What’s driving 3rd-generation business intelligence?
The emergence of 3rd-generation business intelligence would not be possible without a series of technical
developments that have changed the data and analytics landscape:
DATA
In recent years, we’ve seen a massive
transformation in the volume, variety,
and velocity of data available, both
on-premises and increasingly in cloud
environments. This requires organizations
to have a comprehensive data integration
and management strategy.
MOBILE, IOT, AND EMBEDDED ANALYTICS
The explosion of mobile and IoT devices
has led to a tremendous uptick in the
amount of data being generated at the edge
of the enterprise. Naturally, organizations
want to analyze that data – including at the
edge. As a result, embedded analytics are
becoming increasingly important.
INFRASTRUCTURE + CLOUD
Data is now spread across on-premise and
multiple cloud sites, where organizations
need to access it, manage it, and analyze it.
At the same time, cloud infrastructure has
greatly accelerated our ability to scale, and
technologies like Kubernetes and Docker
are providing the compute power needed to
manage and analyze vast quantities of data.
ARTIFICIAL INTELLIGENCE
And finally, one of the most important
capabilities unlocking the third generation
of analytics is the development of Artificial
Intelligence. In the context of analytics, AI
leverages machine intelligence and learning
to provide insights, automation, and new
ways to interact with data, helping drive
data literacy across the organization.
HOW WE GOT HERE
CAUTION: BIG CLOUD
While the cloud has generally
been a positive development
for innovation – especially
in computer power, which
is critical for AI – many of
today's cloud vendors have
a vested interest in capturing
as much of their customers'
data as possible.
Beyond the Hype: How to Get Real Value from AI in Analytics Today 3
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