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Some things don't change, even during a
pandemic. Consistent with previous years, in
CIO’s 2021 State of the CIO survey, a plurality of
the 1,062 IT leaders surveyed chose
“data/business analytics” as the No.1 tech
initiative expected to drive IT investment.

Unfortunately, analytics initiatives seldom do
nearly as well when it comes to stakeholder
satisfaction.

Last year, CIO contributor Mary K. Pratt offered
an excellent analysis of why data analytics
initiatives still fail, including poor-quality or siloed
data, vague rather than targeted business
objectives, and clunky one-size-fits-all feature
sets. But a number of fresh approaches and
technologies are making these pratfalls less
likely.

(...)

New technology invariably incurs new risks. No
advancement has had more momentous impact
on analytics than machine learning – from
automating data prep to detecting meaningful
patterns in data – but it also adds an unforeseen
hazard. As CSO Senior Writer Lucian Constantin
explains in "How data poisoning attacks corrupt
machine learning models," deliberately skewed
data injected by malicious hackers can tilt models toward some nefarious goal. The result could be,
say, manipulated product recommendations, or
even the ability for hackers to infer confidential
underlying data.

(...)

In the end, the secret to successful analytics is
not in choosing and implementing the perfect
technology, but in cultivating a broad
understanding that pervasive analytics yields
better decisions and superior outcomes. Usually,
you can iron out technology kinks or
requirements misunderstandings. But if you can't
change the mindset, few will use the beautiful
analytics machine you just built.

Disponível em: https://www.cio.com/article/3614692/5-perspectiveson-modern-data-analytics.html.

Acesso em: 15 out. 2021.