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Big Data for Big Decisions - Building a Data-Driven Organization (Paperback)
Loot Price: R1,498
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Big Data for Big Decisions - Building a Data-Driven Organization (Paperback)
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Building a data-driven organization (DDO) is an enterprise-wide
initiative that may consume and lock up resources for the long
term. Understandably, any organization considering such an
initiative would insist on a roadmap and business case to be
prepared and evaluated prior to approval. This book presents a
step-by-step methodology in order to create a roadmap and business
case, and provides a narration of the constraints and experiences
of managers who have attempted the setting up of DDOs. The emphasis
is on the big decisions - the key decisions that influence 90% of
business outcomes - starting from decision first and reengineering
the data to the decisions process-chain and data governance, so as
to ensure the right data are available at the right time, every
time. Investing in artificial intelligence and data-driven decision
making are now being considered a survival necessity for
organizations to stay competitive. While every enterprise aspires
to become 100% data-driven and every Chief Information Officer
(CIO) has a budget, Gartner estimates over 80% of all analytics
projects fail to deliver intended value. Most CIOs think a
data-driven organization is a distant dream, especially while they
are still struggling to explain the value from analytics. They know
a few isolated successes, or a one-time leveraging of big data for
decision making does not make an organization data-driven. As of
now, there is no precise definition for data-driven organization or
what qualifies an organization to call itself data-driven. Given
the hype in the market for big data, analytics and AI, every CIO
has a budget for analytics, but very little clarity on where to
begin or how to choose and prioritize the analytics projects. Most
end up investing in a visualization platform like Tableau or
QlikView, which in essence is an improved version of their BI
dashboard that the organization had invested into not too long ago.
The most important stakeholders, the decision-makers, are rarely
kept in the loop while choosing analytics projects. This book
provides a fail-safe methodology for assured success in deriving
intended value from investments into analytics. It is a
practitioners' handbook for creating a step-by-step
transformational roadmap prioritizing the big data for the big
decisions, the 10% of decisions that influence 90% of business
outcomes, and delivering material improvements in the quality of
decisions, as well as measurable value from analytics investments.
The acid test for a data-driven organization is when all the big
decisions, especially top-level strategic decisions, are taken
based on data and not on the collective gut feeling of the decision
makers in the organization.
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