Page 308 - Special Topic Session (STS) - Volume 4

STS637 Magued O.
from the traditional players of the statistical system to new players coming
from the private sector and most of them are multinational companies.
Medium term predictions presented in Table 1 show that the average annual
growth rate in revenues resulting from digital transformation is higher than
the growth expected in many other sectors of the economy. In many cases,
the annual growth rate of revenues is double-digit. Such growth will result in
an increasing amount of data generated as a by-product of the activities
associated with digital transformation and will subsequently raise the demand
for data scientists.
These complex and interacting technological changes will have its impact
on the discipline of statistics whether on the academic side or on the practice
side as the “world of data” will explode in volume and will diverse in nature.
The volume of data sets, such as censuses and household surveys, that was
once a pride of statistical offices, are only a small fraction of data that are/can
be generated every day by Google, Facebook, Netflix, YouTube, Uber, twitter
or Amazon. The volume of data generated outside the traditional statistical
system is increasing exponentially. For example, the hours watched on Netflix
per minute increases from 70K hours in 2017 to 266K hours in 2018 and to
694K in 2019. Such wealth of data is used to understand the mood of the
subscribers in addition to their preferences.
The traditional model of bureau of statistics as the main producer of data
will come to an end and will be challenged by other non-state actors. Shift
from national to global and from public to private will dominate data
ownership and will reduce the national ability to use information to support
and take decisions and to formulate public policies.
The market share of governmental organizations in producing, storing,
analyzing and disseminating data is going to sharply decrease. As a result, the
impact of statistical governmental organizations on decision making process
will shrink and their control on drafting and indorsing professional standards
and ethics governing big data is at stake. Furthermore, fuzzy big data
governance might jeopardize the strict use of international concepts,
classifications and methods to promote international consistency and
subsequently, indicators (especially economic and financial) might lack
international comparability.
The World Economic Forum expects a shift in the jobs landscape. Between
2018 and 2022, it is expected that 133 million new jobs will be created and 75
million will disappear. The list of the top emerging jobs includes “data analysts
and scientists” ranking number one in the list of emerging jobs and “big data
specialists” ranking number six in the list. This is an extra evidence that the
integration of statistics in data science is imperative to improve employability
of the new generation of statisticians.
These sets of paradigm shifts will change the way statistical analysis is
carried out not only in terms of computational tools and storage capacity but

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