trend of defining the key to core business
operations through a global reliance on data and its related infrastructure.
Datafication is also known as datafy. An organization that implements
datafication is said to be datafied.
Organizations
require data and extract knowledge and information to perform critical business
processes. An organization also uses data for decision making, strategies and
other key objectives. Datafication entails that in a modern data-oriented
landscape, an organization's survival is contingent on total control over the
storage, extraction, manipulation and extraction of data and associated
information.
Datafication refers to the process by which
subjects, objects, and practices are transformed into digital data. Associated
with the rise of digital technologies, digitization, and big data, many
scholars argue datafication is intensifying as more dimensions of social life
play out in digital spaces. Datafication renders a diverse range of information
as machine-readable, quantifiable data for the purpose of aggregation and
analysis. Datafication is also used as a term to describe a logic that sees
things in the world as sources of data to be “mined” for correlations or sold,
and from which insights can be gained about human behavior and social issues.
This term is often employed by scholars seeking to critique such logics and
processes.
ELEMENTS OF DATAFICATION
The production of data cannot be
separated from two essential elements: the external infrastructure via which it is
collected, processed and stored, and the processes of
value generation, which include monetisation but also means of
state control, cultural production, civic empowerment, etc. This infrastructure
and those processes are multi-layered and global, including mechanisms for
dissemination, access, storage, analysis and surveillance that are owned or
controlled mostly by corporations and states.
Put another way, datafication combines
two processes: the transformation of human
life into data through processes of quantification, and the generation of
different kinds of value from data.
DATAFICATION:
FROM PAST TO PRESENT
Datafication is implicated in more than just social media
apps and content sharing platforms. The first domain of datafication was
business, not social life. Even today, the amount of data generated by commerce
exceeds the amount of data generated by the datafication of human life
(Chairman’s Letter in IBM, 2018). Key areas of business, such as logistics—the
management of the flow of goods and information—have matured into complex
practices thanks to datafication. The monitoring of continuously connected data
flows to organize all aspects of production and distribution across space and
time within global commodity chains could not be achieved without datafication
(Cowen, 2015).
Yet the effects of power that are intrinsic to datafication are often made invisible. . This understanding of datafication as somehow a natural process is surprisingly common, as evident in this sentence from an information booklet distributed by the UK’s Royal Society: “Machine learning is a brand of artificial intelligence that allows computer systems to learn directly from examples, data and experience” (2019, n.p.).
CONTROVERSIES
OVER DATAFICATION
Important controversies over social justice have emerged
about how datafication is applied by corporations or states in particular
sectors (from credit ratings to social services) to discriminate against
individuals particularly from disadvantaged classes and ethnic populations
(e.g., Gandy, 1993; Eubanks, 2017; Benjamin, 2019). More broadly, disciplines
like political economy, legal studies, and decolonial theory approach the
social quantification sector’s work from different angles, each drawing on
critical data studies.
Layers of datafication
Advantages:
Ability to make better decisions
improve efficiency
Create new products and services.
Datafication Helps in Data
Management
Datafication makes Data
Processing Faster
Disadvantages:
Privacy concerns
Datafication could
take a Long Time
Datafication Has a Poor
Memory
Datafication is Expensive
Conclusion
In conclusion, datafication
is a term used to describe the process of turning data into a commodity.
This is done by collecting, analysing, and packaging data in a way that makes
it easy to sell or trade.
Overview
The concept of datafication was initially employed by scholars seeking
to examine how the digital world is changing with the rise of big data and data
economies. However, as datafication itself becomes more widespread,
scholarship...
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