[Infographic] Everything You Need to Know About the Significance of Customer data lifecycle

“Data really powers everything that we do.” – Jeff Weiner

Hence the life of data is crucial. And the series of phases it goes through during its lifetime highlights the true meaning of data to a brand or entity. 

This is when Data Lifecycle Management comes into the picture! 

Data Lifecycle Management structures the steps followed by the data of a company or brand to optimize it to it’s best during its lifetime. 

But, before that, it is essential to understand the entire journey of data and its phases of the lifecycle.

Customer Data Lifecycle
Data Capture
Data Usage
Data lifecycle is the series of stages
through which a particular data goes
through from its capture or initial
generation to its archival or
deletion at the end of its life.
During its lifetime
a data goes
through seven
The f rst and foremost
experience of data is to
pass within the f rewalls
of a brand. Data cap
ture is an act of creat
ing data values.
Common examples are
data acquisition or data
As the data has been
captured, it encoun
ters data mainte-
nance. Data mainte-
nance supplies data
to the points where
data synthesis and
data usage occurs.
Next is data usage where it
reaches a point, and data is
used as support of a brand. It
is the application of data as
information to tasks while the
business needs to run and
manage itself.
It is the f nal stage of
data, where it’s life
actually ends. P urg
ing is the process of
the removal of
unwanted datasets
from an enterprise.
Data Purging
After many rounds of
usage and publica-
tion, data comes near
to its end, where a
brand might want to
archive the data. The
archival of data leads
to the storage of data
in case it is needed in
the future.
Data Archival
W hile making the most of the
data, it might also go outside of
the company. This is known as
data publication, where the
data is sent out to a location
outside the brand.
Data Publication
It is the compound of analytics
that uses modeling such as risk
modeling, actuarial modeling,
and investment modeling. This
is where the creation of data
values takes place by utilizing
other data as input.
Data Synthesis

When data goes through all the phases of the data lifecycle every day, brands gain various significant insights that would let them make many strategic decisions. Data lifecycle management leads the brands towards the digitization of their business, which allows them to control costs, leverage their data for competitive advantage, and accelerate time to value. 

Thus, a capable data lifecycle management could help you in multiple business operations daily. So, having a robust data lifecycle management software would guarantee the performance of your data and let you gain meaningful insights from it. 

About Aditi L

I'm a technical writer and excel in writing on the latest technologies of the digital advertising industry. I possess significant knowledge and proven experience in adtech & martech trends and even indulge in-depth research on modern digital technologies to deliver engaging content. Writing inspiring blogs and light-minded poems have always been my passion. I also dream of writing a book one day. Apart from writing, enjoying art & music has been my forte.

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