As
an organisational and technological approach, DevOps has driven a lot of gains
for enterprise organisations since the concept was first introduced about a
decade ago. Bringing an agile, more automated approach to application
development and cohesively structuring development and IT operations teams
closer together has undoubtedly changed the game for many organisations in
terms of their application development lifecycles.
DevOps
has spawned a range of well-known advantages including continuous software delivery,
faster updates, improved communications environments, and more productive and
innovative teams. While DevOps is now a bit of a business IT mainstay, with the
rise of Big Data and analytics as important functions of an enterprise
organisation's bottom line, is there room to make a similar ‘DevOps-esque'
approach to the management, provisioning and governance of data?
This
- fundamentally - is what underpins the notion of DataOps, a concept of rising
relevance that makes a case for a more agile approach to a business's use of
data. DataOps - like DevOps - is an umbrella term describing a range of related
technologies and processes employed by an organisation to boost data
productivity and management.
Originally
coined in 2015, DataOps is now approaching its three year anniversary and has
been generating a fair amount of interest in recent years from a variety of
organisations. But just how much of that interest is translating to tangible
adoption and what does a successful DataOps approach look like?
What
is DataOps?
About
us
TMA Solutions was
established in 1997 to provide quality software outsourcing services to
leading companies worldwide. We are one of the largest software outsourcing
companies in Vietnam with 2,400 engineers. Our engineering team was selected
from a large pool of Vietnam IT resources; they are well-trained and have
successfully completed many large and complex projects.
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